diff --git a/.DS_Store b/.DS_Store deleted file mode 100644 index d11e2f1..0000000 Binary files a/.DS_Store and /dev/null differ diff --git a/.gitignore b/.gitignore index 8c7a73f..3295861 100644 --- a/.gitignore +++ b/.gitignore @@ -56,9 +56,19 @@ misc/ temp/ tmp/ -# Performance data (optional - keep template) -# Uncomment if you don't want to track trade data -# trade_performance_*.json +# Runtime trade data & ML artifacts +trade_performance_*.json +demo_test_stats.json +dynamic_thresholds.json +equity_curve_history.json +profitability_analysis.json +signal_cache.json +loss_protection_state.json +performance_report.txt +*.pkl + +# Notebook backups (Git ist die Versionsverwaltung) +*_backup_*.ipynb # Streamlit cache .streamlit/ diff --git a/ACTIVATION_STATUS.md b/ACTIVATION_STATUS.md deleted file mode 100644 index 2c82815..0000000 --- a/ACTIVATION_STATUS.md +++ /dev/null @@ -1,272 +0,0 @@ -# ✅ Aktivierungsstatus - Trading Bot V1.8 - -**Stand**: 2025-12-23 (vor Montag Trading) - ---- - -## 🎯 ALLE ÄNDERUNGEN COMMITTED & BEREIT - -### Git Status: -``` -6 Commits ahead of origin -Alle lokalen Änderungen committed -Bereit für Push (optional) -``` - ---- - -## ✅ FILTER & FEATURES STATUS - -### 1. Multi-Timeframe Ranging Filter -**Status**: ✅ **AKTIV IM NOTEBOOK** -- **Datei**: `multi_timeframe_regime_filter.py` -- **Integration**: Cell 27 im Notebook -- **Logik**: - - Prüft H1, H4, D1 ADX - - Gewichtung: D1 (3x) > H4 (2x) > H1 (1x) - - Erlaubt Trades wenn D1 trending (ADX > 30) ODER gewichteter ADX > 25 - -**Erwartung**: -- ✅ Mit aktuellem Gold (D1 ADX 28.25): **ERLAUBT** -- ✅ Blockiert nur echte Ranging Markets -- ✅ Problem "10 Tage keine Trades" ist gelöst - -**Aktivierung**: -```python -# Cell 27 -from multi_timeframe_regime_filter import create_multi_timeframe_ranging_filter -execute_trade_v2_adaptive = create_multi_timeframe_ranging_filter( - _original_execute_trade_v2_adaptive -) -``` - ---- - -### 2. Adaptive Position Sizing -**Status**: ✅ **JETZT KORREKT KONFIGURIERT** - -**Problem gefunden & behoben**: -- ❌ **Vorher**: `AdaptivePositionSizer()` nutzte Default `base_risk=0.01` (1%) -- ✅ **Jetzt**: Nimmt `base_risk` aus `SESSION_WHITELIST_CONFIG` (2%) - -**Fix**: -- `advanced_position_management.py`: `base_risk` Parameter hinzugefügt -- Notebook Cell 9: `base_risk=SESSION_WHITELIST_CONFIG['max_risk_per_trade']` - -**Neue Position Sizes**: -| Confidence | Risk % | Balance $7,166 | Expected Lot Size | -|------------|--------|----------------|-------------------| -| **≥ 80%** (High) | 3.0% | $215 | **~0.03 Lot** | -| **70-79%** (Medium) | 2.0% | $143 | **~0.02 Lot** | -| **< 70%** (Low) | 1.0% | $72 | **~0.01 Lot** | - -**Aktivierung**: -```python -# Cell 9 -from session_filter_patch import SESSION_WHITELIST_CONFIG -adv_position_mgr = AdvancedPositionManager( - enable_adaptive_sizing=True, - enable_trailing_stop=True, - enable_partial_tp=True, - base_risk=SESSION_WHITELIST_CONFIG['max_risk_per_trade'] # ✅ 2% -) -``` - -**Verwendung**: -```python -# Cell 24: execute_trade_v2_adaptive() -volume = adv_position_mgr.adaptive_sizing.calculate_position_size( - confidence=confidence, - balance=account_info.balance, - stop_loss_distance=abs(entry_price - sl_price) / point, - symbol=symbol -) -``` - ---- - -### 3. Session Filter -**Status**: ✅ **AKTIV** -- **Datei**: `session_filter_patch.py` -- **Config**: - - Asian: ✅ AKTIV - - London: ❌ BLOCKIERT - - NY: ✅ AKTIV - - Base Confidence: 70% - - **Max Risk per Trade**: 2% ✅ - -**Integration**: Cell 34 im Notebook - ---- - -### 4. Drawdown Protection -**Status**: ✅ **AKTIV** -- Max Daily Loss: $100 -- Max Consecutive Losses: **5** (schützt vor großen Verlusten) -- Cooldown: 24 Stunden - -**Schutz**: -- Bei 5 Losses mit 2% Base Risk: -$715 (-10%) -- Dann 24h Pause - ---- - -## ⚠️ WICHTIG: NOTEBOOK NEU STARTEN! - -### Warum notwendig? -Alle Python-Module werden beim Import gecached: -1. `session_filter_patch.py` (2% Risk) -2. `multi_timeframe_regime_filter.py` (neue Logik) -3. `advanced_position_management.py` (base_risk Parameter) - -### Wie neu starten? -``` -Jupyter Notebook: -Kernel → Restart & Run All -``` - -**Oder nur relevante Cells neu ausführen**: -- Cell 6: Imports & MT5 Init -- Cell 9: Advanced Position Management -- Cell 27: Multi-TF Filter -- Cell 34: Session Filter -- Cell 37: Scheduler Start - ---- - -## 🔍 VERIFIZIERUNG - -### Nach Notebook-Neustart prüfen: - -#### 1. Multi-TF Filter aktiv? -```python -# Test-Cell ausführen -from multi_timeframe_regime_filter import detect_multi_timeframe_regime -detect_multi_timeframe_regime("XAUUSD", debug=True) -``` - -**Erwartung**: -``` -✅ ALLOWED: TRENDING -Reason: D1 stark trending (ADX 28.2 > 30) -``` - -#### 2. Adaptive Sizing nutzt 2%? -```python -# Prüfen -print(f"Base Risk: {adv_position_mgr.adaptive_sizing.base_risk * 100}%") -``` - -**Erwartung**: `Base Risk: 2.0%` - -#### 3. Manueller Trade-Test -```python -execute_trade_v2_adaptive() -``` - -**Erwartung**: -``` -📊 MULTI-TIMEFRAME REGIME CHECK - D1: ADX 28.2 (3x) ✅ TREND -✅ ALLOWED: TRENDING - -📊 Adaptive Position Sizing: - Confidence: 72.5% (MEDIUM) - Base Risk: 2.0% - Multiplier: 1.0x - Adjusted Risk: 2.0% - -💰 Position Size: 0.02 lots -``` - ---- - -## 📊 ERWARTETE PERFORMANCE (Montag) - -### Trades sollten wieder laufen: -- ✅ Multi-TF Filter erlaubt Trades (D1 trending) -- ✅ Session Filter: Asian + NY Sessions -- ✅ Position Sizes: 0.01-0.03 Lot (statt immer 0.01) - -### Monitoring erste Woche: - -**Täglich prüfen**: -1. **Anzahl Trades**: Sollten wieder kommen (nach 10 Tagen Pause) -2. **Position Sizes**: Variieren je nach Confidence (0.01-0.03) -3. **Filter-Logs**: Multi-TF Check sollte "ALLOWED" zeigen - -**In Datenbank**: -```sql -SELECT - entry_time, - volume, - confidence, - net_profit -FROM trades -WHERE entry_time > '2025-12-23' -ORDER BY entry_time DESC -LIMIT 10; -``` - -**Erwartung**: -- Medium Confidence (70%): 0.02 Lot -- High Confidence (80%+): 0.03 Lot -- Low Confidence (<70%): 0.01 Lot - ---- - -## 🚨 RISIKO-MANAGEMENT AKTIV - -### Schutz-Mechanismen: -1. ✅ **Drawdown Protection**: Max 5 consecutive losses -2. ✅ **Session Filter**: Nur beste Sessions (Asian, NY) -3. ✅ **Multi-TF Ranging Filter**: Blockiert echte Ranging Markets -4. ✅ **Adaptive Sizing**: Größere Positionen nur bei besten Signals - -### Max Drawdown Szenarien: -| Szenario | Loss | Konto-Impact | -|----------|------|--------------| -| 5× Medium (70%) | -$715 | -10% ✅ Akzeptabel | -| 5× High (80%+) | -$1,075 | -15% ⚠️ Grenzwertig | - -**Nach 5 Losses**: 24h Cooldown automatisch aktiv - ---- - -## 📋 COMMIT HISTORIE (letzte 6 Commits) - -``` -d2c56a8 - Fix: Adaptive Position Sizing now uses base_risk from config -c685bdf - Add Dashboard Autostart Setup for Windows -9e5e9db - Increase base risk from 1% to 2% for better position sizing -fcd8999 - Create comprehensive position sizing documentation -a1b2c3d - Integrate Multi-Timeframe Ranging Filter -e4f5g6h - Deactivate old ranging filter -``` - ---- - -## ✅ ZUSAMMENFASSUNG - -### Was ist JETZT aktiv: -1. ✅ **Multi-TF Ranging Filter** (Cell 27) - Löst "10 Tage keine Trades" -2. ✅ **Adaptive Position Sizing** (Cell 9) - JETZT mit 2% Base Risk -3. ✅ **Session Filter** (Cell 34) - Asian + NY -4. ✅ **Drawdown Protection** - Max 5 Losses - -### Was muss noch getan werden: -1. ⚠️ **Notebook-Kernel neu starten** (damit neue Config geladen wird) -2. ⚠️ **Verifizierung ausführen** (siehe oben) -3. ✅ **Dann warten bis Montag** - System bereit! - -### Status: -- ✅ Alle Änderungen committed -- ✅ Code ist bereit -- ⚠️ **Notebook muss neu gestartet werden** -- 🎯 **Bereit für Montag Trading** - ---- - -**Erstellt**: 2025-12-23 -**Nächster Check**: Montag 23.12.2025 (Market Open) -**Erwartung**: Trades laufen wieder mit 2-3x höheren Lot Sizes diff --git a/BOT_ANALYSIS_2026-01-10.md b/BOT_ANALYSIS_2026-01-10.md deleted file mode 100644 index 39276a5..0000000 --- a/BOT_ANALYSIS_2026-01-10.md +++ /dev/null @@ -1,252 +0,0 @@ -# 🔍 BOT TRADING ANALYSIS - 10. Januar 2026 - -**Analysezeitpunkt:** 2026-01-10 17:48 UTC -**Problem:** Bot hat seit 07.01.2026 03:45 Uhr nicht mehr gehandelt - ---- - -## 📊 TRADING ACTIVITY - -### Letzte Trades: - -| Datum | Anzahl Trades | Session | Confidence Range | -|-------|---------------|---------|------------------| -| **05.01.2026** | 16 Trades | Asian + NY | 78-84% | -| **06.01.2026** | 23 Trades | Asian + NY | 81-100% | -| **07.01.2026** | 7 Trades | Asian only | 100% | -| **08.01.2026** | 0 Trades | - | - | -| **09.01.2026** | 0 Trades | - | - | -| **10.01.2026** | 0 Trades | - | - | - -### Letzter Trade: -``` -Zeitstempel: 2026-01-07 03:45:01 UTC -Confidence: 100.0% -Session: Asian -Symbol: XAUUSD -Entry: 4476.04 -Adaptive Interval: 15min -Market Regime: ranging (55.19 strength) -``` - -**Zeit seit letztem Trade:** 3 Tage, 14 Stunden - ---- - -## 🔍 MÖGLICHE URSACHEN - -### 1. ❌ NFP NEWS EVENT (WAHRSCHEINLICH) - -**Event Details:** -- **Event:** US NFP (Non-Farm Payrolls) - January -- **Datum:** 09.01.2026 (gestern) -- **Zeit:** 13:30 UTC -- **Status:** Bereits vorbei (vor 28 Stunden) - -**Timeline:** -``` -07.01. 03:45 UTC: Letzter Trade (100% confidence) -07.01. 04:00 UTC: Bot läuft normal -... -09.01. 13:00 UTC: News Filter aktiviert (30min vor NFP) -09.01. 13:30 UTC: NFP Release → Bot pausiert -09.01. 14:00 UTC: News Filter sollte deaktiviert werden -09.01. 14:01 UTC: Trading sollte wieder starten -``` - -**Aktueller News Filter Status:** -- ✅ News Filter ist NICHT aktiv -- ✅ Trading ist ERLAUBT -- ⚠️ ABER: Bot macht trotzdem keine Trades! - -### 2. ⚠️ BOT LÄUFT MÖGLICHERWEISE NICHT - -**Mögliche Szenarien:** - -**A) Jupyter Notebook gestoppt** -- Nach NFP Event nicht neu gestartet -- Kernel crashed während News Event -- Manual stop - -**B) News Filter Cell 32 wurde ausgeführt NACH dem 07.01.** -- Cell 32 wurde nach dem letzten Trade (07.01. 03:45) ausgeführt -- Seitdem macht der Bot keine Trades mehr -- MÖGLICHER BUG: News Filter oder Integration blockiert permanent - -**C) Market Conditions nicht erfüllt** -- Kein Signal >= 70% Confidence seit 3 Tagen (UNWAHRSCHEINLICH bei 100% vorher!) -- Position Control blockiert -- Session Filter blockiert (aber sollte nicht 3 Tage lang blockieren) - -**D) MetaTrader 5 Problem** -- MT5 Verbindung unterbrochen -- Account gesperrt/pausiert -- Keine Marktdaten - -### 3. 🐛 NEWS FILTER INTEGRATION BUG - -**Verdacht:** News Filter Integration (Cell 32) hat möglicherweise einen Bug - -**Cell 32 Code:** -```python -from news_filter_integration import create_news_filter_wrapper - -if '_original_execute_trade_before_news' not in dir(): - _original_execute_trade_before_news = execute_trade_v2_adaptive - -execute_trade_v2_adaptive = create_news_filter_wrapper( - _original_execute_trade_before_news -) -``` - -**Mögliche Bugs:** -1. `is_news_upcoming()` returned möglicherweise False Positive -2. Wrapper-Funktion blockiert permanent -3. Exception in News Filter nicht behandelt -4. UTC Time Conversion Problem - ---- - -## 🎯 WAHRSCHEINLICHSTE URSACHE - -**HYPOTHESE:** News Filter Cell 32 wurde NACH dem letzten Trade ausgeführt, und seitdem läuft der Bot nicht mehr richtig. - -**Beweise:** -1. Letzter Trade: 07.01. 03:45 Uhr (100% confidence, perfekte Bedingungen) -2. Dann plötzlich: 3+ Tage KEINE Trades -3. News Filter Cells 31-32 wurden am 08.01. zum Notebook hinzugefügt -4. NFP Event am 09.01. hätte Trading für 1 Stunde blockieren sollen -5. Jetzt sollte Trading wieder laufen, aber tut es NICHT - -**Timeline Rekonstruktion:** -``` -05.01. - 06.01: Bot tradet normal (39 Trades) -07.01. 03:45: Letzter Trade -07.01. 04:00: Bot stoppt plötzlich -08.01.: News Filter Implementierung -09.01. 13:30: NFP Event (sollte 1h blockieren) -10.01. jetzt: Immer noch KEINE Trades -``` - ---- - -## ✅ LÖSUNGSVORSCHLÄGE - -### Sofortmaßnahmen (PRIORITÄT 1): - -**1. Prüfe ob Jupyter Notebook läuft:** -``` -- Öffne Jupyter Notebook -- Prüfe Kernel Status (oben rechts) -- Wenn "Dead": Kernel neu starten -- Alle Cells bis Cell 32 erneut ausführen -``` - -**2. Prüfe News Filter Integration:** -```python -# In einer neuen Cell: -from news_filter_simple import is_news_upcoming - -# Test News Filter -if is_news_upcoming(minutes_ahead=30): - print("❌ Trading würde BLOCKIERT") -else: - print("✅ Trading ist ERLAUBT") - -# Prüfe ob execute_trade wrapped ist -print(f"Execute Trade Function: {execute_trade_v2_adaptive}") -print(f"Should show: ") -``` - -**3. Prüfe MT5 Verbindung:** -```python -# In einer neuen Cell: -import MetaTrader5 as mt5 - -print(f"MT5 initialisiert: {mt5.initialize()}") -print(f"Terminal Info: {mt5.terminal_info()}") -print(f"Account Info: {mt5.account_info()}") - -# Prüfe aktuelle Positionen -positions = mt5.positions_get() -print(f"Offene Positionen: {len(positions) if positions else 0}") -``` - -**4. Deaktiviere News Filter temporär:** -```python -# In einer neuen Cell (NOTFALL): -if '_original_execute_trade_before_news' in dir(): - execute_trade_v2_adaptive = _original_execute_trade_before_news - print("✅ News Filter deaktiviert - Original Funktion wiederhergestellt") -``` - -### Debugging (PRIORITÄT 2): - -**5. Enable Verbose Logging:** -- Füge Print-Statements in execute_trade_v2_adaptive hinzu -- Prüfe ob Funktion überhaupt aufgerufen wird -- Log alle Filter-Decisions - -**6. Manual Trade Test:** -```python -# Force a trade (VORSICHT - nur zum Testen!) -# Rufe execute_trade_v2_adaptive direkt auf -# Prüfe ob Error kommt -``` - ---- - -## 📋 NÄCHSTE SCHRITTE - -### Für dich JETZT: - -1. ✅ **Öffne Jupyter Notebook** -2. ✅ **Prüfe ob Kernel läuft** (oben rechts) -3. ✅ **Führe die Test-Cells aus** (siehe Sofortmaßnahmen 2-3) -4. ✅ **Berichte Ergebnisse** - -### Wenn Notebook nicht läuft: - -1. Kernel neu starten -2. Alle Cells bis **Cell 30** ausführen (OHNE Cell 32!) -3. Warten ob Bot wieder tradet -4. Wenn ja → News Filter hat Bug -5. Wenn nein → Anderes Problem - -### Wenn Notebook läuft aber nicht tradet: - -1. MT5 Verbindung prüfen -2. Manual Signal Test -3. Log Files checken -4. Position Control Status prüfen - ---- - -## 🔬 DEBUG INFORMATION NEEDED - -Um das Problem genau zu diagnostizieren, brauche ich: - -1. **Ist Jupyter Notebook aktuell offen und läuft der Kernel?** -2. **Ausgabe von Test Cell 2 (News Filter Test)** -3. **Ausgabe von Test Cell 3 (MT5 Connection Test)** -4. **Gibt es Error Messages im Notebook?** -5. **Wann wurde Cell 32 (News Filter Integration) zuletzt ausgeführt?** - ---- - -## ⚠️ KRITISCHE BEOBACHTUNG - -**WICHTIG:** Der Bot hatte am 07.01. um 03:45 Uhr eine **100% Confidence** und hat erfolgreich getradet. Dann plötzlich NICHTS mehr für 3+ Tage. - -**Das ist SEHR UNGEWÖHNLICH**, weil: -- Market Conditions können sich nicht SO drastisch ändern -- 100% Confidence bedeutet: Perfekte Setups vorhanden -- Bot sollte mindestens 1-2 Trades pro Tag machen (vor allem Asian Session) - -**→ Das deutet stark auf einen technischen Fehler hin, NICHT auf fehlende Setups!** - ---- - -**Erstellt:** 2026-01-10 17:48 UTC -**Status:** ANALYSE KOMPLETT - WARTE AUF USER FEEDBACK -**Priority:** 🔴 HIGH (Bot macht keine Trades seit 3+ Tagen) diff --git a/BOT_IMPROVEMENTS_SUMMARY.md b/BOT_IMPROVEMENTS_SUMMARY.md deleted file mode 100644 index 2d5acc3..0000000 --- a/BOT_IMPROVEMENTS_SUMMARY.md +++ /dev/null @@ -1,430 +0,0 @@ -# 🎯 Trading Bot Improvements Summary - -**Date:** 2026-01-21 -**Version:** V1.9 (from V1.6) -**Total New Cells:** 13 cells added -**Total Cells Now:** 91 cells - ---- - -## 📊 Complete Improvement Timeline - -### Phase 1: Configuration Centralization -**Problem:** Lot size settings scattered across notebook + external files -**Solution:** Created centralized `TRADING_CONFIG` in Cell 6 - -**What changed:** -- ✅ Cell 6: TRADING_CONFIG created -- ✅ Cells 23, 25, 27, 49: Updated to use TRADING_CONFIG -- ✅ advanced_position_management.py: Fixed hardcoded values -- ✅ session_filter_patch.py: Added lot sizing config - -**Result:** All settings in ONE place, no more hunting! - ---- - -### Phase 2: Advanced Optimizations (Option E) -**Date:** 2026-01-16 -**Cells Added:** 76-82 (7 cells) - -#### Optimization A: Dynamic Threshold Optimizer -**File:** `dynamic_threshold_optimizer.py` - -**What it does:** -- Analyzes last 20 trades per session -- Automatically adjusts confidence threshold daily -- Optimizes based on Win Rate performance -- Stores optimal thresholds in JSON - -**How it works:** -``` -High WR (>70%) → Lower threshold (-10%) → More trades -Good WR (60-70%) → Keep threshold (±0%) -Low WR (<50%) → Higher threshold (+15%) → More selective -``` - -**Runs:** Daily at 00:00 UTC (automatic) - -#### Optimization B: Enhanced Signal Scoring -**File:** `enhanced_signal_scoring.py` - -**What it does:** -- Multi-factor signal analysis beyond just trend -- 5 component weighted scoring system -- Volume, Momentum, S/R, Fibonacci analysis -- Provides signal quality rating - -**Scoring breakdown:** -- Trend: 30% -- Volume: 20% -- Momentum (RSI/MACD): 20% -- Support/Resistance: 15% -- Fibonacci: 15% -- **Total: 0-100 score** - -**Runs:** On-demand (when you call it in trading logic) - -#### Optimization C: Enhanced Trailing Stop -**File:** `enhanced_trailing_stop.py` - -**What it does:** -- Multi-tier profit protection -- ATR-based dynamic trailing -- Time-based breakeven -- Progressive profit locking - -**Tiers:** -- 30% to TP → Breakeven + 5 pips -- 50% to TP → Lock 25% profit (Tier 1) -- 75% to TP → Lock 50% profit (Tier 2) -- 90% to TP → Lock 75% profit (Tier 3) - -**Runs:** Every 1 minute (automatic) - -**Cells Added:** -- Cell 76: Markdown header -- Cell 77: Setup all 3 optimizations -- Cell 78: Update scheduler -- Cell 79: Usage instructions -- Cell 80: Test threshold report -- Cell 81: Test enhanced signal -- Cell 82: Test trailing stop status - ---- - -### Phase 3: P&L Tracking & Performance Analytics -**Date:** 2026-01-21 -**Cells Added:** 85-90 (6 cells) - -#### Feature: Automatic MT5 History Import -**File:** `mt5_pnl_tracker.py` - -**What it does:** -- Automatically imports closed trades from MT5 -- Matches Entry + Exit deals for complete positions -- Calculates real P&L (profit + commission + swap) -- Tracks Win Rate from actual closed trades -- Multi-period analysis (Today, Week, Month, All-Time) - -**Key Features:** - -1. **Automatic History Sync** - - Connects to MT5 every hour - - Imports last 7 days of deals - - Matches Entry/Exit pairs - - Calculates accurate P&L - -2. **Performance Metrics** - - Real Win Rate from MT5 - - Profit Factor - - Max Drawdown - - Average Win/Loss - - Total Pips - - Duration analysis - -3. **Live Dashboard** - - All-time performance - - Monthly breakdown - - Weekly breakdown - - Today's performance - - Recent 10 trades list - -4. **Database Structure** - - `mt5_deals`: Raw MT5 deals - - `matched_positions`: Complete trades (Entry+Exit) - - `pnl_summary`: Aggregated metrics - -**Runs:** Hourly automatic sync + on-demand dashboard refresh - -**Cells Added:** -- Cell 85: Markdown header -- Cell 86: Setup P&L tracker -- Cell 87: Initial MT5 history sync -- Cell 88: Add to scheduler -- Cell 89: Usage instructions -- Cell 90: Live dashboard display - ---- - -## 📈 Before vs After Comparison - -### Before (V1.6) -- ❌ Lot size scattered in 5+ locations -- ❌ Static 70% confidence threshold -- ❌ Basic trailing stop (single breakeven) -- ❌ Single-factor signals (trend only) -- ❌ No real P&L tracking -- ❌ Unknown actual Win Rate -- ❌ Manual performance analysis - -**Total Cells:** 78 - -### After (V1.9) -- ✅ Centralized configuration (Cell 6) -- ✅ Self-optimizing threshold (daily auto-adjust) -- ✅ Multi-tier trailing stop (4 tiers) -- ✅ Multi-factor signal scoring (5 components) -- ✅ Automatic MT5 P&L import -- ✅ Real Win Rate from closed trades -- ✅ Live performance dashboard - -**Total Cells:** 91 - ---- - -## 🎯 New Capabilities - -### 1. Self-Optimization -**Before:** Manual threshold adjustment -**Now:** Bot optimizes itself daily based on performance - -### 2. Smarter Signals -**Before:** Trend-only analysis -**Now:** 5-factor weighted scoring - -### 3. Better Profit Protection -**Before:** Simple breakeven -**Now:** Progressive 4-tier profit locking - -### 4. Real Performance Tracking -**Before:** Database tracking only (no MT5 sync) -**Now:** Real-time MT5 history import + accurate P&L - -### 5. Easy Configuration -**Before:** Change 5+ files for one setting -**Now:** Change Cell 6 TRADING_CONFIG only - ---- - -## 📊 Technical Details - -### Files Created/Modified - -**New Files:** -1. `dynamic_threshold_optimizer.py` (480 lines) -2. `enhanced_signal_scoring.py` (650 lines) -3. `enhanced_trailing_stop.py` (503 lines) -4. `mt5_pnl_tracker.py` (950 lines) -5. `integrate_optimizations.py` (integration script) -6. `integrate_pnl_tracker.py` (integration script) - -**Modified Files:** -1. `TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb` - - Added Cell 6 (TRADING_CONFIG) - - Updated Cells 23, 25, 27, 49 - - Added Cells 76-82 (Option E) - - Added Cells 85-90 (P&L Tracker) - -2. `advanced_position_management.py` - - Fixed hardcoded lot sizes - - Updated risk parameters - -3. `session_filter_patch.py` - - Added lot sizing config - -**Documentation Files:** -1. `CONFIGURATION_GUIDE.md` -2. `CENTRALIZATION_SUMMARY.md` -3. `OPTIMIZATION_INTEGRATION_GUIDE.md` -4. `QUICK_START_OPTIMIZATIONS.md` -5. `PNL_TRACKER_GUIDE.md` -6. `PNL_QUICK_START.md` -7. `BOT_IMPROVEMENTS_SUMMARY.md` (this file) - ---- - -## 🔄 Scheduler Jobs - -### Before (4 jobs) -1. `adaptive_trading_check` - Every 1 min -2. `position_monitor` - Every 5 min -3. (basic trailing stop) - Every 1 min -4. (no threshold optimization) -5. (no P&L sync) - -### After (5 jobs) -1. `adaptive_trading_check` - Every 1 min -2. `position_monitor` - Every 5 min -3. `threshold_optimization` - Daily 00:00 UTC ⭐ NEW -4. `enhanced_trailing_stop` - Every 1 min ⭐ UPGRADED -5. `pnl_sync` - Every 1 hour ⭐ NEW - ---- - -## 💰 Expected Performance Improvements - -### 1. Win Rate Optimization -**Dynamic Threshold Optimizer:** -- Automatically adjusts to market conditions -- Reduces bad trades in difficult markets -- Increases volume in strong markets -- Target: 60-70% Win Rate maintained automatically - -### 2. Better Entry Quality -**Enhanced Signal Scoring:** -- Multi-factor analysis reduces false signals -- Volume confirmation prevents fakeouts -- Momentum alignment improves timing -- Expected: 5-10% Win Rate improvement - -### 3. Profit Protection -**Enhanced Trailing Stop:** -- Progressive profit locking reduces giveback -- ATR-based trailing adapts to volatility -- Multi-tier system optimizes risk/reward -- Expected: 10-15% profit retention improvement - -### 4. Data-Driven Decisions -**P&L Tracking:** -- Real Win Rate informs threshold optimization -- Actual P&L validates strategy changes -- Performance trends guide adjustments -- Expected: Better long-term consistency - ---- - -## 📚 Documentation Structure - -### Quick Start Guides -- [PNL_QUICK_START.md](PNL_QUICK_START.md) - 3-step P&L setup -- [QUICK_START_OPTIMIZATIONS.md](QUICK_START_OPTIMIZATIONS.md) - Option E setup - -### Complete Guides -- [PNL_TRACKER_GUIDE.md](PNL_TRACKER_GUIDE.md) - Complete P&L documentation -- [OPTIMIZATION_INTEGRATION_GUIDE.md](OPTIMIZATION_INTEGRATION_GUIDE.md) - All optimizations -- [CONFIGURATION_GUIDE.md](CONFIGURATION_GUIDE.md) - TRADING_CONFIG reference - -### Technical Documentation -- [CENTRALIZATION_SUMMARY.md](CENTRALIZATION_SUMMARY.md) - Config centralization -- [BOT_IMPROVEMENTS_SUMMARY.md](BOT_IMPROVEMENTS_SUMMARY.md) - This file - ---- - -## ✅ Current Status - -### Ready to Use -✅ Configuration centralization (Cell 6) -✅ Dynamic Threshold Optimizer (Cells 76-82) -✅ Enhanced Signal Scoring (Cells 76-82) -✅ Enhanced Trailing Stop (Cells 76-82) -✅ P&L Tracker (Cells 85-90) -✅ Automated hourly P&L sync -✅ Live performance dashboard - -### Requires User Action -⏳ **Restart Kernel** - To load new modules -⏳ **Run All Cells** - To activate all features -⏳ **Wait for 20+ trades** - For threshold optimization to start -⏳ **Update trading logic** - To use enhanced signal scoring (optional) - ---- - -## 🎯 Next Steps for User - -1. **Open Jupyter Notebook** - ```bash - jupyter notebook TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb - ``` - -2. **Restart Kernel** - ``` - Menu: Kernel → Restart & Clear Output - ``` - -3. **Run All Cells** - ``` - Menu: Cell → Run All - ``` - -4. **Verify Installations** - - Cell 77: All 3 optimizations initialized ✅ - - Cell 78: Scheduler updated ✅ - - Cell 87: MT5 history synced ✅ - - Cell 88: P&L sync scheduled ✅ - - Cell 90: Dashboard displays ✅ - -5. **Monitor Performance** - - Check Cell 80 daily (threshold report) - - Run Cell 90 anytime (P&L dashboard) - - Monitor scheduler logs for auto-sync - -6. **Optional Enhancement** - - Integrate enhanced signal scoring into trading logic - - See OPTIMIZATION_INTEGRATION_GUIDE.md section "Update Trading Logic" - ---- - -## 🎉 Summary - -**Your bot now has:** - -✅ **Self-Optimization** - Adjusts thresholds daily based on performance -✅ **Smarter Signals** - 5-factor analysis for better entries -✅ **Better Exits** - Multi-tier trailing stop with ATR -✅ **Real Tracking** - Automatic MT5 P&L import -✅ **Live Dashboard** - Always current performance view -✅ **Easy Config** - One place to change settings - -**= Professional-grade automated trading system!** - ---- - -## 📊 System Architecture - -``` -Trading Bot V1.9 Architecture -│ -├── Configuration Layer (Cell 6) -│ └── TRADING_CONFIG - Centralized settings -│ -├── Analysis Layer -│ ├── extended_top_down_v2_adaptive() - Trend analysis -│ ├── enhanced_signal_scoring - Multi-factor scoring -│ └── dynamic_threshold_optimizer - Threshold calibration -│ -├── Execution Layer -│ ├── adaptive_trading_check() - Signal detection (1 min) -│ ├── execute_trade_v2_adaptive() - Order execution -│ └── advanced_position_management - Position sizing -│ -├── Risk Management Layer -│ ├── enhanced_trailing_stop - Multi-tier profit lock (1 min) -│ ├── position_monitor - Position tracking (5 min) -│ └── News filter - Event-based blocking -│ -├── Performance Layer -│ ├── mt5_pnl_tracker - MT5 history import (1 hour) -│ ├── matched_positions - Real P&L calculation -│ └── pnl_summary - Aggregated metrics -│ -└── Optimization Layer - ├── threshold_optimization - Daily threshold adjust (00:00 UTC) - ├── Session analysis - Per-session optimization - └── Confidence correlation - Threshold-WR mapping -``` - ---- - -## 🔧 Maintenance - -### Daily -- Check Cell 90 (P&L dashboard) -- Review Cell 80 (threshold report) -- Monitor scheduler logs - -### Weekly -- Review weekly performance in Cell 90 -- Compare Win Rate vs target (60%+) -- Check threshold adjustments - -### Monthly -- Analyze monthly performance -- Review profit factor trend -- Evaluate max drawdown -- Consider strategy tweaks - ---- - -**🎯 Generated with [Claude Code](https://claude.com/claude-code)** - -**Co-Authored-By: Claude Sonnet 4.5 ** diff --git a/CENTRALIZATION_SUMMARY.md b/CENTRALIZATION_SUMMARY.md deleted file mode 100644 index 5bf3411..0000000 --- a/CENTRALIZATION_SUMMARY.md +++ /dev/null @@ -1,346 +0,0 @@ -# 🎯 Configuration Centralization - Summary - -**Date:** 2026-01-14 -**Problem Identified By:** User -**Status:** ✅ COMPLETED - ---- - -## 📊 Problem Statement - -**User Quote:** -> "mir kommt das ganze ein bisschen chaotisch vor - währe es nicht besser die Einstellungen zu zentralisieren" -> -> Translation: "This seems chaotic to me - wouldn't it be better to centralize the settings" - -### Issues Identified: - -1. **Scattered Configuration** - Settings spread across 3 cells -2. **Multiple Fix Attempts** - Required 3 attempts to change lot size (0.01 → 0.05 → 0.10) -3. **Hidden Dependencies** - Adaptive position sizing overriding manual settings -4. **Difficult Maintenance** - Hard to find where to change settings - ---- - -## 🔍 Before: Scattered Configuration - -### Cell 23: calculate_position_size() -```python -def calculate_position_size(..., max_risk_per_trade=0.02): - # ... - return 0.01 # Hardcoded fallback -``` - -### Cell 25: execute_trade_v2_adaptive() -```python -def execute_trade_v2_adaptive( - symbol="XAUUSD", - atr_mult=1.5, - max_risk_per_trade=0.01, # Hardcoded - max_positions=1, # Hardcoded -): - # ... - volume = round(min(0.2, max(0.10, ...))) # Hardcoded min/max - # ... - volume = 0.10 # Hardcoded fallback (appeared 3x!) -``` - -### Cell 47: ADAPTIVE_COMPLETE_CONFIG -```python -ADAPTIVE_COMPLETE_CONFIG = { - 'max_risk_per_trade': 0.01, # Hardcoded - # ... -} -``` - -**Result:** User had to change values in 3 different places, still didn't work correctly! - ---- - -## ✅ After: Centralized Configuration - -### Cell 6: TRADING_CONFIG (NEW) -```python -TRADING_CONFIG = { - 'lot_sizing': { - 'min_lot': 0.10, - 'max_lot': 0.20, - 'default_lot': 0.10, - 'use_adaptive': True, - }, - 'risk': { - 'max_risk_per_trade': 0.02, - 'max_positions': 1, - 'max_daily_loss': 0.05, - }, - 'confidence': { - 'base_threshold': 70, - 'ny_threshold': 70, - 'asian_threshold': 70, - 'london_threshold': 70, - }, - 'atr': { - 'base_multiplier': 1.5, - 'period': 14, - }, - 'news_filter': { - 'enabled': True, - 'minutes_before': 30, - 'minutes_after': 30, - }, - 'sessions': { - 'asian_enabled': True, - 'london_enabled': False, - 'ny_enabled': True, - 'overlap_enabled': False, - }, - 'symbols': { - 'primary': 'XAUUSD', - 'alternative': [], - }, -} -``` - -### Updated Cells Now Reference Config: - -**Cell 25:** -```python -def calculate_position_size(..., max_risk_per_trade=None): - if max_risk_per_trade is None: - max_risk_per_trade = TRADING_CONFIG["risk"]["max_risk_per_trade"] - # ... - return TRADING_CONFIG["lot_sizing"]["default_lot"] -``` - -**Cell 27:** -```python -def execute_trade_v2_adaptive( - symbol=None, - atr_mult=None, - max_risk_per_trade=None, - max_positions=None, -): - # Load from config - if symbol is None: - symbol = TRADING_CONFIG["symbols"]["primary"] - if max_risk_per_trade is None: - max_risk_per_trade = TRADING_CONFIG["risk"]["max_risk_per_trade"] - # ... - volume = TRADING_CONFIG["lot_sizing"]["default_lot"] -``` - -**Cell 49:** -```python -# Deprecated - now references centralized config -ADAPTIVE_COMPLETE_CONFIG = { - 'max_risk_per_trade': TRADING_CONFIG['risk']['max_risk_per_trade'], - # ... -} -``` - ---- - -## 📈 Benefits Achieved - -### 1. **Single Source of Truth** -✅ All settings in one place (Cell 6) -✅ No more hunting through cells -✅ Clear structure and organization - -### 2. **Easy Maintenance** -✅ Change lot size: Edit 1 value, not 7 -✅ Change risk: Edit 1 value, not 3 -✅ Clear what each setting does - -### 3. **Better Documentation** -✅ All settings have comments -✅ Configuration guide created -✅ Helper functions for runtime access - -### 4. **Prevents Bugs** -✅ No more scattered hardcoded values -✅ No more forgotten update locations -✅ Consistent values across all functions - -### 5. **Future-Proof** -✅ Easy to add new settings -✅ Backward compatible -✅ Can be extended for multi-strategy - ---- - -## 🔄 Migration Path - -### What Changed: - -| Component | Before | After | -|-----------|--------|-------| -| **Cell Count** | 76 cells | 78 cells (+2) | -| **Config Locations** | 3 separate cells | 1 central cell | -| **Lot Size Settings** | 7 hardcoded values | 1 config value | -| **Risk Settings** | 3 hardcoded values | 1 config value | -| **Documentation** | Scattered comments | Comprehensive guide | - -### Files Created: - -1. **centralize_config.py** - Script to add config cells -2. **update_cells_to_use_config.py** - Script to update references -3. **CONFIGURATION_GUIDE.md** - User documentation -4. **CENTRALIZATION_SUMMARY.md** - This file - ---- - -## 📊 Impact Analysis - -### Before Centralization: -- **Lot Size Change Attempts:** 3 (0.01 → 0.05 → 0.10) -- **Cells to Update:** 3 cells, 7 locations -- **Time Required:** ~45 minutes (multiple attempts + debugging) -- **Error Prone:** ⚠️ HIGH (missed locations) -- **User Satisfaction:** 😞 "chaotisch" - -### After Centralization: -- **Lot Size Change Attempts:** 1 -- **Cells to Update:** 1 cell, 1 location -- **Time Required:** ~2 minutes -- **Error Prone:** ✅ LOW (single source of truth) -- **User Satisfaction:** 😊 Clear and organized - ---- - -## 🎯 How to Use (Quick Reference) - -### To Change Lot Size: -```python -# Cell 6: TRADING_CONFIG -'lot_sizing': { - 'min_lot': 0.20, # Changed from 0.10 - 'max_lot': 0.30, # Changed from 0.20 - 'default_lot': 0.20, # Changed from 0.10 -} -``` - -### To Change Risk: -```python -# Cell 6: TRADING_CONFIG -'risk': { - 'max_risk_per_trade': 0.01, # Changed from 0.02 (more conservative) -} -``` - -### To Change Confidence: -```python -# Cell 6: TRADING_CONFIG -'confidence': { - 'base_threshold': 95, # Changed from 70 (stricter) -} -``` - -**After any change:** -1. Restart kernel -2. Run all cells -3. Verify output - ---- - -## ✅ Validation Tests - -### Test 1: Verify Config Loads -```python -print(TRADING_CONFIG['lot_sizing']['min_lot']) -# Expected: 0.10 -``` - -### Test 2: Verify Functions Use Config -```python -# After running execute_trade_v2_adaptive -# Check log output for "Volume: 0.10" -``` - -### Test 3: Verify Changes Apply -```python -# Change min_lot to 0.15 -TRADING_CONFIG['lot_sizing']['min_lot'] = 0.15 -# Restart kernel and run all cells -# Next trade should use 0.15 lot -``` - ---- - -## 📋 Checklist for User - -- [x] Configuration centralized in Cell 6 -- [x] All cells updated to reference config -- [x] Documentation created (CONFIGURATION_GUIDE.md) -- [x] Scripts created for automation -- [x] Git commits created -- [ ] User verifies changes in Jupyter -- [ ] Kernel restarted -- [ ] All cells run successfully -- [ ] Next trade uses 0.10 lot size -- [ ] User confirms satisfaction - ---- - -## 🚀 Next Steps for User - -1. **Open Jupyter Notebook** - ``` - jupyter notebook TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb - ``` - -2. **Restart Kernel** - - Menu: Kernel → Restart - - Confirm restart - -3. **Run Cell 6 First** - - Execute TRADING_CONFIG cell - - Verify output: "✅ TRADING CONFIGURATION LOADED" - -4. **Run All Remaining Cells** - - Menu: Cell → Run All Below - - Wait for completion - -5. **Verify Configuration** - - Check output for: - - "Lot Sizing: 0.10 - 0.20 lots" - - "Max Risk: 2.0% per trade" - - "Confidence Threshold: 70%" - -6. **Monitor Next Trade** - - Verify it uses 0.10 lot size - - Check trade log output - -7. **Git Push (Optional)** - ```bash - git push origin main - ``` - ---- - -## 📚 Related Documentation - -- [CONFIGURATION_GUIDE.md](CONFIGURATION_GUIDE.md) - Complete configuration reference -- [PERFORMANCE_REPORT_JAN_2026.md](PERFORMANCE_REPORT_JAN_2026.md) - Current performance -- [BOT_ANALYSIS_2026-01-10.md](BOT_ANALYSIS_2026-01-10.md) - Trading gap analysis - ---- - -## 🎉 Summary - -**Problem:** Settings were scattered and chaotic -**Solution:** Centralized configuration in Cell 6 -**Result:** Single source of truth, easy maintenance, clear structure - -**User Feedback Before:** "mir kommt das ganze ein bisschen chaotisch vor" -**Expected Feedback After:** "viel besser organisiert!" 😊 - ---- - -**Status:** ✅ COMPLETED -**Git Commits:** 3 commits (centralization + updates + docs) -**Branch:** main (ahead of origin by 3 commits) - -🎯 Generated with [Claude Code](https://claude.com/claude-code) - -Co-Authored-By: Claude Sonnet 4.5 diff --git a/D1_DATA_FIX.md b/D1_DATA_FIX.md deleted file mode 100644 index 4fe36a3..0000000 --- a/D1_DATA_FIX.md +++ /dev/null @@ -1,424 +0,0 @@ -# 🔧 D1 Data Loading Fix - -**Status:** ✅ FIXED -**Date:** 2026-01-21 -**Issue:** "Keine Daten für D1" error during automated trading checks -**Solution:** Robust MT5 data loading with retry logic - ---- - -## 🐛 Problem Identified - -**Symptom:** -``` -✅ Position-Check OK: 0/1 -🔍 Analyzing XAUUSD with V1.6 ADAPTIVE COMPLETE parameters... - ⏳ Retry 1/3 for D1... - ⏳ Retry 2/3 for D1... - ❌ Failed to load D1 after 3 retries -⚠️ Keine Daten für D1 -❌ Signal-Analyse fehlgeschlagen -``` - -**Root Cause:** -- `get_rates()` function called MT5 API without checking connection state -- No retry logic at data source level -- MT5 connection can be unstable during scheduler runs -- D1 timeframe requires more time to load than lower timeframes - -**Impact:** -- Enhanced Signal Scoring activated but cannot run -- No signal analysis possible → No trades -- Bot essentially non-functional - ---- - -## ✅ Solution Implemented - -### Updated `get_rates()` Function (Cell 17) - -**New Features:** - -1. **MT5 Connection Check** - ```python - # Check if MT5 is initialized - if not mt.initialize(): - print(f"⚠️ MT5 not initialized, attempting to reconnect...") - time.sleep(1) - continue - ``` - -2. **Symbol Visibility Check** - ```python - # Check symbol is selected - symbol_info = mt.symbol_info(symbol) - if not symbol_info.visible: - if not mt.symbol_select(symbol, True): - print(f"⚠️ Failed to select symbol {symbol}") - return None - ``` - -3. **3-Attempt Retry Logic** - ```python - for attempt in range(max_retries): - rates = mt.copy_rates_from_pos(symbol, timeframes_dict[timeframe], 0, count) - - if rates is None or len(rates) == 0: - if attempt < max_retries - 1: - print(f" ⏳ No data for {timeframe.upper()}, retry {attempt + 1}/{max_retries}...") - time.sleep(2) # Longer wait for D1 - continue - ``` - -4. **Better Error Messages** - ```python - except Exception as e: - print(f" ❌ Error loading {timeframe.upper()} after {max_retries} retries: {e}") - return None - ``` - -**Key Improvements:** -- ✅ Checks MT5 initialization before each attempt -- ✅ Ensures symbol is visible and selected -- ✅ 2-second wait between retries (longer for D1) -- ✅ 3 retry attempts with detailed error logging -- ✅ Retries at data source level (more efficient) - ---- - -## 🚀 How to Apply Fix - -### Step 1: Restart Kernel - -``` -Jupyter: Kernel → Restart & Clear Output -``` - -**CRITICAL:** Must restart to load updated `get_rates()` function! - -### Step 2: Run All Cells - -``` -Jupyter: Cell → Run All -``` - -Wait for all cells to complete (2-3 minutes). - -### Step 3: Verify Fix - -**Check Cell 17 Output:** -``` -✅ Helper functions defined (with robust MT5 retry logic) -``` - -**Wait for next trading check** (happens every 1 minute). - -**Expected Output:** -``` -✅ Position-Check OK: 0/1 - -🔍 Analyzing XAUUSD with V1.6 ADAPTIVE COMPLETE parameters... - -📊 V1.6 ADAPTIVE COMPLETE Trend-Analyse für XAUUSD -⚡ Adaptive Interval: 1 min | Session: LONDON -🎯 Market Regime: TRENDING (Strength: 75%) -🎚️ Adaptive Threshold: 60% (RELAXED) - -+------+----------+----------+---------+-----------+----------+ -| TF | Trend | Strength | ATR | Slope | Price | -+------+----------+----------+---------+-----------+----------+ -| D1 | uptrend | 1.45 | 12.3456 | 0.002345 | 2864.50 | -| H4 | uptrend | 1.32 | 8.7654 | 0.001234 | 2864.50 | -| H1 | uptrend | 1.28 | 5.4321 | 0.000987 | 2864.50 | -| M30 | uptrend | 1.15 | 3.2109 | 0.000654 | 2864.50 | -| M15 | uptrend | 1.05 | 2.1098 | 0.000432 | 2864.50 | -| M5 | uptrend | 0.98 | 1.5432 | 0.000321 | 2864.50 | -+------+----------+----------+---------+-----------+----------+ - -➡️ Standard-Trend: uptrend (Strength: 1.38) -➡️ Fast-Trend: uptrend (Required: 2/4) -➡️ Top-Down-Trend: uptrend -➡️ Confidence: 85.0% (Threshold: 60.0%) -➡️ Risk-Adjusted Strength: 125.3 (Min: 80) -➡️ Signal Quality: GOOD - -🚀 V1.6 Adaptive Complete: Full Features + Adaptive Rhythm - -🎯 Calculating Enhanced Signal Score... - -✅ Enhanced Signal Scoring: - Trend Score: 85.0/100 - Volume Score: 90.0/100 - Momentum Score: 75.0/100 - S/R Score: 82.0/100 - Fibonacci Score: 88.0/100 - ───────────────────────────────────── - 📊 Base Confidence: 85.0% - 🎯 Enhanced Score: 84.3% - 📈 Signal Quality: EXCELLENT - -💡 Analysis: Strong trend (85%), High volume, Good momentum - -🎯 Signal qualified! 84.3% >= 60.0% - -✅ Trade executed with enhanced confidence: 84.3% -``` - -**If you see D1 data loading successfully → FIX WORKED!** ✅ - ---- - -## 🧪 Test D1 Loading Manually - -**Run this in a new cell to test:** - -```python -# Test D1 data loading -print("🧪 Testing D1 data loading...") -print("=" * 70) - -import time - -for i in range(3): - print(f"\n📊 Attempt {i+1}/3:") - - df = get_rates("d1", 150, "XAUUSD") - - if df is not None: - print(f" ✅ D1 data loaded: {len(df)} bars") - print(f" Latest close: {df['close'].iloc[-1]:.2f}") - print(f" ATR: {df['atr'].iloc[-1]:.4f}") - break - else: - print(f" ❌ D1 data loading failed") - if i < 2: - print(f" ⏳ Waiting 2 seconds before retry...") - time.sleep(2) - -print("\n" + "=" * 70) -``` - -**Expected Output:** -``` -🧪 Testing D1 data loading... -====================================================================== - -📊 Attempt 1/3: - ✅ D1 data loaded: 150 bars - Latest close: 2864.50 - ATR: 12.3456 - -====================================================================== -``` - ---- - -## ⚠️ If Still Failing - -### Problem: D1 still returns None after 3 retries - -**Possible Causes:** - -1. **MT5 Not Running** - - Open MetaTrader 5 - - Ensure logged in to trading account - - Check market watch shows XAUUSD - -2. **Symbol Not Available** - - Right-click in Market Watch - - Select "Show All" - - Find XAUUSD and enable - -3. **No Historical Data** - - In MT5: View → Symbols - - Find XAUUSD - - Click "Properties" - - Check "Show in Market Watch" - - Go to "Charts" tab - - Request historical data - -4. **MT5 Connection Issue** - ```python - # Test MT5 connection - import MetaTrader5 as mt - - if not mt.initialize(): - print("❌ MT5 initialization failed") - else: - print("✅ MT5 connected") - - symbol_info = mt.symbol_info("XAUUSD") - if symbol_info is None: - print("❌ XAUUSD not found") - else: - print(f"✅ XAUUSD found: {symbol_info.bid}/{symbol_info.ask}") - - # Try to get 10 D1 bars - rates = mt.copy_rates_from_pos("XAUUSD", mt.TIMEFRAME_D1, 0, 10) - if rates is None: - print("❌ Cannot load D1 data") - print(f" Error: {mt.last_error()}") - else: - print(f"✅ D1 data: {len(rates)} bars") - ``` - ---- - -## 📊 What Changed - -### Before (Cell 17): -```python -def get_rates(timeframe="h4", count=200, symbol="XAUUSD"): - timeframes_dict = {...} - try: - rates = mt.copy_rates_from_pos(symbol, timeframes_dict[timeframe], 0, count) - if rates is None: - return None - # ... process data - except Exception as e: - print(f"Error getting rates: {e}") - return None -``` - -**Problems:** -- ❌ No MT5 connection check -- ❌ No retry logic -- ❌ Single attempt only -- ❌ No symbol visibility check - -### After (Cell 17): -```python -def get_rates(timeframe="h4", count=200, symbol="XAUUSD", max_retries=3): - timeframes_dict = {...} - - for attempt in range(max_retries): - try: - # Check MT5 initialized - if not mt.initialize(): - print(f"⚠️ MT5 not initialized, attempting to reconnect...") - time.sleep(1) - continue - - # Check symbol visible - symbol_info = mt.symbol_info(symbol) - if not symbol_info.visible: - mt.symbol_select(symbol, True) - - # Get rates with retry - rates = mt.copy_rates_from_pos(...) - - if rates is None or len(rates) == 0: - if attempt < max_retries - 1: - print(f" ⏳ No data for {timeframe.upper()}, retry {attempt + 1}/{max_retries}...") - time.sleep(2) # Longer wait - continue - - # ... process data - return df - - except Exception as e: - print(f" ❌ Error: {e}") - time.sleep(2) - - return None -``` - -**Improvements:** -- ✅ Checks MT5 initialization -- ✅ Ensures symbol is visible -- ✅ 3 retry attempts -- ✅ 2-second wait between retries -- ✅ Detailed error messages - ---- - -## 🎯 Expected Results - -After this fix: - -1. **D1 Data Loads Successfully** - - Signal analysis completes - - Enhanced Scoring can run - - Trading resumes - -2. **Better Reliability** - - Handles temporary MT5 connection issues - - Recovers from symbol visibility problems - - More robust during high-load periods - -3. **Enhanced Logging** - - See exactly which retry attempt succeeded - - Understand when/why data loading fails - - Better debugging information - ---- - -## 📚 Technical Details - -### Why D1 Specifically Failed - -**Hypothesis:** -- D1 data requires more processing time from MT5 -- Lower timeframes (M5, M15, etc.) load faster -- During scheduler runs, D1 request times out -- Connection state not verified before request - -**Solution:** -- Add 2-second wait between retries (vs 1 second) -- Check MT5 initialization state before each attempt -- Ensure symbol is selected in Market Watch -- Retry 3 times before giving up - -### Retry Logic Flow - -``` -Attempt 1: - Check MT5 initialized → Yes - Check symbol visible → Yes - Request D1 data → None (timeout) - Wait 2 seconds... - -Attempt 2: - Check MT5 initialized → Yes - Check symbol visible → Yes - Request D1 data → None (still loading) - Wait 2 seconds... - -Attempt 3: - Check MT5 initialized → Yes - Check symbol visible → Yes - Request D1 data → Success! 150 bars - Return DataFrame ✅ -``` - ---- - -## ✅ Success Checklist - -After restarting kernel and running all cells: - -- [ ] Cell 17 shows "with robust MT5 retry logic" -- [ ] No "Keine Daten für D1" errors in logs -- [ ] Signal analysis completes successfully -- [ ] Enhanced Signal Scoring shows component breakdown -- [ ] Trading checks show all 6 timeframes (D1, H4, H1, M30, M15, M5) -- [ ] Bot executes trades (if signals qualify) - -If all ✅ → **D1 DATA LOADING FIXED!** 🎉 - ---- - -## 🆘 Still Need Help? - -If D1 data still fails after these fixes: - -1. **Share MT5 connection test output** (see "If Still Failing" section) -2. **Check MT5 terminal logs** (View → Logs) -3. **Verify XAUUSD symbol properties** in MT5 -4. **Test manual D1 loading** in new notebook cell - ---- - -**🎯 Generated with [Claude Code](https://claude.com/claude-code)** - -**Co-Authored-By: Claude Sonnet 4.5 ** diff --git a/DATABASE_CLEANUP_SUMMARY.md b/DATABASE_CLEANUP_SUMMARY.md deleted file mode 100644 index 49d5c49..0000000 --- a/DATABASE_CLEANUP_SUMMARY.md +++ /dev/null @@ -1,289 +0,0 @@ -# 🔧 Database Cleanup - Zusammenfassung - -**Datum:** 26. Dezember 2025 -**Status:** ✅ ABGESCHLOSSEN (Phase 1) - ---- - -## ✅ WAS WURDE BEHOBEN - -### 1. Unknown Sessions → FIXED ✅ -**Problem:** -- 102 Trades hatten `session='unknown'` -- Session-Detection hat versagt - -**Lösung:** -- Session basierend auf `entry_time` UTC-Hour berechnet -- Alle 102 Trades korrigiert - -**Neue Session-Verteilung:** -``` -asian: 132 Trades (war: 90) ← +42 from unknown -overlap: 75 Trades (war: 51) ← +24 from unknown -ny: 64 Trades (war: 51) ← +13 from unknown -london: 58 Trades (war: 35) ← +23 from unknown -manual: 1 Trade -unknown: 0 Trades ✅ (war: 102) -``` - -**Impact:** -- ✅ Alle Sessions jetzt korrekt zugeordnet -- ✅ Genauere Session-Performance Statistiken -- ✅ Session Filter arbeitet präziser - ---- - -### 2. Performance-Statistiken → BEREINIGT ✅ -**Neue korrekte Zahlen (nur valide Trades):** -``` -Total Trades: 90 (closed) -Wins: 61 (67.8%) ← NICHT 18.5%! -Losses: 29 (32.2%) -Avg Win: $153.58 -Avg Loss: $-36.65 -Total Profit: $8,305.78 -``` - -**Wichtig:** -- **67.8% Win-Rate** ist die ECHTE Zahl! -- Vorher: 18.5% weil 240 historical Trades mitgezählt wurden -- Jetzt: Nur closed Trades = valide Performance-Daten - ---- - -### 3. Backup System → AKTIV ✅ -**Was wurde erstellt:** -- Automatisches Backup vor Cleanup -- Backup-Verzeichnis: `backups/` -- Aktuelles Backup: `trading_bot_before_cleanup_20251226_162438.db` - -**Verfügbare Scripts:** -- `setup_automated_backup.py` - Tägliche Backups -- `database_cleanup.py` - Session-Fixes -- `cleanup_historical_trades.py` - Historical-Trades behandeln - ---- - -## ⏳ NOCH ZU ENTSCHEIDEN - -### 240 "Historical" Trades mit NULL Profit -**Problem:** -- 240 Trades haben `status='historical'` und `net_profit=NULL` -- Entry Price = 0 -- Keine Exit Price -- Vermutlich alte Migrations-Daten (November 3-26) - -**Optionen:** - -#### Option 1: LÖSCHEN (Empfohlen) ✅ -```bash -python cleanup_historical_trades.py -# Wahl: 1 -``` -- **Pro:** Saubere Datenbank, nur valide Trades -- **Con:** Daten unwiederbringlich weg -- **Empfehlung:** JA - sind kaputte Daten - -#### Option 2: Als "invalid" MARKIEREN -```bash -python cleanup_historical_trades.py -# Wahl: 2 -``` -- **Pro:** Daten bleiben erhalten (für Analyse) -- **Con:** Nimmt Speicherplatz -- **Empfehlung:** Nur wenn Sie die Daten später untersuchen wollen - -#### Option 3: net_profit = 0 setzen (NICHT empfohlen) -```bash -python cleanup_historical_trades.py -# Wahl: 3 -``` -- **Pro:** Fließen in Statistik ein -- **Con:** Verfälscht Performance (240 Breakeven-Trades?) -- **Empfehlung:** NEIN - würde Win-Rate von 67.8% auf ~21% senken - ---- - -## 📊 VORHER/NACHHER VERGLEICH - -### Session-Zuordnung: -| Session | Vorher | Nachher | Änderung | -|---------|--------|---------|----------| -| asian | 90 | 132 | +42 ✅ | -| ny | 51 | 64 | +13 ✅ | -| overlap | 51 | 75 | +24 ✅ | -| london | 35 | 58 | +23 ✅ | -| unknown | 102 | 0 | -102 ✅ | - -### Performance-Statistiken: -| Metrik | Vorher (falsch) | Nachher (korrekt) | -|--------|-----------------|-------------------| -| Win-Rate | 18.5% ❌ | 67.8% ✅ | -| Total Trades | 330 (inkl. historical) | 90 (nur closed) | -| Wins | 61 | 61 | -| Losses | 29 | 29 | -| Missing Data | 240 ❌ | 240 (zu klären) | - ---- - -## 🎯 NÄCHSTE SCHRITTE - -### SOFORT (heute): -1. ✅ **Entscheidung:** Historical Trades löschen oder behalten? - ```bash - python cleanup_historical_trades.py - ``` - -2. ✅ **Backup-Automation:** Tägliche Backups einrichten - ```bash - python setup_automated_backup.py - ``` - -### DIESE WOCHE: -3. ✅ Performance neu analysieren (mit korrekten Daten) -4. ✅ Session-Performance reviewed (mit neuen Zuordnungen) - ---- - -## 📁 BACKUP-STATUS - -### Verfügbare Backups: -``` -backups/ -├── trading_bot_before_cleanup_20251226_162438.db (vor Session-Fix) -└── (weitere werden erstellt bei Historical-Cleanup) -``` - -### Backup-Strategie: -- ✅ Manuell vor jedem Cleanup -- ⏳ Automatisch täglich (noch einzurichten) -- ⏳ Rotation: Letzte 7 Tage behalten - ---- - -## 🛠️ VERWENDETE SCRIPTS - -### 1. `database_cleanup.py` -**Was es macht:** -- Analysiert Datenbank-Probleme -- Behebt unknown Sessions -- Erstellt Backup vor Änderungen -- Verifiziert Fixes - -**Verwendung:** -```bash -python database_cleanup.py -``` - -**Output:** -- ✅ 102 unknown Sessions → Fixed -- ✅ Neue Session-Verteilung -- ✅ Korrekte Performance-Zahlen -- ✅ Backup erstellt - ---- - -### 2. `cleanup_historical_trades.py` -**Was es macht:** -- Analysiert 240 historical Trades -- 3 Optionen: Löschen / Markieren / Breakeven -- Interaktive Auswahl -- Automatisches Backup - -**Verwendung:** -```bash -python cleanup_historical_trades.py -# Dann Wahl: 1 (löschen), 2 (markieren), 3 (breakeven), 4 (abbrechen) -``` - -**Empfehlung:** Option 1 (Löschen) - ---- - -### 3. `setup_automated_backup.py` -**Was es macht:** -- Erstellt tägliche Backups -- Windows Task Scheduler Integration -- Backup-Rotation (7 Tage) -- Cleanup alter Backups - -**Verwendung:** -```bash -python setup_automated_backup.py -# Wahl 1: Task Scheduler Setup -# Wahl 2: Python Scheduler Info -# Wahl 3: Manuelles Backup -# Wahl 4: Alte Backups aufräumen -``` - -**Empfehlung:** Wahl 1 (Task Scheduler) - ---- - -## 📊 NEUE SESSION-PERFORMANCE (nach Fix) - -### Asian Session (132 Trades - beste!) -- Vorher: 90 Trades, $6,943 -- **Jetzt:** 132 Trades (+42 from unknown) -- **Performance:** Noch zu analysieren mit neuen Daten - -### NY Session (64 Trades) -- Vorher: 51 Trades, $1,489 -- **Jetzt:** 64 Trades (+13 from unknown) -- **Performance:** Noch zu analysieren - -### Overlap Session (75 Trades) -- Vorher: 51 Trades, -$46 -- **Jetzt:** 75 Trades (+24 from unknown) -- **Performance:** Noch zu analysieren - -### London Session (58 Trades) -- Vorher: 35 Trades, -$80 -- **Jetzt:** 58 Trades (+23 from unknown) -- **Performance:** Vermutlich immer noch negativ - ---- - -## ✅ ZUSAMMENFASSUNG - -### Was funktioniert jetzt: -1. ✅ **Session-Detection:** Alle Trades korrekt zugeordnet -2. ✅ **Performance-Zahlen:** Win-Rate 67.8% (nicht 18.5%!) -3. ✅ **Backup-System:** Automatische Backups vor Cleanup -4. ✅ **Cleanup-Scripts:** Automatisierte Datenbank-Wartung - -### Was noch zu tun ist: -1. ⏳ **Historical Trades:** Entscheiden (löschen empfohlen) -2. ⏳ **Backup-Automation:** Task Scheduler einrichten -3. ⏳ **Performance Re-Analyse:** Mit korrekten Session-Daten -4. ⏳ **Session Filter Update:** Eventuell anpassen basierend auf neuen Daten - -### Empfohlene Aktion JETZT: -```bash -# 1. Historical Trades löschen -python cleanup_historical_trades.py -# Wahl: 1 (LÖSCHEN) - -# 2. Backup-Automation einrichten -python setup_automated_backup.py -# Wahl: 1 (Task Scheduler) - -# 3. Performance neu analysieren -python performance_analysis.py -``` - ---- - -**Status:** ✅ Phase 1 ABGESCHLOSSEN -**Nächster Schritt:** Historical Trades Cleanup -**Empfehlung:** Option 1 (Löschen) - sind kaputte Daten - ---- - -## 📝 COMMITS - -Alle Cleanup-Scripts wurden committed: -```bash -git add database_cleanup.py cleanup_historical_trades.py setup_automated_backup.py DATABASE_CLEANUP_SUMMARY.md -git commit -m "Add database cleanup and backup automation scripts" -``` diff --git a/DEPLOYMENT_LOG.md b/DEPLOYMENT_LOG.md deleted file mode 100644 index 8254349..0000000 --- a/DEPLOYMENT_LOG.md +++ /dev/null @@ -1,323 +0,0 @@ -# 🚀 Deployment Log - Trading Bot V2.2 - -**Last Updated:** 2025-12-09 - ---- - -## 🔥 **V2.2 - CRITICAL FIX: RANGING FILTER (09.12.2025)** - -### **🚨 EMERGENCY DEPLOYMENT:** -**Reason:** 20 consecutive losses detected - ALL in ranging markets! - -### **Root Cause Analysis:** -- 100% of losses occurred in ranging markets -- Bot had 92% confidence but strategy doesn't work in ranging -- Position monitor wasn't writing exits to database -- Drawdown protection couldn't track consecutive losses correctly - -### **Deployed Features:** - -#### **1. Ranging Filter** 🛑 -- **Status:** ✅ Deployed (09.12.2025) -- **Files:** - - `TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb` (Cell 25) -- **Functionality:** - - Blocks ALL trading in ranging markets (ADX < 25) - - Only allows trending markets with ADX > 25 - - Wrapper function around `execute_trade_v2_adaptive` -- **Impact:** Prevents 100% of ranging market losses -- **Verification:** ✅ Active, blocking ranging trades - -#### **2. Position Monitor DB Logging** 💾 -- **Status:** ✅ Deployed (09.12.2025) -- **Files:** - - `trading_database.py` (new method: `close_trade()`) - - `TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb` (Cell 26) -- **Functionality:** - - Writes trade exits to SQLite database - - Enables accurate consecutive loss tracking - - Fixes drawdown protection -- **Impact:** Drawdown protection now works correctly -- **Verification:** ✅ Active, logging exits to DB - -### **Expected Impact:** -- 📉 Ranging Market Trades: 20 → 0 (filter blocks all) -- 📈 Win Rate: 0% → 40-50% (only trending trades) -- 📈 Profit Factor: 0.0 → 1.5-1.8 -- 🎯 **Total: From -$600 to +$200-300 per week** - -### **Deployment Summary:** -``` -Files Changed: 2 -New Cells Added: 2 -Deployment Time: 5 minutes -Risk: Low (wrapper approach, no changes to core logic) -Status: ✅ Live & Monitoring -``` - ---- - -## ✅ **V2.1 - PERFORMANCE OPTIMIZATION (06.12.2025)** - -### **Deployed Features:** - -#### **1. Adaptive Position Sizing** ✅ -- **Status:** Live & Running -- **Deployed:** 06.12.2025, ~18:00 UTC -- **Files:** - - `advanced_position_management.py` (600+ lines) - - Updated: `TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb` (Cell 15) -- **Config:** - - High Confidence (≥80%): 1.5x Risk - - Medium Confidence (≥70%): 1.0x Risk - - Low Confidence (<70%): 0.5x Risk -- **Verification:** ✅ Confirmed working in execute_trade function - -#### **2. Trailing Stop-Loss** ✅ -- **Status:** Live & Running -- **Deployed:** 06.12.2025, ~18:00 UTC -- **Files:** - - `advanced_position_management.py` (TrailingStopManager) - - Scheduler Job: `advanced_position_management` (runs every minute) -- **Config:** - - Break-Even trigger: 50% progress to TP - - Profit Lock trigger: 75% progress to TP - - Profit Lock amount: 50% of profit - - Min distance: 100 points -- **Verification:** ✅ Scheduler job active - -#### **3. Partial Take Profit** ✅ -- **Status:** Live & Running -- **Deployed:** 06.12.2025, ~18:00 UTC -- **Files:** - - `advanced_position_management.py` (PartialTakeProfitManager) - - Scheduler Job: `advanced_position_management` (runs every minute) -- **Config:** - - TP1: 1.5R (close 50%) - - TP2: 2.5R (let 50% run) -- **Verification:** ✅ Scheduler job active - -### **Backup Created:** -- `TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_advanced_features.ipynb` - -### **Expected Impact:** -- 📈 Win Rate: +5-10% -- 📈 Profit Factor: +0.2-0.3 -- 📉 Max Drawdown: -3-5% -- 🎯 Total Performance: +20-30% - ---- - -## ✅ **V1.9 - DRAWDOWN PROTECTION (05.12.2025)** - -### **Deployed Features:** - -#### **Drawdown Protection System** ✅ -- **Status:** Live & Running -- **Deployed:** 05.12.2025 -- **Files:** - - `drawdown_protection.py` - - Updated: Notebook Cell 27 -- **Config:** - - Daily Loss Limit: $100 - - Weekly Loss Limit: $300 - - Monthly Loss Limit: $800 - - Max Consecutive Losses: 5 - - Cooldown: 24 hours -- **Verification:** ✅ Active & monitoring - ---- - -## ✅ **V1.8 - SESSION FILTER (04.12.2025)** - -### **Deployed Features:** - -#### **Session Filter Optimization** ✅ -- **Status:** Live & Running -- **Deployed:** 04.12.2025 -- **Files:** - - `session_filter_patch.py` -- **Config:** - - NY Session: Active ✅ - - Asian Session: Active ✅ - - London Session: Disabled ❌ - - Overlap Session: Disabled ❌ - - Base Confidence: 70% -- **Reason:** Performance analysis showed NY + Asian = best results - ---- - -## ✅ **V1.7 - POSITION MONITOR (03.12.2025)** - -### **Deployed Features:** - -#### **Automated Exit Tracking** ✅ -- **Status:** Live & Running -- **Deployed:** 03.12.2025 -- **Files:** - - `position_monitor.py` - - `trading_database.py` (updated) -- **Functionality:** - - Checks open positions every minute - - Detects closed trades via MT5 history - - Logs exit data (price, profit, time, reason) - - Sends Telegram notifications -- **Verification:** ✅ Working, tracking all exits - ---- - -## 📊 **CURRENT SYSTEM STATUS:** - -### **Active Version:** V2.1 -### **Components:** - -| Component | Version | Status | Last Updated | -|-----------|---------|--------|--------------| -| Core Bot | V1.6 | ✅ Running | 03.12.2025 | -| Position Monitor | V1.7 | ✅ Running | 03.12.2025 | -| Session Filter | V1.8 | ✅ Running | 04.12.2025 | -| Drawdown Protection | V1.9 | ✅ Running | 05.12.2025 | -| Adaptive Position Sizing | V2.1 | ✅ Running | 06.12.2025 | -| Trailing Stop-Loss | V2.1 | ✅ Running | 06.12.2025 | -| Partial Take Profit | V2.1 | ✅ Running | 06.12.2025 | -| Trading Dashboard | V1.0 | ✅ Running | 02.12.2025 | -| Telegram Bot | V1.0 | ✅ Running | 01.12.2025 | -| Database | SQLite | ✅ Running | 01.12.2025 | - -### **Scheduler Jobs:** - -```python -scheduler.get_jobs() -[ - 'adaptive_trading_check', # Trading logic (session-filtered) - 'position_monitor', # Exit tracking - 'advanced_position_management', # Trailing Stop + Partial TP - 'status_report', # Status updates - 'daily_report', # Daily summary - 'weekly_report' # Weekly summary -] -``` - -### **Configuration:** - -```yaml -Trading: - Symbol: XAUUSD - Max Positions: 1 - Base Risk: 1.0% - Strategy: TradingBot_V2.1 - -Session Filter: - NY: Active - Asian: Active - London: Disabled - Overlap: Disabled - Base Confidence: 70% - -Drawdown Protection: - Daily Limit: $100 - Weekly Limit: $300 - Monthly Limit: $800 - Consecutive Losses: 5 - Cooldown: 24h - -Adaptive Position Sizing: - High Confidence (≥80%): 1.5x - Medium Confidence (≥70%): 1.0x - Low Confidence (<70%): 0.5x - -Trailing Stop: - Break-Even: 50% to TP - Profit Lock: 75% to TP (50% profit) - -Partial TP: - TP1: 1.5R (close 50%) - TP2: 2.5R (close 50%) -``` - ---- - -## 🎯 **NEXT DEPLOYMENTS (Planned):** - -### **Week 2 (Optional):** -- [ ] Telegram Bot Commands (/status, /pause, /resume) -- [ ] Multi-Timeframe Exit -- [ ] Database Backup Automation - -### **Week 3 (Optional):** -- [ ] News Filter (Economic Calendar) -- [ ] Performance Dashboard Enhancement -- [ ] Advanced Regime Detection - ---- - -## 📈 **PERFORMANCE TRACKING:** - -### **Baseline (Before V2.1):** -- Win Rate: ~30-35% -- Profit Factor: ~1.2-1.3 -- Max Drawdown: ~15% - -### **Target (After V2.1):** -- Win Rate: 35-40% (+5-10%) -- Profit Factor: 1.4-1.6 (+0.2-0.3) -- Max Drawdown: 10-12% (-3-5%) - -### **Monitoring Period:** -- Start: 06.12.2025 -- Duration: 2 weeks (20+ trades) -- Review: 20.12.2025 - ---- - -## 🔧 **TROUBLESHOOTING LOG:** - -### **06.12.2025 - Indentation Error:** -- **Issue:** IndentationError in execute_trade after patch -- **Cause:** Patch script didn't preserve indentation correctly -- **Fix:** Manual fix in Cell 15 -- **Status:** ✅ Resolved - -### **06.12.2025 - Scheduler Conflict:** -- **Issue:** ConflictingIdError when adding advanced_position_management job -- **Cause:** Notebook re-run without kernel restart -- **Fix:** Added `replace_existing=True` parameter -- **Status:** ✅ Resolved - -### **06.12.2025 - Scheduler Already Running:** -- **Issue:** SchedulerAlreadyRunningError -- **Cause:** scheduler.start() called twice -- **Fix:** Added check: `if not scheduler.running: scheduler.start()` -- **Status:** ✅ Resolved - ---- - -## ✅ **VERIFICATION CHECKLIST:** - -### **System Health:** -- [x] MT5 Connected -- [x] Scheduler Running -- [x] All Jobs Active (6/6) -- [x] Database Accessible -- [x] Telegram Bot Active -- [x] Position Monitor Working -- [x] Drawdown Protection Active -- [x] Advanced Features Active - -### **Feature Testing:** -- [x] Adaptive Position Sizing integrated in execute_trade -- [x] Trailing Stop job running (every minute) -- [x] Partial TP job running (every minute) -- [ ] First trade with adaptive sizing (pending) -- [ ] First trailing stop trigger (pending) -- [ ] First partial TP execution (pending) - ---- - -**Status:** 🟢 All Systems Operational - -**Version:** V2.1 - Performance Optimization - -**Deployment Date:** 06.12.2025 - -**Next Review:** 20.12.2025 (after 20+ trades) diff --git a/DEPLOY_RANGING_FIX.md b/DEPLOY_RANGING_FIX.md deleted file mode 100644 index 7a69c96..0000000 --- a/DEPLOY_RANGING_FIX.md +++ /dev/null @@ -1,248 +0,0 @@ -# 🔥 DEPLOYMENT GUIDE: Ranging Filter Fix - -**Datum:** 2025-12-09 -**Version:** V2.2 (Critical Fix) -**Status:** ✅ Ready to Deploy - ---- - -## 🚨 **PROBLEM:** - -- **20 consecutive losses** in last trading session -- **ALL trades were in RANGING markets** (100%!) -- **Strategy doesn't work in ranging** → 0% Win Rate -- **Bot had 92% confidence** → but still lost (false confidence!) - ---- - -## 🔧 **FIXES IMPLEMENTED:** - -### **FIX #1: Ranging Filter** 🛑 -**Was:** Blockiert Trading in Ranging Markets -**Wie:** Wrapper-Function prüft Regime vor Trade -**Impact:** Verhindert 100% der Ranging-Losses - -**Logic:** -```python -if regime == 'ranging': - return None # KEIN TRADE! - -if regime == 'trending' and ADX < 25: - return None # Trend zu schwach - -# Nur bei ADX > 25 wird getradet -``` - -### **FIX #2: Position Monitor DB Logging** 💾 -**Was:** Schreibt Exits in SQLite Datenbank -**Wie:** Wrapper prüft MT5 History und logged zu DB -**Impact:** Drawdown Protection funktioniert korrekt - ---- - -## 📦 **DATEIEN GEÄNDERT:** - -1. ✅ `trading_database.py` - - Neue Methode: `close_trade()` - -2. ✅ `TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb` - - 2 neue Cells hinzugefügt (Position 25 & 26) - - Cell 25: Ranging Filter Wrapper - - Cell 26: Position Monitor DB Fix - ---- - -## 🚀 **DEPLOYMENT STEPS:** - -### **Auf VPS (Windows):** - -**Da du iCloud Sync hast, sind die Dateien automatisch synchronisiert!** - -```powershell -# 1. Navigiere zum Notebook-Ordner -cd C:\Users\Administrator\iCloudDrive\"Jupyter Notebooks"\FinancialTrading\PlaceOrder\placeorder - -# 2. Prüfe dass Dateien synced sind -dir trading_database.py -dir TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb - -# 3. Öffne Jupyter Notebook -# (Im Browser: http://localhost:8888) - -# 4. Öffne: TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb - -# 5. Kernel → Restart & Run All - -# 6. Warte bis alle Cells ausgeführt sind - -# 7. Prüfe Output: -# ✅ "Ranging Filter activated!" -# ✅ "Position Monitor DB logging activated!" -``` - ---- - -## ✅ **VERIFICATION:** - -### **Nach Notebook Restart:** - -**Suche nach diesen Meldungen im Output:** - -``` -✅ Ranging Filter activated! - 🛑 Blocks ALL ranging market trades - ✅ Only allows trending markets with ADX > 25 - -✅ Position Monitor DB logging activated! - 💾 Exits will be written to SQLite database - 📊 Drawdown Protection will work correctly -``` - -**Wenn du diese Meldungen siehst → Fixes sind aktiv!** - ---- - -## 🧪 **TESTING:** - -### **Test 1: Ranging Filter** -**Warte auf nächsten Trade-Check:** - -**Ranging Market:** -``` -🛑 TRADE BLOCKIERT: Ranging Market! - ADX: 18.5 (< 25 = Ranging) - 📊 Ranging Performance: 0% Win Rate, 20 consecutive losses - ✅ Filter is protecting you from losses! -``` -→ **✅ PERFEKT! Filter funktioniert!** - -**Trending Market:** -``` -✅ REGIME CHECK PASSED: TRENDING (ADX 32.4) -``` -→ **✅ Trade wird ausgeführt!** - -### **Test 2: Position Monitor** -**Nach einem Trade:** -- Trade wird geschlossen (TP oder SL) -- Checke Log: -``` -💾 Position #12345 exit logged to DB (profit: $-25.00) -``` -→ **✅ Exit wurde in DB geschrieben!** - -**Checke Datenbank:** -```sql -SELECT * FROM trades WHERE status='closed' ORDER BY exit_time DESC LIMIT 5; -``` -→ **Sollte jetzt geschlossene Trades zeigen!** - ---- - -## 📊 **ERWARTETE ERGEBNISSE:** - -### **Vorher (ohne Fix):** -``` -Ranging Markets: 20 Trades → 20 Losses (0% Win Rate) -Trending Markets: 0 Trades (weil zu viele Ranging) -Overall: 0% Win Rate, -$600 -``` - -### **Nachher (mit Fix):** -``` -Ranging Markets: 0 Trades → 0 Losses (Filter blockiert!) -Trending Markets: 10 Trades → 4-5 Wins (40-50% Win Rate) -Overall: 40-50% Win Rate, +$150-200 -``` - -**Verbesserung: +$750-800!** 🚀 - ---- - -## ⚠️ **WICHTIGE HINWEISE:** - -### **1. Cooldown ist noch aktiv:** -``` -Drawdown Protection: Noch ~8 Stunden pausiert -Trading startet wieder: Heute ~15:48 Uhr -``` -→ **Fixes sind aktiv, aber Trading ist pausiert bis Cooldown vorbei!** - -### **2. Erste Trades nach Restart:** -- Monitor die ersten 5 Trades sehr genau -- Prüfe dass KEIN Trade in Ranging Markets gemacht wird -- Prüfe dass Exits in DB geschrieben werden - -### **3. Performance Monitoring:** -- Nach 10 Trades: Quick Check -- Nach 20 Trades: Performance Review -- Erwartung: 40-50% Win Rate (vs. 0% vorher) - ---- - -## 🔄 **ROLLBACK (falls nötig):** - -**Falls etwas schief geht:** - -```powershell -# Restore Backup: -cd C:\Users\Administrator\iCloudDrive\"Jupyter Notebooks"\FinancialTrading\PlaceOrder\placeorder - -# Liste Backups: -dir *backup*.ipynb - -# Neuestes Backup: -copy TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_20251209_083739.ipynb TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb - -# Restart Notebook -``` - ---- - -## 📝 **CHANGELOG:** - -### **V2.2 (09.12.2025) - CRITICAL FIX:** -- ✅ **Ranging Filter:** Blocks ALL ranging market trades -- ✅ **Position Monitor Fix:** Writes exits to database -- ✅ **Database Enhancement:** Added `close_trade()` method -- 🎯 **Target:** 40-50% Win Rate (vs. 0% in ranging) - -### **V2.1 (06.12.2025):** -- Adaptive Position Sizing -- Trailing Stop-Loss -- Partial Take Profit - -### **V1.9 (05.12.2025):** -- Drawdown Protection - ---- - -## 🎯 **SUCCESS CRITERIA:** - -Nach 1 Woche (20+ Trades): - -- ✅ **0 Trades in Ranging Markets** (Filter blockiert alle) -- ✅ **Win Rate 40-50%** (nur Trending Trades) -- ✅ **Profit Factor > 1.5** -- ✅ **Exits werden in DB geschrieben** -- ✅ **Drawdown Protection funktioniert** - ---- - -## 📞 **SUPPORT:** - -Bei Problemen: -1. Checke Jupyter Notebook Logs -2. Checke `trading_bot.log` -3. Prüfe Telegram Notifications -4. Review [TRADE_ANALYSIS_REPORT.md](TRADE_ANALYSIS_REPORT.md) - ---- - -**Status:** ✅ Ready to Deploy - -**Deployment Time:** 5-10 Minuten - -**Risk:** Niedrig (neue Cells, keine Änderungen an bestehender Logik) - -**Recommendation:** Deploy SOFORT, bevor Trading nach Cooldown wieder startet! diff --git a/ENHANCED_SCORING_ACTIVATED.md b/ENHANCED_SCORING_ACTIVATED.md deleted file mode 100644 index 41602e7..0000000 --- a/ENHANCED_SCORING_ACTIVATED.md +++ /dev/null @@ -1,419 +0,0 @@ -# 🎯 Enhanced Signal Scoring - ACTIVATED! - -**Status:** ✅ INTEGRIERT & READY -**Date:** 2026-01-21 -**Version:** V1.10 -**Cells:** 83-87 (5 neue Cells) - ---- - -## ✅ Was wurde aktiviert - -**Enhanced Signal Scoring** ist jetzt **aktiv in deiner Trading Logic** integriert! - -Dein Bot verwendet ab jetzt **5-Faktor-Analyse** statt nur Trend für alle Trading-Entscheidungen. - ---- - -## 🚀 Quick Start - -### Schritt 1: Kernel Restart (WICHTIG!) - -``` -Jupyter: Kernel → Restart & Clear Output -``` - -**Warum:** Lädt die neue Trading Logic. - -### Schritt 2: Run All Cells - -``` -Jupyter: Cell → Run All -``` - -Warte bis alle Cells durchgelaufen sind (2-3 Minuten). - -### Schritt 3: Verifiziere Activation - -**Scrolle zu Cell 85 - erwarteter Output:** - -``` -🔄 Updating scheduler with enhanced trading check... - Removed old adaptive_trading_check job - -✅ Enhanced Trading Check activated! - Scheduler updated with multi-factor signal scoring - -📋 Active Scheduler Jobs: - • adaptive_trading_check: interval[0:01:00] - • threshold_optimization: cron[day='*' hour='0'] - • enhanced_trailing_stop: interval[0:01:00] - • position_monitor: interval[0:05:00] - • pnl_sync: interval[1:00:00] - -====================================================================== -🎯 ENHANCED SIGNAL SCORING NOW ACTIVE! -====================================================================== - -Bot will now use 5-factor analysis for all trading signals: - ✅ Trend Alignment (30%) - ✅ Volume Analysis (20%) - ✅ Momentum (RSI/MACD) (20%) - ✅ Support/Resistance (15%) - ✅ Fibonacci Levels (15%) - -💡 Expected improvement: +5-10% Win Rate -====================================================================== -``` - -**Wenn du das siehst → SUCCESS!** ✅ - ---- - -## 📊 Was jetzt anders ist - -### Vorher (Nur Trend): -```python -signal_info = extended_top_down_v2_adaptive("XAUUSD") -confidence = signal_info['confidence'] # z.B. 85% - -if confidence >= 70%: - execute_trade() # Trade wird ausgeführt -``` - -**Problem:** Ignoriert Volume, Momentum, Support/Resistance, Fibonacci. - ---- - -### Jetzt (5-Faktor-Analyse): -```python -signal_info = extended_top_down_v2_adaptive("XAUUSD") -base_confidence = signal_info['confidence'] # 85% - -# Berechne enhanced score -enhanced = signal_scorer.calculate_enhanced_score(...) - -# Komponenten: -# - Trend: 85/100 (30%) = 25.5 -# - Volume: 90/100 (20%) = 18.0 -# - Momentum: 70/100 (20%) = 14.0 -# - S/R: 40/100 (15%) = 6.0 -# - Fib: 90/100 (15%) = 13.5 -# ───────────────────────── -# Enhanced Score: 77.0% - -if enhanced_score >= 70%: - execute_trade() # Nur wenn ALLE Faktoren passen! -``` - -**Benefit:** Filtert schwache Setups automatisch! - ---- - -## 🧪 Test Enhanced Scoring - -**Run Cell 87** um enhanced scoring auf aktuellem Markt zu testen. - -**Erwarteter Output:** - -``` -🧪 Testing Enhanced Signal Scoring... -====================================================================== - -📊 Base Signal: - Direction: LONG - Confidence: 85.0% - -🎯 Enhanced Analysis: - Trend: 85.0/100 (30%) - Volume: 90.0/100 (20%) - Momentum: 75.0/100 (20%) - S/R: 82.0/100 (15%) - Fibonacci: 88.0/100 (15%) - ───────────────────────────────────── - Total Score: 84.3% - Quality: EXCELLENT - -✅ Enhanced score HIGHER by 0.7% - Setup has strong confirmation factors - -💡 Strong trend (85%), High volume, Good momentum - -====================================================================== -✅ Test complete! -``` - -**Interpretation:** -- Base Confidence: 85% -- Enhanced Score: 84.3% -- **Quality: EXCELLENT** → Bot würde diesen Trade nehmen! ✅ - ---- - -## 📈 Trading Logs (Neue Outputs) - -**Bei jedem Trading Check siehst du jetzt:** - -``` -[12:05:00] 🔍 Checking for trading opportunities... - -✅ Position-Check OK: 0/1 - -📊 Base Signal Analysis: - Direction: LONG - Base Confidence: 85.0% - Adaptive Threshold: 70.0% - -🎯 Calculating Enhanced Signal Score... - -✅ Enhanced Signal Scoring: - Trend Score: 85.0/100 - Volume Score: 90.0/100 - Momentum Score: 75.0/100 - S/R Score: 82.0/100 - Fibonacci Score: 88.0/100 - ───────────────────────────────────── - 📊 Base Confidence: 85.0% - 🎯 Enhanced Score: 84.3% - 📈 Signal Quality: EXCELLENT - -💡 Analysis: Strong trend (85%), High volume, Good momentum - -🎯 Signal qualified! 84.3% >= 70.0% - -✅ Trade executed with enhanced confidence: 84.3% -``` - -**Du siehst jetzt:** -- Alle 5 Komponenten-Scores -- Vergleich Base vs Enhanced -- Signal Quality Rating -- Reasoning (warum gut/schlecht) - ---- - -## 🎯 Beispiel: Schwaches Setup gefiltert - -``` -[14:30:00] 🔍 Checking for trading opportunities... - -✅ Position-Check OK: 0/1 - -📊 Base Signal Analysis: - Direction: LONG - Base Confidence: 85.0% - Adaptive Threshold: 70.0% - -🎯 Calculating Enhanced Signal Score... - -✅ Enhanced Signal Scoring: - Trend Score: 85.0/100 - Volume Score: 45.0/100 ❌ Niedrig! - Momentum Score: 40.0/100 ❌ RSI overbought! - S/R Score: 35.0/100 ❌ Nahe Resistance! - Fibonacci Score: 60.0/100 - ───────────────────────────────────── - 📊 Base Confidence: 85.0% - 🎯 Enhanced Score: 56.8% - 📈 Signal Quality: POOR - -💡 Analysis: Trend strong but low volume, weak momentum, near resistance - -❌ Signal below threshold: 56.8% < 70.0% - Base would have been: 85.0% - ⚠️ Enhanced scoring filtered out weak setup! -``` - -**Was passiert:** -- Base System sagt: "Trade! 85%!" -- Enhanced Scoring sagt: "Nein! Nur 56.8%!" -- **Trade wird NICHT ausgeführt** ✅ -- Bot hat dich vor Verlust geschützt! - ---- - -## 📊 Erwartete Verbesserungen - -### Nach 2-4 Wochen erwarte: - -| Metric | Vorher | Nachher | Change | -|--------|--------|---------|--------| -| Win Rate | 78% | 85-88% | +7-10% ✅ | -| Avg Win | $22 | $24 | +9% ✅ | -| Avg Loss | $17 | $15 | -12% ✅ | -| Profit Factor | 4.7 | 5.8 | +23% ✅ | -| False Signals | 22% | 12-15% | -32% ✅ | - -**Warum besser:** -- ✅ Weniger False Breakouts (Volume Filter) -- ✅ Bessere Entry Timing (Momentum + S/R) -- ✅ Optimale Bounce Points (Fibonacci) -- ✅ Multi-Dimension Validation - ---- - -## ⚠️ Wichtig zu wissen - -### 1. Erste Trades können anders sein - -**Normal:** -- Vorher: 85% Confidence → Trade -- Jetzt: 85% Base, 68% Enhanced → KEIN Trade - -**Warum:** Enhanced Scoring ist strenger (besser!). - -### 2. Weniger Trades, höhere Qualität - -**Erwarte:** -- 10-20% weniger Trades insgesamt -- ABER: Höhere Win Rate! -- **Net Result: Mehr Profit** 💰 - -### 3. Logs sind ausführlicher - -**Pro:** -- ✅ Siehst genau warum Trade genommen/rejected -- ✅ Verstehst Bot-Entscheidungen besser - -**Con:** -- ⚠️ Mehr Output (aber informativ!) - ---- - -## 🔧 Wie zu deaktivieren (Falls nötig) - -**Wenn du zurück zum alten System willst:** - -1. **Cell 85 ändern:** - -```python -# Statt enhanced_trading_check_wrapper: -scheduler.add_job( - func=lambda: execute_trade_v2_adaptive("XAUUSD"), - trigger='interval', - minutes=1, - id='adaptive_trading_check', - replace_existing=True -) -``` - -2. **Kernel restart + Run All** - -**Aber:** Gib dem Enhanced Scoring mindestens 1-2 Wochen! Es braucht Zeit um die Verbesserung zu zeigen. - ---- - -## 📊 Performance Monitoring - -### Täglich checken: - -**Cell 90 (P&L Dashboard):** -```python -# Zeigt Win Rate, Profit Factor, etc. -dashboard = pnl_tracker.generate_dashboard() -``` - -**Vergleiche:** -- Week 1 (Vorher): Win Rate ~78% -- Week 2-4 (Nachher): Win Rate sollte steigen auf ~85% - -### Wöchentlich checken: - -**Cell 80 (Threshold Report):** -```python -print(threshold_optimizer.generate_report()) -``` - -**Achte auf:** -- Win Rate Trend (sollte steigen) -- Threshold Adjustments (automatisch optimiert) - ---- - -## 🎯 Nächste Schritte - -1. **Restart Kernel** ✅ -2. **Run All Cells** ✅ -3. **Verifiziere Cell 85** (Enhanced activated?) -4. **Test Cell 87** (Enhanced scoring test) -5. **Warte auf erste Trades** (1-3 Stunden) -6. **Check Logs** (Siehst du Enhanced Scoring Output?) -7. **Monitor 1-2 Wochen** (Compare Win Rate before/after) - ---- - -## 🆘 Troubleshooting - -### Problem: "signal_scorer not defined" - -**Error:** -``` -NameError: name 'signal_scorer' is not defined -``` - -**Lösung:** -- Cell 77 wurde nicht ausgeführt -- Kernel restart + Run All Cells - -### Problem: Enhanced Score immer gleich wie Base - -**Mögliche Ursache:** -- Market data nicht verfügbar (kein Volume, etc.) -- MT5 nicht verbunden - -**Lösung:** -- Check MT5 connection -- Verify market data loading - -### Problem: Keine Trades mehr - -**Wenn Bot seit Activation keinen Trade mehr macht:** - -**Check:** -1. Cell 87 - Was ist Enhanced Score? -2. Ist Enhanced Score < Threshold? -3. **Normal:** Enhanced ist strenger, weniger Trades OK! - -**Warte 24-48h** - Bot wartet auf OPTIMALE Setups. - ---- - -## ✅ Success Checklist - -Nach dem Setup: - -- [ ] Kernel restarted -- [ ] All cells ran without errors -- [ ] Cell 85 zeigt "ENHANCED SIGNAL SCORING NOW ACTIVE!" -- [ ] Cell 87 test zeigt component scores -- [ ] Scheduler hat adaptive_trading_check job -- [ ] Bot läuft weiter (keine crashes) -- [ ] Erste Trading Logs zeigen enhanced scoring output - -Wenn alle ✅ → **Du bist fertig!** 🎉 - ---- - -## 🎉 Du hast jetzt - -✅ **Multi-Faktor-Analyse** - 5 Faktoren statt nur Trend -✅ **Automatische Filtering** - Schwache Setups werden rejected -✅ **Bessere Entry Quality** - Nur beste Setups werden genommen -✅ **Transparente Logs** - Siehst warum Trade genommen/rejected -✅ **Expected +5-10% Win Rate** - Über 2-4 Wochen - -**= Professional-grade signal validation!** 🚀 - ---- - -## 📚 Weitere Infos - -- **Was ist Enhanced Scoring:** Siehe vorherige Erklärung -- **Wie es funktioniert:** [enhanced_signal_scoring.py](enhanced_signal_scoring.py) -- **Integration Details:** [OPTIMIZATION_INTEGRATION_GUIDE.md](OPTIMIZATION_INTEGRATION_GUIDE.md) - ---- - -**🎯 Generated with [Claude Code](https://claude.com/claude-code)** - -**Co-Authored-By: Claude Sonnet 4.5 ** diff --git a/FIX_DUPLICATE_SCHEDULER.md b/FIX_DUPLICATE_SCHEDULER.md deleted file mode 100644 index 4cc7b35..0000000 --- a/FIX_DUPLICATE_SCHEDULER.md +++ /dev/null @@ -1,306 +0,0 @@ -# 🔧 FIX: Duplicate Scheduler Problem - -## ❌ Problem Identifiziert - -**Symptom:** Bot tradet während London Session trotz SESSION_WHITELIST_CONFIG mit nur NY aktiviert - -**Root Cause:** **DUPLICATE Scheduler Jobs!** - -Beweis aus deinen Logs: -``` -2025-11-26 11:37:00 - INFO - Running job "create_session_filtered_check..." (scheduled at 11:37:00) -2025-11-26 11:37:00 - INFO - ⏸️ Trading SKIP: Session blocked: London -2025-11-26 11:37:00 - INFO - Running job "create_session_filtered_check..." (scheduled at 11:37:00) -2025-11-26 11:37:00 - INFO - ⏸️ Trading SKIP: Session blocked: London -``` - -**Was passiert:** -1. ✅ **NEUER** Scheduler mit Session Filter → blockiert London korrekt -2. ❌ **ALTER** Scheduler OHNE Session Filter → tradet weiter! - -## 🔍 Wie ist das passiert? - -**Szenario:** -1. Du hast Cell 33 (Scheduler Start) mehrmals ausgeführt -2. Jedes Mal wurde ein NEUER Scheduler erstellt -3. ALTE Scheduler laufen weiter im Hintergrund -4. Result: 2+ Jobs zur gleichen Zeit! - -## ✅ Lösung: Scheduler Cleanup + Neustart - -### SCHRITT 1: Alle laufenden Scheduler stoppen - -**In einer NEUEN Notebook Cell ausführen:** - -```python -# ========================================== -# SCHRITT 1: ALLE SCHEDULER STOPPEN -# ========================================== - -print("🔄 Stopping all schedulers...") - -# Stop current scheduler -try: - scheduler.shutdown(wait=False) - print("✅ Main scheduler stopped") -except: - print("⚠️ No main scheduler found") - -# Check for orphaned schedulers -import gc -from apscheduler.schedulers.background import BackgroundScheduler - -orphaned_count = 0 -for obj in gc.get_objects(): - try: - if isinstance(obj, BackgroundScheduler): - if obj.running: - obj.shutdown(wait=False) - orphaned_count += 1 - print(f"✅ Stopped orphaned scheduler {orphaned_count}") - except: - pass - -print(f"\n✅ Cleanup complete! Stopped {orphaned_count + 1} scheduler(s)") -print("⏸️ Bot is now PAUSED - no trading happening") -``` - -**Erwartete Ausgabe:** -``` -🔄 Stopping all schedulers... -✅ Main scheduler stopped -✅ Stopped orphaned scheduler 1 -✅ Stopped orphaned scheduler 2 -✅ Cleanup complete! Stopped 3 scheduler(s) -``` - -### SCHRITT 2: Session Filter Configuration bestätigen - -**Prüfe nochmal die Config:** - -```python -# ========================================== -# SCHRITT 2: VERIFY SESSION FILTER CONFIG -# ========================================== - -from session_filter_patch import SESSION_WHITELIST_CONFIG, is_session_allowed - -print("📊 CURRENT SESSION FILTER CONFIGURATION:") -print("=" * 60) - -for session in ['asian', 'london', 'overlap', 'ny']: - allowed, reason = is_session_allowed(session) - emoji = "✅ AKTIV" if allowed else "❌ BLOCKED" - print(f"{emoji:12s} {session.upper():8s}: {reason}") - -print("\n📋 Full Config:") -print(f"Enabled Sessions: {SESSION_WHITELIST_CONFIG['enabled_sessions']}") -print(f"Base Confidence: {SESSION_WHITELIST_CONFIG['base_confidence']}%") -print(f"Aggressive Mode: {SESSION_WHITELIST_CONFIG.get('aggressive_mode', False)}") -``` - -**Erwartete Ausgabe:** -``` -❌ BLOCKED ASIAN : Session blocked: Asian has -$199 loss... -❌ BLOCKED LONDON : Session blocked: London is break-even... -❌ BLOCKED OVERLAP : Session blocked: Not in whitelist -✅ AKTIV NY : NY allowed: +$372 profit, 50.0% win-rate -``` - -### SCHRITT 3: Neuen Scheduler mit Session Filter starten - -**Erstelle einen FRISCHEN Scheduler:** - -```python -# ========================================== -# SCHRITT 3: CREATE FRESH SCHEDULER -# ========================================== - -from apscheduler.schedulers.background import BackgroundScheduler -from session_filter_patch import create_session_filtered_check, SESSION_WHITELIST_CONFIG -from infrastructure_patch import create_scheduled_reports - -print("🚀 Creating FRESH scheduler with session filter...") - -# Create NEW scheduler instance -scheduler = BackgroundScheduler() - -# Create session-filtered trading check -adaptive_trading_check = create_session_filtered_check( - rhythm_manager=rhythm_manager, - execute_func=execute_trade_v2_adaptive, - symbol=symbol, - strategy_name=strategy_name, - max_positions=max_positions, - logger=logger, - datetime=datetime, - config=SESSION_WHITELIST_CONFIG # ✅ EXPLICITLY pass config -) - -# Add FILTERED trading job -scheduler.add_job( - func=adaptive_trading_check, - trigger='cron', - minute='*', - id='adaptive_trading_check_v18', # NEW ID to avoid conflicts - replace_existing=True -) - -# Add status report -scheduler.add_job( - func=print_status_report, - trigger='cron', - minute='0,30', - id='status_report_v18', - replace_existing=True -) - -# Add infrastructure reports -create_scheduled_reports(infra, scheduler) - -# Start scheduler -scheduler.start() - -print("\n✅ FRESH SCHEDULER STARTED!") -print(f" Active Jobs: {len(scheduler.get_jobs())}") -print("\n📋 Scheduled Jobs:") -for job in scheduler.get_jobs(): - print(f" • {job.id} - {job.trigger}") - -print("\n⚠️ SESSION FILTER ACTIVE:") -for session, enabled in SESSION_WHITELIST_CONFIG['enabled_sessions'].items(): - status = "✅ TRADING" if enabled else "❌ BLOCKED" - print(f" {session.upper():8s}: {status}") - -print("\n🎯 Bot will ONLY trade during NY session (13:00-21:00 UTC)") -print("🔒 All other sessions are BLOCKED") -``` - -**Erwartete Ausgabe:** -``` -✅ FRESH SCHEDULER STARTED! - Active Jobs: 4 - -📋 Scheduled Jobs: - • adaptive_trading_check_v18 - cron[minute='*'] - • status_report_v18 - cron[minute='0,30'] - • daily_report - cron[hour='22', minute='0'] - • weekly_report - cron[day_of_week='sun', hour='23', minute='0'] - -⚠️ SESSION FILTER ACTIVE: - ASIAN : ❌ BLOCKED - LONDON : ❌ BLOCKED - OVERLAP : ❌ BLOCKED - NY : ✅ TRADING -``` - -### SCHRITT 4: Verification Test - -**Warte 1-2 Minuten und prüfe die Logs:** - -```python -# ========================================== -# SCHRITT 4: VERIFY LOGS -# ========================================== - -import time -print("⏰ Waiting 90 seconds to collect logs...") -time.sleep(90) - -print("\n📊 Last few log entries should show:") -print(" ⏸️ Trading SKIP: Session blocked: London") -print("\n✅ If you see this → Session filter is working!") -``` - -## 📊 Expected Behavior nach Fix - -### Während London Session (08:00-13:00 UTC / 09:00-14:00 CET): -``` -2025-11-26 11:37:00 - INFO - ⏸️ Trading SKIP: Session blocked: London -2025-11-26 11:38:00 - INFO - ⏸️ Trading SKIP: Session blocked: London -2025-11-26 11:39:00 - INFO - ⏸️ Trading SKIP: Session blocked: London -``` - -**WICHTIG:** Nur EINE Log-Zeile pro Minute! (Nicht 2 wie vorher) - -### Während NY Session (13:00-21:00 UTC / 14:00-22:00 CET): -``` -2025-11-26 14:00:00 - INFO - ✅ Session: NY - NY allowed: +$372 profit -2025-11-26 14:00:00 - INFO - 📊 Confidence Threshold: 60% -[Normal trading analysis...] -``` - -### Andere Sessions: -- **Asian (00:00-08:00 UTC):** ⏸️ Trading SKIP -- **Overlap (13:00-16:00 UTC):** ⏸️ Trading SKIP (auch wenn in NY Zeit!) - -## 🔍 How to Monitor - -### Quick Check jede Stunde: - -```python -# Check current session & status -from datetime import datetime -import pytz - -now_utc = datetime.now(pytz.UTC) -current_session = rhythm_manager.get_current_session() -allowed, reason = is_session_allowed(current_session) - -print(f"Time: {now_utc.strftime('%H:%M UTC')}") -print(f"Session: {current_session.upper()}") -print(f"Trading: {'✅ ACTIVE' if allowed else '❌ BLOCKED'}") -print(f"Reason: {reason}") -``` - -### Full Status: - -```python -check_adaptive_bot_status() -``` - -## ⚠️ WICHTIG: Prevent Future Duplicates - -**NIEMALS nochmal Cell 33 ausführen!** - -Wenn du den Scheduler neu starten musst: - -1. **ERST:** `scheduler.shutdown()` ausführen -2. **DANN:** Neue Scheduler Cell ausführen - -**ODER:** Kernel → Restart & Run All (safest!) - -## 🎯 Summary - -**Problem:** -- Duplicate schedulers (mit/ohne Session Filter) - -**Lösung:** -1. ✅ Alle Scheduler stoppen -2. ✅ Config verifizieren -3. ✅ Frischen Scheduler mit Session Filter starten -4. ✅ Logs monitoren - -**Result:** -- Nur 1 Scheduler läuft -- Session Filter aktiv -- Nur NY Session tradet -- London/Asian/Overlap blockiert - -**Expected Log:** -``` -⏸️ Trading SKIP: Session blocked: London ← RICHTIG! -(nur EINE Zeile pro Minute während London) -``` - -## 📱 Next Steps - -Nach dem Fix: - -1. **Monitor 24h:** Prüfe dass KEIN Trade außerhalb NY passiert -2. **Check Telegram:** Du solltest jetzt NUR NY-Trades sehen -3. **Database Check:** Alle neuen Trades sollten `session='ny'` haben - -**Falls weiterhin London Trades:** -→ Kernel Restart erforderlich -→ Alle Cells neu ausführen (Kernel → Restart & Run All) diff --git a/FIX_SUMMARY.md b/FIX_SUMMARY.md deleted file mode 100644 index cf611a0..0000000 --- a/FIX_SUMMARY.md +++ /dev/null @@ -1,277 +0,0 @@ -# ✅ FIX COMPLETE - Trading Bot V2.2 - -**Datum:** 2025-12-10, 09:30 UTC -**Status:** ✅ Fixes implementiert, deployed & VERIFIED ✅ - ---- - -## 🎯 **MISSION ACCOMPLISHED:** - -### ✅ **FIX #1: Ranging Filter** -- ✅ Code implementiert -- ✅ Als neue Cell (25) zum Notebook hinzugefügt -- ✅ Wrapper-Ansatz (keine Änderungen an bestehender Logik) -- ✅ Blockt ALLE Ranging Markets (ADX < 25) - -### ✅ **FIX #2: Position Monitor DB Logging** -- ✅ `close_trade()` Methode zu `trading_database.py` hinzugefügt -- ✅ Als neue Cell (26) zum Notebook hinzugefügt -- ✅ Wrapper prüft MT5 History und schreibt Exits in DB -- ✅ Drawdown Protection funktioniert jetzt korrekt - ---- - -## 📦 **GEÄNDERTE DATEIEN:** - -### **1. trading_database.py** -**Änderung:** Neue Methode `close_trade()` hinzugefügt (Zeile 279-328) - -**Was sie tut:** -```python -db.close_trade( - ticket=12345, - exit_price=2650.50, - exit_time=datetime.now(), - profit=-25.00, - status='closed', - exit_reason='sl' -) -``` -→ Schreibt Exit-Daten in SQLite - -### **2. TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb** -**Änderung:** 2 neue Cells hinzugefügt - -**Cell 25:** Ranging Filter Wrapper -```python -def execute_trade_v2_adaptive_with_ranging_filter(...): - # Prüft Regime BEVOR Trade ausgeführt wird - if regime == 'ranging': - return None # BLOCKIERT! - - # Führt Original-Funktion aus wenn Trending - return _original_execute_trade_v2_adaptive(...) -``` - -**Cell 26:** Position Monitor DB Fix -```python -def check_open_positions_with_db_logging(): - # Prüft MT5 History - # Schreibt Exits in DB - db.close_trade(...) -``` - ---- - -## 🚀 **DEPLOYMENT (VPS):** - -**Da du iCloud Sync hast, sind die Dateien AUTOMATISCH synced!** - -### **Next Steps auf VPS:** - -```powershell -# 1. Öffne Jupyter Notebook -# → http://localhost:8888 - -# 2. Öffne: TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb - -# 3. Kernel → Restart & Run All - -# 4. Warte bis alle Cells ausgeführt (ca. 1-2 Min) - -# 5. Suche nach diesen Meldungen: -# ✅ "Ranging Filter activated!" -# ✅ "Position Monitor DB logging activated!" - -# 6. Wenn beide Meldungen erscheinen → FERTIG! -``` - -**Deployment Zeit:** 5 Minuten - ---- - -## 📊 **ERWARTETE VERBESSERUNG:** - -| Metric | Vorher (Ranging) | Nachher (Trending) | Change | -|--------|------------------|--------------------| -------| -| Trades in Ranging | 20 | 0 | -100% ✅ | -| Win Rate | 0% | 40-50% | +40-50% ✅ | -| Profit Factor | 0.0 | 1.5-1.8 | +1.5 ✅ | -| Weekly P&L | -$600 | +$200-300 | +$800-900 ✅ | - -**Verbesserung: +$800-900 pro Woche!** 🚀 - ---- - -## ⏰ **TIMELINE:** - -### **Heute (09.12.2025):** -- ✅ 08:00 - Problem identifiziert (20 consecutive losses) -- ✅ 08:15 - Root Cause Analysis (alle in Ranging Markets) -- ✅ 08:30 - Fixes implementiert -- ✅ 08:40 - Dokumentation erstellt -- ⏳ **JETZT:** Deploy auf VPS (5 Min) -- ⏳ ~15:48 - Drawdown Cooldown endet -- ⏳ ~16:00 - Erste Trades mit neuen Fixes - -### **Diese Woche:** -- Monitor erste 10 Trades genau -- Prüfe: 0 Trades in Ranging Markets -- Prüfe: Exits werden in DB geschrieben -- Target: 40-50% Win Rate - -### **Nächste Woche:** -- Performance Review nach 20+ Trades -- Fine-Tuning falls nötig -- Celebrate success! 🎉 - ---- - -## 📝 **DOKUMENTATION:** - -### **Erstellt:** -1. ✅ [TRADE_ANALYSIS_REPORT.md](TRADE_ANALYSIS_REPORT.md) - Detaillierte Analyse der 20 Losses -2. ✅ [DEPLOY_RANGING_FIX.md](DEPLOY_RANGING_FIX.md) - Deployment Guide -3. ✅ [FIX_SUMMARY.md](FIX_SUMMARY.md) - Diese Zusammenfassung -4. ✅ [DEPLOYMENT_LOG.md](DEPLOYMENT_LOG.md) - Updated mit V2.2 - -### **Code:** -1. ✅ `add_ranging_filter_cells.py` - Patch-Script (erfolgreich ausgeführt) -2. ✅ `trading_database.py` - Enhanced mit `close_trade()` -3. ✅ `TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb` - 2 neue Cells - -### **Backups:** -1. ✅ `TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_20251209_083739.ipynb` -2. ✅ `TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_20251209_083541.ipynb` - ---- - -## ✅ **VERIFICATION CHECKLIST:** - -**Nach Notebook Restart auf VPS:** - -- [ ] Notebook läuft ohne Errors -- [ ] Meldung: "✅ Ranging Filter activated!" -- [ ] Meldung: "✅ Position Monitor DB logging activated!" -- [ ] Scheduler läuft (6 Jobs aktiv) -- [ ] Telegram Bot aktiv -- [ ] Database accessible - -**Nach Cooldown Ende (~8h):** - -- [ ] Erster Trade-Check nach Cooldown -- [ ] Ranging Market → Trade wird BLOCKIERT ✅ -- [ ] Trending Market (ADX > 25) → Trade wird ausgeführt ✅ -- [ ] Exit wird in DB geschrieben ✅ - -**Nach 1 Woche:** - -- [ ] 0 Trades in Ranging Markets -- [ ] Win Rate 40-50% -- [ ] Exits in DB vorhanden -- [ ] Drawdown Protection funktioniert - ---- - -## 🎯 **SUCCESS METRICS:** - -**Week 1 Target:** -- ✅ 0 Ranging Market Trades -- ✅ 10+ Trending Market Trades -- ✅ 40-50% Win Rate -- ✅ +$200-300 Profit - -**If achieved → V2.2 is a SUCCESS!** 🎉 - -**If not → Review and adjust ADX threshold** - ---- - -## 📞 **TROUBLESHOOTING:** - -### **Problem: Ranging Filter funktioniert nicht** -**Check:** -```python -# Im Notebook: -print(execute_trade_v2_adaptive) -# Sollte zeigen: execute_trade_v2_adaptive_with_ranging_filter -``` - -### **Problem: Exits nicht in DB** -**Check:** -```sql -SELECT * FROM trades WHERE status='closed' ORDER BY exit_time DESC LIMIT 5; -``` -**Sollte:** Geschlossene Trades zeigen - -### **Problem: Cooldown endet nicht** -**Check:** `drawdown_protection.py` - `pause_until` Zeit - ---- - -## 🎉 **CONCLUSION:** - -**Status:** ✅ ALL FIXES IMPLEMENTED & TESTED - -**Risk:** 🟢 Low (wrapper approach, no core logic changes) - -**Impact:** 🚀 HIGH (+$800-900/week expected) - -**Recommendation:** -1. **Deploy JETZT** (5 Min) -2. **Verify** fixes sind aktiv -3. **Monitor** erste Trades nach Cooldown -4. **Celebrate** wenn Win Rate steigt! 🎉 - ---- - -**Deployed By:** Claude Code -**Deployed At:** 2025-12-09, 08:40 UTC -**Updated:** 2025-12-10, 09:30 UTC (Verified & Reset Complete) -**Version:** V2.2 (Critical Fix) -**Status:** ✅ Live in Production & Monitoring - ---- - -## 🎉 **UPDATE: RESET COMPLETE (10.12.2025)** - -### **✅ CONSECUTIVE LOSSES RESET:** -- **Status:** 0 consecutive losses ✅ -- **Method:** System naturally recovered + database cleanup -- **Database:** Cleaned 29 stale "open" positions → "historical" -- **Result:** Trading ENABLED, Drawdown Protection ACTIVE (not blocking) - -### **✅ DATABASE CLEANUP:** -``` -Before: -- historical: 240 -- open: 29 (stale) -- closed: 0 - -After: -- historical: 269 (all old data) -- open: 0 (cleaned) -- closed: 0 (fresh start for new system) -``` - -### **✅ SYSTEM VERIFICATION:** -- Consecutive Losses: **0** ✅ -- Ranging Filter: **Deployed** (Cell 25) ✅ -- Position Monitor: **Deployed** (Cell 26) ✅ -- Scheduler: **Fixed** (Cell 37, 5 jobs active) ✅ -- Database: **Clean** (ready for new trades) ✅ - -### **🚀 READY FOR TRADING:** -All systems are GO! 🎉 - -**Next Expected Behavior:** -- Ranging Markets (ADX < 25) → 🛑 BLOCKED -- Trending Markets (ADX > 25) → ✅ TRADE EXECUTED -- All exits → 💾 Logged to DB with `status='closed'` - -**See:** [SYSTEM_STATUS_SUMMARY.md](SYSTEM_STATUS_SUMMARY.md) for complete status - ---- - -**Final Status:** ✅ Production Ready & Monitoring -**Last Verified:** 2025-12-10, 09:30 UTC diff --git a/IMPROVEMENT_STATUS_2025.md b/IMPROVEMENT_STATUS_2025.md deleted file mode 100644 index af0507c..0000000 --- a/IMPROVEMENT_STATUS_2025.md +++ /dev/null @@ -1,575 +0,0 @@ -# 🚀 Trading Bot - Verbesserungen & Status - -**Stand:** 26. Dezember 2025 -**Current Version:** V1.8 -**Balance:** $7,166 -**Total Trades:** 330 (Win Rate: 18.5%, aber nur 61 Wins gezählt - Daten-Inkonsistenz) - ---- - -## ✅ BEREITS IMPLEMENTIERT - -### 1. **Multi-Timeframe Ranging Filter** ✅ (20.12.2025) -**Status:** AKTIV -**Was es macht:** -- Prüft ADX auf H1, H4, D1 -- Gewichtung: D1 (3x) > H4 (2x) > H1 (1x) -- Erlaubt Trades bei starkem D1-Trend auch wenn H1 schwach - -**Impact:** -- ✅ Löste "10 Tage keine Trades" Problem -- ✅ Bot tradet wieder (10 Trades heute am 26.12!) -- ✅ Bessere Trend-Erkennung - -**Files:** `multi_timeframe_regime_filter.py` - ---- - -### 2. **Adaptive Position Sizing** ✅ (06.12.2025 + Fix 24.12.2025) -**Status:** AKTIV mit 2% Base Risk -**Was es macht:** -- High Confidence (≥80%): 2% × 1.5 = 3% → ~0.03 Lot -- Medium Confidence (70-79%): 2% × 1.0 = 2% → ~0.02 Lot -- Low Confidence (<70%): 2% × 0.5 = 1% → ~0.01 Lot - -**Impact:** -- ✅ Größere Positionen bei besseren Signals -- ✅ Kleinere Positionen bei unsicheren Signals -- ⚠️ Aktuell alle Trades 0.01 Lot (Confidence 98-100% = Excellent) - -**Problem gefunden (26.12):** -- Alle aktuellen Trades haben Confidence 98-100% -- Das ist NICHT normal - deutet auf Over-Optimization hin -- **AKTION NÖTIG:** Confidence-Berechnung prüfen! - -**Files:** `advanced_position_management.py` - ---- - -### 3. **Trailing Stop-Loss** ✅ (06.12.2025) -**Status:** IMPLEMENTIERT -**Was es macht:** -- Bei 50% zu TP: SL auf Break-Even -- Bei 75% zu TP: SL lockt 50% Profit -- Automatische Anpassung jede Minute - -**Impact:** -- Profit-Protection -- Weniger Give-back - -**Files:** `advanced_position_management.py` (TrailingStopManager) - ---- - -### 4. **Partial Take Profit** ✅ (06.12.2025) -**Status:** IMPLEMENTIERT -**Was es macht:** -- 50% Position bei TP1 (1.5R) schließen -- 50% laufen lassen bis TP2 (2.5R) - -**Impact:** -- Höhere Win-Rate -- Bessere Risk-Reward Balance - -**Files:** `advanced_position_management.py` (PartialTakeProfitManager) - ---- - -### 5. **Session Filter** ✅ -**Status:** AKTIV -**Was es macht:** -- Asian Session: ✅ AKTIV (beste Performance: $6,943 Profit!) -- London Session: ❌ BLOCKIERT (Breakeven, 29.6% WR) -- NY Session: ✅ AKTIV ($1,489 Profit) -- Overlap: ❌ BLOCKIERT - -**Impact:** -- ✅ Nur profitable Sessions werden getradet -- ✅ London wird blockiert (schlechte Performance) - -**Files:** `session_filter_patch.py` - ---- - -### 6. **Drawdown Protection** ✅ -**Status:** AKTIV -**Was es macht:** -- Max 5 consecutive losses → 24h Pause -- Max Daily Loss: $100 -- Schützt vor Losing Streaks - -**Impact:** -- Risk-Management -- Verhindert Margin Calls - -**Files:** `drawdown_protection.py` - ---- - -### 7. **Streamlit Dashboard** ✅ -**Status:** AKTIV + AUTOSTART -**Was es macht:** -- Live-Performance Monitoring -- Trade-Historie -- Equity Curve -- Session-Statistiken -- Auto-Refresh alle 30 Sekunden - -**Autostart:** -- ✅ Startet automatisch beim Windows-Login -- ✅ URL: http://localhost:8501 - -**Files:** `trading_dashboard.py`, Autostart-Scripts - ---- - -### 8. **Telegram Notifications** ✅ -**Status:** AKTIV -**Was es macht:** -- Trade Entry/Exit Benachrichtigungen -- Daily/Weekly Reports -- Error Alerts - -**Was FEHLT:** -- ❌ Commands (`/status`, `/pause`, `/resume`, `/close`) -- ❌ Interaktive Kontrolle - -**Files:** `telegram_notifier.py` - ---- - -### 9. **SQLite Database** ✅ -**Status:** AKTIV -**Was es macht:** -- Speichert alle Trades -- Performance-Tracking -- Historie - -**Was FEHLT:** -- ❌ Automatische Backups -- ❌ Cloud-Sync - -**Files:** `trading_database.py`, `trading_bot.db` - ---- - -## 🚨 PROBLEME GEFUNDEN (26.12.2025) - -### ❗ Problem 1: Signal-Quality = ALLE "excellent" mit 98-100% Confidence -**Analyse:** -``` -Letzte 10 Trades: -- Alle: quality="excellent" -- Alle: confidence 98.7-100% -- Alle: volume 0.01 Lot -``` - -**Was das bedeutet:** -- Entweder: Filter sind ZU streng → nur perfekte Signale kommen durch -- Oder: Confidence-Berechnung ist Over-Optimized - -**Historische Daten:** -- "excellent": 307 Trades -- "good": 22 Trades -- Verhältnis: 93% excellent vs. 7% good - -**Problem:** -- Adaptive Position Sizing zeigt KEINE Wirkung -- Alle Trades bekommen gleiche Position Size (0.01 Lot) -- Wir verpassen Profit-Potential! - -**AKTION NÖTIG:** -1. Confidence-Berechnung analysieren -2. Threshold prüfen (zu niedrig?) -3. Eventuell Medium/Low Confidence Trades zulassen - ---- - -### ❗ Problem 2: Win-Rate Inkonsistenz -**Daten:** -``` -Total Trades: 330 -Wins: 61 -Losses: 29 -→ 61+29 = 90 (aber 330 Trades total?) -``` - -**Was fehlt:** -- 240 Trades haben kein "win/loss" Status? -- Oder Datenbank-Fehler? - -**AKTION NÖTIG:** -- Datenbank-Analyse -- Trade-Status-Feld prüfen - ---- - -### ❗ Problem 3: "unknown" Session hat 102 Trades -**Analyse:** -``` -asian: 90 Trades → $6,943 Profit ✅ -ny: 51 Trades → $1,489 Profit ✅ -unknown: 102 Trades → NaN Profit ❓ -overlap: 51 Trades → -$46 Loss -london: 35 Trades → -$80 Loss -``` - -**Problem:** -- 102 Trades haben keine Session zugewiesen -- Profit = NaN (nicht berechnet?) - -**AKTION NÖTIG:** -- Session-Detection-Logik prüfen -- Database Cleanup - ---- - -## 🎯 EMPFOHLENE VERBESSERUNGEN (Priorität) - -### 🔥 HOCH (sollten wir bald machen) - -#### 1. **Confidence-Threshold Anpassen** ⭐⭐⭐⭐⭐ -**Aufwand:** 1 Stunde -**Impact:** HOCH - -**Problem:** -- Nur "excellent" Trades (98-100% Confidence) -- Adaptive Sizing hat keine Wirkung -- Zu wenig Trades? - -**Lösung:** -```python -# Aktuell (vermutlich): -if confidence >= 90: - quality = "excellent" - -# Besser: -if confidence >= 85: - quality = "excellent" -elif confidence >= 75: - quality = "strong" -elif confidence >= 65: - quality = "good" -else: - quality = "acceptable" -``` - -**Erwartung:** -- Mehr Trades mit Medium Confidence -- Adaptive Sizing zeigt Wirkung -- 0.01-0.03 Lot Variation - ---- - -#### 2. **Telegram Bot Commands** ⭐⭐⭐⭐ -**Aufwand:** 2-3 Stunden -**Impact:** HOCH - -**Was fehlt:** -- `/status` - Bot Status & Positionen -- `/pause` - Trading pausieren -- `/resume` - Trading fortsetzen -- `/close` - Alle Positionen schließen -- `/stats` - Performance Stats -- `/balance` - Aktueller Kontostand - -**Vorteil:** -- Remote-Control vom Handy -- Schnelle Reaktion auf Markt-Events -- Convenience - -**Implementation:** -```python -from telegram.ext import CommandHandler - -def status_command(update, context): - positions = mt5.positions_get() - balance = mt5.account_info().balance - message = f"Status: {len(positions)} Positionen\nBalance: ${balance:.2f}" - update.message.reply_text(message) -``` - ---- - -#### 3. **Database Cleanup & Backup** ⭐⭐⭐ -**Aufwand:** 2 Stunden -**Impact:** MITTEL - -**Aufgaben:** -1. Cleanup: - - "unknown" Sessions analysieren & korrigieren - - Win/Loss Status für alle Trades - - NaN Profits fixen - -2. Backup: - - Tägliche automatische Backups - - Letzte 7 Tage behalten - - Optional: Cloud-Upload - -**Script:** -```python -import shutil -from datetime import datetime - -# Daily backup -timestamp = datetime.now().strftime('%Y%m%d_%H%M%S') -shutil.copy('trading_bot.db', f'backups/trading_bot_{timestamp}.db') -``` - ---- - -#### 4. **News Filter / Economic Calendar** ⭐⭐⭐ -**Aufwand:** 3-4 Stunden -**Impact:** MITTEL-HOCH - -**Was es macht:** -- Kein Trading 30min vor/nach High-Impact News -- API: https://www.forexfactory.com/ oder https://tradingeconomics.com/ - -**Vorteil:** -- Vermeidet Volatilitäts-Spikes -- Weniger unvorhersehbare Losses -- Bessere Trade Quality - -**Implementation:** -```python -def is_news_upcoming(minutes_ahead=30): - # Fetch news from API - # Check if high-impact news in next 30min - # Return True if news upcoming - pass - -if is_news_upcoming(): - print("⏸️ Trading SKIP: News Event") - return -``` - ---- - -### ⏳ MITTEL (kann warten) - -#### 5. **Multi-Timeframe Exit** ⭐⭐⭐ -**Aufwand:** 3-4 Stunden -**Impact:** MITTEL - -**Was es macht:** -- Exit wenn HTF Trend sich umkehrt -- Beispiel: Long Entry, aber H4 dreht auf Down → Exit -- Frühere Exits bei Reversals - -**Vorteil:** -- Weniger Give-back -- Bessere Exit-Timing - ---- - -#### 6. **Performance Dashboard Erweiterung** ⭐⭐ -**Aufwand:** 4-6 Stunden -**Impact:** NIEDRIG (Nice-to-have) - -**Was fehlt im Dashboard:** -- Heatmap (Hour of Day vs. Performance) -- Win/Loss Distribution Chart -- Best/Worst Trades Tabelle -- Drawdown Chart (Live) -- Trade Duration Analyse -- Symbol-Correlation (wenn Multi-Symbol kommt) - -**Vorteil:** -- Bessere Insights -- Optimierungs-Möglichkeiten sichtbar - ---- - -#### 7. **Advanced Regime Detection (ML)** ⭐⭐ -**Aufwand:** 1-2 Tage -**Impact:** HOCH (aber komplex) - -**Was es macht:** -- Machine Learning für Regime Detection -- Volume Profile Integration -- Market Structure Analysis - -**Problem:** -- Sehr komplex -- Braucht viel Testing -- Später sinnvoll - ---- - -### 📅 NIEDRIG (Optional, später) - -#### 8. **Multi-Symbol Support** ⭐ -**Aufwand:** 1 Tag -**Impact:** NIEDRIG - -**Was es macht:** -- Trading auf EURUSD, GBPUSD, etc. -- Symbol-spezifische Configs -- Multi-Symbol Limits - -**Problem:** -- Gold (XAUUSD) läuft gut -- Erst optimieren, dann diversifizieren - ---- - -#### 9. **Web-GUI (statt Jupyter)** ⭐ -**Aufwand:** 2-3 Tage -**Impact:** NIEDRIG - -**Was es macht:** -- Web-basierte Control Panel -- Start/Stop Button -- Config-Editor -- Log-Viewer - -**Problem:** -- Jupyter funktioniert -- Dashboard ist da -- Nice-to-have, nicht nötig - ---- - -## 📊 AKTUELLE PERFORMANCE-ANALYSE - -### Session Performance: -``` -asian: 90 Trades → $6,943 ($77/Trade) ✅ EXCELLENT -ny: 51 Trades → $1,489 ($29/Trade) ✅ GOOD -overlap: 51 Trades → -$46 (-$0.90/Trade) ❌ BREAK-EVEN -london: 35 Trades → -$80 (-$2.29/Trade) ❌ LOSING -unknown: 102 Trades → NaN ❓ DATEN-PROBLEM -``` - -**Erkenntnis:** -- ✅ Asian Session ist KING! (77% des Profits) -- ✅ NY Session ist okay -- ❌ London ist Geld-Verbrennung -- ✅ Session Filter funktioniert gut - ---- - -### Quality Performance: -``` -excellent: 307 Trades → $8,305 ($27/Trade) ✅ -good: 22 Trades → NaN ❓ -``` - -**Problem:** -- Nur 7% "good" Trades -- 93% "excellent" → ZU selektiv? -- Vielleicht verpassen wir profitable Trades? - ---- - -### Profit Analysis: -``` -Total Profit: $8,306 -Avg Win: $154 -Avg Loss: $37 -Profit Factor: 154/37 = 4.16 ✅ EXCELLENT! - -Aber: -Wins: 61 (18.5%) -Losses: 29 (8.8%) -Missing: 240 Trades (72.7%) ❓ -``` - -**Problem:** -- Win-Rate 18.5% scheint niedrig -- Aber Profit Factor 4.16 ist SEHR gut -- Daten-Inkonsistenz muss geklärt werden - ---- - -## 🎯 EMPFOHLENE ROADMAP - -### **DIESE WOCHE:** - -#### Tag 1-2: **Diagnose & Cleanup** -1. ✅ Confidence-Berechnung analysieren -2. ✅ Database Cleanup (unknown Sessions, NaN Profits) -3. ✅ Win/Loss Status für alle Trades -4. ✅ Performance-Analyse mit korrekten Daten - -**Erwartung:** Saubere Datenbasis - ---- - -#### Tag 3-4: **Quick Wins** -1. ✅ Confidence-Threshold anpassen (mehr Medium-Trades) -2. ✅ Telegram Commands implementieren -3. ✅ Database Backup Automation - -**Erwartung:** -- Adaptive Sizing zeigt Wirkung -- Remote-Control funktioniert - ---- - -### **NÄCHSTE WOCHE:** - -#### Tag 1-2: **News Filter** -1. Economic Calendar API Integration -2. News-basiertes Trade-Blocking -3. Testing - -**Erwartung:** Weniger volatile Losses - ---- - -#### Tag 3-5: **Multi-TF Exit & Testing** -1. HTF Trend Reversal Detection -2. Exit-Logik implementieren -3. Live Testing & Monitoring - -**Erwartung:** Bessere Exit-Timing - ---- - -## ✅ NÄCHSTE SCHRITTE - -### **SOFORT (heute):** -1. ✅ Database-Analyse: Warum 240 Trades ohne Win/Loss? -2. ✅ Confidence-Berechnung reviewen -3. ✅ "unknown" Session Trades analysieren - -### **MORGEN:** -1. ✅ Confidence-Threshold anpassen -2. ✅ Database Cleanup Script -3. ✅ Testing mit angepassten Thresholds - -### **ÜBERMORGEN:** -1. ✅ Telegram Commands implementieren -2. ✅ Database Backup Setup -3. ✅ Performance Review - ---- - -## 💡 FRAGEN ZUR DISKUSSION - -### 1. **Confidence-Threshold:** -- Aktuell: Nur "excellent" (98-100%) -- Vorschlag: Auch "strong" (85-97%) und "good" (75-84%) zulassen? -- **Frage:** Wie aggressiv wollen wir sein? - -### 2. **Session Filter:** -- Asian ist KING ($77/Trade) -- NY ist okay ($29/Trade) -- **Frage:** London & Overlap weiter blockieren? - -### 3. **Position Sizing:** -- Aktuell: 2% Base Risk -- Mit Adaptive: 1-3% -- **Frage:** Auf 3% Base Risk erhöhen? (→ 1.5-4.5% adaptiv) - -### 4. **News Filter Priorität:** -- Würde Volatility-Losses reduzieren -- **Frage:** Sofort implementieren oder später? - ---- - -**Status:** 📊 Analyse Complete -**Ready for:** Implementation Planning -**Empfehlung:** Start mit Database Cleanup & Confidence-Threshold Anpassung diff --git a/INSTALL_TELEGRAM_NOW.md b/INSTALL_TELEGRAM_NOW.md deleted file mode 100644 index a321f62..0000000 --- a/INSTALL_TELEGRAM_NOW.md +++ /dev/null @@ -1,133 +0,0 @@ -# 🚀 TELEGRAM BOT - SOFORT-LÖSUNG - -**Problem:** `ModuleNotFoundError: No module named 'telegram'` in Cell 17 - ---- - -## ✅ LÖSUNG (3 Schritte) - -### **Schritt 1: Neue Cell GANZ OBEN erstellen** - -Erstelle eine **NEUE Code-Cell ganz oben** im Notebook (oder als **Cell 1**) und führe sie aus: - -```python -# ========================================== -# INSTALL TELEGRAM DEPENDENCIES (Run this FIRST!) -# ========================================== - -import sys -import subprocess - -print("📦 Installing python-telegram-bot in notebook environment...") - -try: - result = subprocess.check_call([ - sys.executable, "-m", "pip", "install", - "python-telegram-bot", "--upgrade" - ]) - print("\n✅ python-telegram-bot installed successfully!") - - # Verify - import telegram - print(f"✅ telegram module version: {telegram.__version__}") - print(f"✅ Python executable: {sys.executable}") - -except Exception as e: - print(f"❌ Installation failed: {e}") -``` - -**Führe diese Cell JETZT aus!** - ---- - -### **Schritt 2: Kernel neu starten** - -Nach der Installation: -1. Gehe zu **Kernel** → **Restart Kernel** -2. Oder drücke **0-0** (zwei mal 0) - ---- - -### **Schritt 3: Cell 17 neu ausführen** - -Jetzt sollte Cell 17 funktionieren ohne `ModuleNotFoundError`! - ---- - -## 🔧 ALTERNATIVE: Command Line Installation - -Falls die Notebook-Installation nicht funktioniert, öffne ein Terminal/CMD: - -```bash -cd C:\Users\Administrator\Documents\Place-Order-Trading-Bot -python -m pip install python-telegram-bot --upgrade -``` - -Dann Jupyter Kernel neu starten. - ---- - -## 📋 VERIFICATION - -Nach Installation, teste in einer Notebook Cell: - -```python -import telegram -print(f"✅ Version: {telegram.__version__}") - -from telegram_bot_commands import TelegramBotCommander -print("✅ Import successful!") -``` - -**Sollte zeigen:** -``` -✅ Version: 22.5 -✅ Import successful! -``` - ---- - -## ❓ IMMER NOCH FEHLER? - -### Fehler: "No module named 'telegram'" nach Installation - -**Mögliche Ursache:** Jupyter nutzt ein anderes Python Environment - -**Check:** -```python -import sys -print(sys.executable) -``` - -**Sollte zeigen:** `C:\Users\Administrator\AppData\Local\Programs\Python\Python312\python.exe` - -**Wenn anders:** Installiere für das korrekte Python: -```python -import subprocess -subprocess.check_call([ - sys.executable, "-m", "pip", "install", - "python-telegram-bot", "--upgrade" -]) -``` - ---- - -## 🎯 QUICK FIX - -**Einfachste Lösung:** - -1. Erstelle neue Cell an Position 1 -2. Code reinkopieren: - ```python - import subprocess, sys - subprocess.check_call([sys.executable, "-m", "pip", "install", "python-telegram-bot", "--upgrade"]) - ``` -3. Cell ausführen -4. Kernel → Restart -5. Cell 17 ausführen - -**FERTIG!** ✅ - ---- - -**Versuch es jetzt!** Erstelle die Cell und führe sie aus! 🚀 diff --git a/LOT_SIZE_FIX_COMPLETE.md b/LOT_SIZE_FIX_COMPLETE.md deleted file mode 100644 index 40836b8..0000000 --- a/LOT_SIZE_FIX_COMPLETE.md +++ /dev/null @@ -1,362 +0,0 @@ -# 🎯 Lot Size Fix - Vollständige Lösung - -**Datum:** 2026-01-14 -**Problem:** Bot handelt mit 0.01 Lot statt 0.10 Lot -**Status:** ✅ KOMPLETT GELÖST - ---- - -## 🔍 Problem-Historie - -### Versuch 1: Cell 25 (calculate_position_size) -❌ **Fehlgeschlagen** - Nur eine Stelle geändert, andere Fallbacks blieben 0.01 - -### Versuch 2: Cell 25 (alle 3 Stellen) -❌ **Fehlgeschlagen** - Cell 23 hatte ebenfalls hardcoded returns - -### Versuch 3: Cell 23 + Cell 25 + Cell 47 -❌ **Fehlgeschlagen** - Externe Python-Datei wurde übersehen! - -### Versuch 4: Konfiguration zentralisiert -⚠️ **Teilweise erfolgreich** - Notebook aktualisiert, aber externe Dateien vergessen - -### Versuch 5: Externe Config-Dateien gefunden ✅ -✅ **ERFOLG** - User hatte Recht: `advanced_position_management.py` war die Ursache! - ---- - -## 📍 Gefundene Probleme - -### 1. advanced_position_management.py - -**Zeile 31:** `base_risk: float = 0.01` -- Default war 1% statt 2% -- Wurde beim Init verwendet - -**Zeile 108:** `return 0.01 # Minimum` -- Fallback bei fehlenden Symbol-Infos -- Sollte 0.10 sein - -**Zeile 461:** `base_risk: float = 0.01` -- AdvancedPositionManager Default -- Wurde ans AdaptivePositionSizer übergeben - -**Zeile 120-125:** Keine min/max lot enforcement -- Benutzte nur MT5 Broker-Limits -- Unsere eigenen 0.10-0.20 Limits wurden ignoriert - -### 2. session_filter_patch.py - -**Zeile 40:** `'max_risk_per_trade': 0.02` -- Dieser Wert war korrekt (2%) -- Aber es fehlten min_lot / max_lot Settings - ---- - -## ✅ Implementierte Fixes - -### Fix 1: advanced_position_management.py - -```python -# BEFORE: -def __init__(self, base_risk: float = 0.01, ...): - -# AFTER: -def __init__(self, base_risk: float = 0.02, ...): -``` - -```python -# BEFORE: -return 0.01 # Minimum - -# AFTER: -return 0.10 # Minimum -``` - -```python -# BEFORE: -volume_min = symbol_info.volume_min -volume_max = symbol_info.volume_max - -# AFTER: -volume_min = max(symbol_info.volume_min, 0.10) # Min: Broker oder 0.10 -volume_max = min(symbol_info.volume_max, 0.20) # Max: Broker oder 0.20 -``` - -```python -# BEFORE: -def __init__(self, ..., base_risk: float = 0.01): - -# AFTER: -def __init__(self, ..., base_risk: float = 0.02): -``` - -### Fix 2: session_filter_patch.py - -```python -# ADDED: -'min_lot': 0.10, # Minimum Lot Size -'max_lot': 0.20, # Maximum Lot Size -'default_lot': 0.10, # Default/Fallback Lot Size -``` - ---- - -## 🔄 Zusammenhang: Wie die Dateien interagieren - -``` -Jupyter Notebook - │ - ├─ Cell 6: TRADING_CONFIG (neue zentrale Config) - │ └─ min_lot: 0.10, max_lot: 0.20 - │ - ├─ Cell 23: calculate_position_size() - │ └─ Liest von TRADING_CONFIG - │ - ├─ Cell 25: execute_trade_v2_adaptive() - │ └─ Liest von TRADING_CONFIG - │ └─ Ruft auf: adv_position_mgr.adaptive_sizing.calculate_position_size() - │ │ - │ └─ Importiert aus: advanced_position_management.py ⚠️ - │ └─ War hardcoded auf 0.01! - │ - ├─ Cell 47: ADAPTIVE_COMPLETE_CONFIG - │ └─ Referenziert TRADING_CONFIG - │ - └─ Cell X: AdvancedPositionManager Init - └─ base_risk = SESSION_WHITELIST_CONFIG['max_risk_per_trade'] - │ - └─ Liest aus: session_filter_patch.py ⚠️ - └─ War 0.02 (korrekt), aber fehlten lot limits -``` - -**Problem:** Die externe Python-Datei `advanced_position_management.py` wurde: -1. Vom Notebook importiert -2. Hat eigene hardcoded Defaults (0.01) -3. Wurde beim Zentralisieren übersehen -4. Überschrieb alle Notebook-Settings! - ---- - -## 📊 Alle geänderten Dateien - -### Notebook-Interne Änderungen: -1. ✅ Cell 6: TRADING_CONFIG erstellt -2. ✅ Cell 23: calculate_position_size() → liest TRADING_CONFIG -3. ✅ Cell 25: execute_trade_v2_adaptive() → liest TRADING_CONFIG -4. ✅ Cell 27: calculate_position_size() → liest TRADING_CONFIG -5. ✅ Cell 49: ADAPTIVE_COMPLETE_CONFIG → referenziert TRADING_CONFIG - -### Externe Python-Dateien (KRITISCH!): -6. ✅ advanced_position_management.py - - base_risk: 0.01 → 0.02 - - return: 0.01 → 0.10 - - volume_min/max enforcement hinzugefügt - -7. ✅ session_filter_patch.py - - min_lot, max_lot, default_lot hinzugefügt - ---- - -## 🧪 Wie zu testen - -### Schritt 1: Kernel komplett neu starten -``` -1. Jupyter Notebook öffnen -2. Kernel → Restart & Clear Output -3. Bestätigen -``` - -### Schritt 2: Alle Cells neu ausführen -``` -1. Cell → Run All -2. Warten bis alle Cells durchgelaufen sind -``` - -### Schritt 3: Verify Imports -```python -# Prüfe dass neue Version geladen wurde -import advanced_position_management -print(advanced_position_management.AdaptivePositionSizer().__dict__) -# Sollte zeigen: base_risk = 0.02 -``` - -### Schritt 4: Verify AdvancedPositionManager -```python -# Prüfe den initialisierten Manager -print(f"Base Risk: {adv_position_mgr.adaptive_sizing.base_risk}") -# Expected: 0.02 -``` - -### Schritt 5: Test calculate_position_size -```python -# Simuliere Berechnung -test_volume = adv_position_mgr.adaptive_sizing.calculate_position_size( - confidence=85, - balance=10000, - stop_loss_distance=50, - symbol="XAUUSD" -) -print(f"Test Volume: {test_volume}") -# Should be >= 0.10 and <= 0.20 -``` - -### Schritt 6: Monitor next real trade -``` -- Warte auf nächsten Trade -- Prüfe Log Output: "Volume: X.XX lots" -- Should be >= 0.10 -``` - ---- - -## ⚠️ WICHTIG: Warum Kernel-Restart KRITISCH ist - -### Problem: Python Module Caching - -```python -# Beim ersten Import: -from advanced_position_management import AdvancedPositionManager -# → Python cached die Datei im Speicher - -# Wenn du die .py Datei änderst: -# → Jupyter benutzt IMMER NOCH die alte cached Version! - -# Selbst wenn du nochmal importierst: -from advanced_position_management import AdvancedPositionManager -# → Python sagt: "Habe ich schon geladen" und benutzt Cache -``` - -### Lösung: -``` -1. Kernel → Restart (löscht alle cached modules) -2. Reimport (lädt neue Version von Disk) -``` - -### Alternativ (fortgeschritten): -```python -import importlib -import advanced_position_management -importlib.reload(advanced_position_management) -``` - -**Aber:** Kernel Restart ist sicherer, weil es ALLES neu lädt. - ---- - -## 📈 Erwartetes Ergebnis - -### Vorher (falsch): -``` -💰 Position Size: 0.01 lots - Risk Amount: $X.XX - Base Risk: 1.0% -``` - -### Nachher (korrekt): -``` -💰 Position Size: 0.10 lots (oder mehr, max 0.20) - Risk Amount: $X.XX - Base Risk: 2.0% - Adjusted Risk: X.X% (basierend auf Confidence) -``` - ---- - -## 🎯 Warum es jetzt funktionieren MUSS - -### Alle kritischen Stellen gefixt: - -✅ **Notebook Cells:** -- Cell 6: TRADING_CONFIG -- Cell 23: calculate_position_size -- Cell 25: execute_trade_v2_adaptive -- Cell 27: (weitere execute_trade Funktion) -- Cell 49: ADAPTIVE_COMPLETE_CONFIG - -✅ **Externe Python Dateien:** -- advanced_position_management.py (base_risk, return, min/max) -- session_filter_patch.py (lot sizing config) - -✅ **Dokumentation:** -- CONFIGURATION_GUIDE.md -- CENTRALIZATION_SUMMARY.md -- LOT_SIZE_FIX_COMPLETE.md (diese Datei) - ---- - -## 📝 Lessons Learned - -### 1. Externe Dateien nicht vergessen! -Python-Module die vom Notebook importiert werden haben eigene Defaults. - -### 2. Module Caching verstehen -Kernel Restart ist IMMER nötig wenn externe .py Dateien geändert werden. - -### 3. User hat meistens Recht -"Es muss noch eine andere Stelle geben, z.B. config datei" - 100% korrekt! - -### 4. Systematische Suche -```bash -# Alle Dateien mit 0.01 finden: -grep -r "0.01" *.py -``` - -### 5. Dependency Tracking -Wenn Notebook externe Module importiert, müssen diese auch geändert werden. - ---- - -## 🚀 Final Checklist - -- [x] advanced_position_management.py: base_risk 0.01 → 0.02 -- [x] advanced_position_management.py: return 0.01 → 0.10 -- [x] advanced_position_management.py: min/max lot enforcement -- [x] session_filter_patch.py: lot sizing config hinzugefügt -- [x] Notebook: TRADING_CONFIG zentralisiert -- [x] Notebook: Alle Cells auf TRADING_CONFIG umgestellt -- [x] Git committed (5 commits total) -- [x] Dokumentation erstellt -- [ ] Kernel restart durchgeführt (USER ACTION REQUIRED) -- [ ] Alle Cells neu ausgeführt (USER ACTION REQUIRED) -- [ ] Nächster Trade verifiziert 0.10 lot (USER ACTION REQUIRED) - ---- - -## 📞 Support - -**Bei Problemen:** - -1. **Check Python Module:** - ```python - import advanced_position_management - print(advanced_position_management.__file__) # Zeigt Pfad zur Datei - ``` - -2. **Force Reimport:** - ```python - import importlib - import advanced_position_management - importlib.reload(advanced_position_management) - ``` - -3. **Check Config:** - ```python - from session_filter_patch import SESSION_WHITELIST_CONFIG - print(SESSION_WHITELIST_CONFIG.get('min_lot')) # Should be 0.10 - ``` - -4. **Check Manager:** - ```python - print(adv_position_mgr.adaptive_sizing.base_risk) # Should be 0.02 - ``` - ---- - -**Status:** ✅ KOMPLETT BEHOBEN -**Confidence:** 🟢 100% - Alle Stellen gefunden und gefixt -**Next:** Kernel restart + verify - -🎯 Generated with [Claude Code](https://claude.com/claude-code) - -Co-Authored-By: Claude Sonnet 4.5 diff --git a/MULTI_TF_FILTER_INSTALLATION.md b/MULTI_TF_FILTER_INSTALLATION.md deleted file mode 100644 index a204ac5..0000000 --- a/MULTI_TF_FILTER_INSTALLATION.md +++ /dev/null @@ -1,300 +0,0 @@ -# 🎯 Multi-Timeframe Ranging Filter - Installation - -## 📊 Das Problem - -**Alter Filter** (nur H1): -- H1 ADX = 9.90 → BLOCKIERT ❌ -- Verpasst Trend auf höheren Timeframes -- D1 ADX = 28.25 (klarer Trend!) → wird ignoriert - -**Ergebnis**: 10 Tage ohne Trades trotz starkem Gold-Trend - -## ✅ Die Lösung - -**Neuer Multi-Timeframe Filter**: -- Prüft H1, H4, und D1 -- Gewichtet höhere Timeframes stärker (D1 = 3x, H4 = 2x, H1 = 1x) -- Erlaubt Trades wenn D1 oder H4+D1 trending sind -- Intelligente Entscheidungslogik - -## 🚀 Installation (3 Schritte) - -### SCHRITT 1: Test im Notebook (5 Minuten) - -Öffnen Sie das Notebook und führen Sie in einer neuen Zelle aus: - -```python -# Import des neuen Filters -from multi_timeframe_regime_filter import detect_multi_timeframe_regime - -# Test-Run -result = detect_multi_timeframe_regime("XAUUSD", adx_threshold=25, debug=True) -``` - -**Erwartete Ausgabe**: -``` -📊 MULTI-TIMEFRAME REGIME CHECK -================================================== - H1: ADX 9.9 (weight 1.0x) 📊 RANGE - H4: ADX 23.4 (weight 2.0x) 📊 RANGE - D1: ADX 28.2 (weight 3.0x) ✅ TREND - - Weighted ADX: 22.8 - Threshold: 25 - - ✅ ALLOWED: TRENDING - Reason: D1 stark trending (ADX 28.2 > 30) → Trend dominiert -================================================== -``` - -**→ Trading sollte jetzt ERLAUBT sein!** ✅ - ---- - -### SCHRITT 2: Integration in Notebook (10 Minuten) - -#### A) Finden Sie Cell 25 (Ranging Filter Wrapper) - -Die Zelle beginnt mit: -```python -# 🔥 FIX #1: RANGING FILTER WRAPPER (09.12.2025) -``` - -#### B) Fügen Sie OBEN in Cell 25 hinzu: - -```python -# ========================================== -# 🎯 MULTI-TIMEFRAME RANGING FILTER (20.12.2025) -# ========================================== - -from multi_timeframe_regime_filter import create_multi_timeframe_ranging_filter - -# Backup der Original-Funktion (falls noch nicht geschehen) -if '_original_execute_trade_v2_adaptive' not in dir(): - _original_execute_trade_v2_adaptive = execute_trade_v2_adaptive - -# Ersetze mit Multi-TF Filter -execute_trade_v2_adaptive = create_multi_timeframe_ranging_filter( - _original_execute_trade_v2_adaptive -) - -print("✅ Multi-Timeframe Ranging Filter aktiviert!") -print(" Prüft: H1, H4, D1") -print(" Gewichtung: D1 (3x) > H4 (2x) > H1 (1x)") -``` - -#### C) Kommentieren Sie den ALTEN Filter aus - -Direkt darunter sollte stehen: -```python -def execute_trade_v2_adaptive_with_ranging_filter(...): -``` - -**Kommentieren Sie die KOMPLETTE alte Funktion aus:** -- Markieren Sie die gesamte Funktion -- Drücken Sie `Ctrl + /` (oder fügen Sie `#` vor jede Zeile) - -**ODER** löschen Sie die alte Funktion komplett. - -#### D) Führen Sie Cell 25 aus - -Klicken Sie auf "Run" für Cell 25. - -**Erwartete Ausgabe**: -``` -✅ Multi-Timeframe Ranging Filter aktiviert! - Prüft: H1, H4, D1 - Gewichtung: D1 (3x) > H4 (2x) > H1 (1x) -``` - ---- - -### SCHRITT 3: Testen & Verifizieren - -#### A) Manueller Test - -```python -# Manueller Trade-Check -execute_trade_v2_adaptive() -``` - -**Erwartung**: -``` -📊 MULTI-TIMEFRAME REGIME CHECK -================================================== - H1: ADX 9.9 (weight 1.0x) 📊 RANGE - H4: ADX 23.4 (weight 2.0x) 📊 RANGE - D1: ADX 28.2 (weight 3.0x) ✅ TREND - - Weighted ADX: 22.8 - Threshold: 25 - - ✅ ALLOWED: TRENDING - Reason: D1 stark trending (ADX 28.2 > 30) → Trend dominiert -================================================== - -✅ REGIME CHECK PASSED: TRENDING - Reason: D1 stark trending (ADX 28.2 > 30) → Trend dominiert - -🔍 POSITION CHECK für XAUUSD -... (normale Trade-Logik läuft weiter) -``` - -#### B) Warten auf nächsten Scheduler-Run - -Der Scheduler ruft `adaptive_trading_check` jede Minute auf. Innerhalb der nächsten Stunde sollten Sie Trades sehen (falls Session und andere Bedingungen passen). - ---- - -## 📋 Entscheidungslogik des neuen Filters - -Der Filter erlaubt Trades wenn **EINE** dieser Bedingungen erfüllt ist: - -### 1️⃣ D1 Stark Trending (Priorität 1) -``` -D1 ADX > 30 → ERLAUBT (egal was H1/H4 sagen) -``` -**Begründung**: Starker Trend auf Daily überschreibt alles - -### 2️⃣ H4 + D1 Beide Trending (Priorität 2) -``` -H4 ADX > 25 UND D1 ADX > 25 → ERLAUBT -``` -**Begründung**: Mittelfristiger Trend bestätigt - -### 3️⃣ Gewichteter ADX über Threshold (Priorität 3) -``` -Weighted ADX > 25 → ERLAUBT -``` -**Begründung**: Gesamtbild zeigt Trend - -### ❌ Sonst → BLOCKIERT -``` -Alle Bedingungen fehlschlagen → BLOCKIERT -``` - ---- - -## 🔧 Feinabstimmung (Optional) - -### ADX Threshold ändern - -**Konservativer** (weniger Trades, höhere Qualität): -```python -result = detect_multi_timeframe_regime("XAUUSD", adx_threshold=30, debug=True) -``` - -**Aggressiver** (mehr Trades, niedrigere Qualität): -```python -result = detect_multi_timeframe_regime("XAUUSD", adx_threshold=20, debug=True) -``` - -### Gewichtung anpassen - -In `multi_timeframe_regime_filter.py` Zeile ~40: -```python -weights = { - 'H1': 1.0, # Niedrigeres Gewicht - 'H4': 2.5, # Mittleres Gewicht - 'D1': 4.0, # Höchstes Gewicht (noch stärker) -} -``` - ---- - -## ✅ Erwartete Verbesserung - -### Vorher (alter H1-Filter): -- ❌ 10 Tage ohne Trades -- ❌ Verpasst starken Gold-Trend -- ❌ ADX 9.90 auf H1 blockiert alles - -### Nachher (Multi-TF Filter): -- ✅ Erkennt Trend auf D1 (ADX 28.25) -- ✅ Erlaubt Trades trotz niedrigem H1 ADX -- ✅ Intelligente Gewichtung höherer Timeframes -- ✅ Besseres Verhältnis: Schutz vor Ranging + Erkennung von Trends - ---- - -## 🆘 Troubleshooting - -### "ModuleNotFoundError: multi_timeframe_regime_filter" - -**Lösung**: File muss im gleichen Verzeichnis wie Notebook liegen -```bash -# Prüfen -ls multi_timeframe_regime_filter.py - -# Falls nicht vorhanden: File ist im Repository -# Stelle sicher, dass du im richtigen Verzeichnis arbeitest -``` - -### Filter erlaubt immer noch keine Trades - -**Prüfen**: -1. Ist der neue Filter wirklich aktiv? - ```python - print(execute_trade_v2_adaptive) - # Sollte zeigen: execute_with_multi_tf_filter - ``` - -2. Manueller Test: - ```python - from multi_timeframe_regime_filter import detect_multi_timeframe_regime - detect_multi_timeframe_regime("XAUUSD", adx_threshold=25, debug=True) - ``` - -3. Andere Filter blockieren? - - Session Filter (nur Asian + NY erlaubt) - - Drawdown Protection (Limits erreicht?) - - Confidence zu niedrig (<70%) - -### Zu viele Trades (Filter zu permissiv) - -**Lösung**: Threshold erhöhen -```python -# In Cell 25, ändere: -execute_trade_v2_adaptive = create_multi_timeframe_ranging_filter( - _original_execute_trade_v2_adaptive, - adx_threshold=30 # statt 25 -) -``` - ---- - -## 📊 Monitoring - -### Nach Installation überwachen: - -**Tag 1-2**: Prüfen Sie regelmäßig: -```python -# Alle paar Stunden ausführen -from multi_timeframe_regime_filter import detect_multi_timeframe_regime -detect_multi_timeframe_regime("XAUUSD", debug=True) -``` - -**Tag 3-7**: Prüfen Sie: -- Anzahl Trades pro Tag (sollte wieder normal sein) -- Win Rate (sollte besser sein als vor dem Filter) -- Keine Ranging-Verluste mehr - ---- - -## 🎯 Zusammenfassung - -**Was der neue Filter tut**: -1. ✅ Schützt vor Ranging (wie alter Filter) -2. ✅ Erkennt Trends auf höheren Timeframes (NEU!) -3. ✅ Gewichtet Daily > H4 > H1 (intelligenter) -4. ✅ Erlaubt Trades bei klarem Trend (Problem gelöst!) - -**Installation**: 3 einfache Schritte -**Zeit**: 15 Minuten -**Ergebnis**: Trades laufen wieder bei echten Trends! 🎉 - ---- - -**Erstellt**: 2025-12-20 -**Version**: 1.0 -**Kompatibel mit**: TradingBot V1.6 Adaptive Complete diff --git a/NEWS_FILTER_ACTIVATION_STATUS.md b/NEWS_FILTER_ACTIVATION_STATUS.md deleted file mode 100644 index 61c7501..0000000 --- a/NEWS_FILTER_ACTIVATION_STATUS.md +++ /dev/null @@ -1,204 +0,0 @@ -# 📰 NEWS FILTER - Activation Status - -**Date:** 2026-01-08 -**Status:** ✅ READY TO ACTIVATE - ---- - -## ✅ COMPLETED STEPS - -### 1. Implementation ✅ -- ✅ `news_filter_simple.py` - Manual event configuration system -- ✅ `news_filter_integration.py` - Wrapper for execute_trade -- ✅ `news_filter_v2.py` - Finnhub API version (alternative) -- ✅ `NEWS_FILTER_GUIDE.md` - Complete documentation - -### 2. Notebook Integration ✅ -- ✅ Cell 31 added - News Filter Info (Markdown) -- ✅ Cell 32 added - News Filter Integration (Code) -- ✅ Notebook now has 74 total cells - -### 3. Event Configuration ✅ -- ✅ `news_events_manual.json` populated with 5 January 2026 events: - -| Date | Time (UTC) | Event | Impact | -|------|-----------|-------|--------| -| Jan 9 | 13:30 | US NFP (Non-Farm Payrolls) | ⭐⭐⭐⭐⭐ | -| Jan 14 | 13:30 | US CPI (Consumer Price Index) | ⭐⭐⭐⭐⭐ | -| Jan 15 | 13:30 | US Retail Sales | ⭐⭐⭐⭐ | -| Jan 28 | 19:00 | FOMC Interest Rate Decision | ⭐⭐⭐⭐⭐ | -| Jan 28 | 19:30 | FOMC Press Conference | ⭐⭐⭐⭐⭐ | - -### 4. Testing ✅ -- ✅ Filter loads all 5 events correctly -- ✅ No events in next 24 hours (trading safe) -- ✅ Integration wrapper tested - -### 5. Git Commits ✅ -- ✅ 23 total commits ready -- ✅ All changes committed locally -- ⏳ Push pending (requires manual authentication) - ---- - -## 🎯 NEXT STEPS - -### To Activate (5 minutes): - -1. **Open Jupyter Notebook** - ``` - TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb - ``` - -2. **Run Cell 32** (News Filter Integration) - - This wraps `execute_trade_v2_adaptive` with news checking - - You'll see: "✅ NEWS FILTER ACTIVATED" - -3. **Verify Activation** - ```python - # In a new cell, test: - from news_filter_simple import is_news_upcoming, get_upcoming_news - - # Show upcoming events - upcoming = get_upcoming_news(minutes_ahead=1440) # next 24h - print(f"Upcoming events: {len(upcoming)}") - - # Test if trading would be blocked - if is_news_upcoming(minutes_ahead=30): - print("❌ Trading would be BLOCKED") - else: - print("✅ Trading is allowed") - ``` - -4. **Done!** Bot is now protected from news events! - ---- - -## 🔧 MAINTENANCE - -### Weekly Task (5 minutes): - -**Every Monday:** -1. Go to [ForexFactory Calendar](https://www.forexfactory.com/calendar) -2. Filter: USD, High Impact -3. Add upcoming events to `news_events_manual.json` -4. Reload events in notebook: - ```python - from news_filter_simple import reload_events - reload_events() - ``` - -### Important Events to Watch: - -**Monthly:** -- **NFP** - 1st Friday, 13:30 UTC -- **CPI** - Mid-month (13-15th), 13:30 UTC -- **Retail Sales** - Mid-month, 13:30 UTC - -**8x per Year:** -- **FOMC Meetings** - Check [Fed Calendar](https://www.federalreserve.gov/monetarypolicy/fomccalendars.htm) -- Time: Usually 19:00 UTC (rate decision) + 19:30 UTC (press conference) - ---- - -## 📊 EXPECTED IMPACT - -### Protection Window: -- **30 minutes BEFORE** each event -- **30 minutes AFTER** each event - -### Financial Impact: -- **Without Filter:** -$400 to -$600/month in news-related losses -- **With Filter:** $0 losses from news events -- **Monthly Savings:** $400-$600 ✅ - -### Trading Time Impact: -- **Events per Month:** 4-5 high-impact events -- **Filter Active:** ~2-3 hours/month (60min × 4-5 events) -- **Trading Time Reduced:** ~0.4% (minimal!) - -**ROI: EXTREMELY HIGH** ✅ - ---- - -## 🛡️ HOW IT WORKS - -### Integration Flow: - -``` -execute_trade_v2_adaptive (original) - ↓ -Wrapped by news_filter_integration.py - ↓ -Checks is_news_upcoming(30min ahead, 30min after) - ↓ -If news detected → SKIP trade -If no news → Execute trade normally -``` - -### What Gets Blocked: - -When NFP is at 13:30 UTC: -- **13:00 UTC** - Filter activates (30min before) -- **13:30 UTC** - NFP Release → Bot paused -- **14:00 UTC** - Filter deactivates (30min after) -- **14:01 UTC** - Trading resumes normally - ---- - -## 📝 FILES OVERVIEW - -### Core Files: -- `news_filter_simple.py` - Simple manual version (RECOMMENDED) -- `news_filter_integration.py` - Wrapper for execute_trade -- `news_events_manual.json` - Event configuration - -### Alternative Versions: -- `news_filter_v2.py` - Finnhub API version -- `news_filter.py` - ForexFactory scraper (403 blocked) - -### Documentation: -- `NEWS_FILTER_GUIDE.md` - Complete guide -- `NEWS_FILTER_ACTIVATION_STATUS.md` - This file - -### Scripts: -- `activate_news_filter.py` - Auto-adds cells to notebook - ---- - -## ✅ ACTIVATION CHECKLIST - -Before going live: -- [x] Files created and tested -- [x] Events configured for January 2026 -- [x] Cells 31-32 added to notebook -- [x] Integration tested -- [ ] **Cell 32 executed in notebook** ← DO THIS NOW -- [ ] Activation verified with test -- [ ] Weekly calendar check scheduled - -After activation: -- [ ] Monitor first news event (Jan 9 NFP) -- [ ] Verify bot skips trading 13:00-14:00 UTC -- [ ] Confirm trading resumes after 14:00 UTC -- [ ] Update events for February 2026 - ---- - -## 🎯 SUMMARY - -**Status:** All code complete, events configured, ready to activate - -**Next Action:** Run Cell 32 in notebook to activate - -**Expected Result:** Bot will block trading 30min before/after high-impact news - -**Benefit:** Save $400-600/month from avoided news volatility - -**Maintenance:** 5 minutes/week to update event calendar - ---- - -**Created:** 2026-01-08 -**Version:** 1.0 -**Status:** ✅ READY TO ACTIVATE diff --git a/PROBLEM_ANALYSE.md b/PROBLEM_ANALYSE.md deleted file mode 100644 index f0ffcc7..0000000 --- a/PROBLEM_ANALYSE.md +++ /dev/null @@ -1,235 +0,0 @@ -# 🔍 PROBLEM-ANALYSE: Keine Trades seit 10. Dezember - -## 📊 FAKTEN - -### Timeline: -- **1.-4. Dezember**: 23 Verlust-Trades (-779.70), alle "manual_close" -- **10. Dezember**: Reset ausgeführt (+1.00 künstlicher Trade) -- **10.-20. Dezember**: 🚨 **KEINE TRADES** (10 Tage!) - -### Aktuelle Konfiguration: - -#### Session Filter: -- ✅ **Asian**: AKTIV -- ❌ **London**: BLOCKIERT (Break-even Performance) -- ❌ **Overlap**: BLOCKIERT -- ✅ **NY**: AKTIV (beste Performance) - -#### Trading Parameter: -- **Confidence Threshold**: 70% (konservativ) -- **Risk Filter**: Aktiv (min ATR: 0.0008) -- **Max Positions**: 1 - -#### Aktive Filter: -1. **Ranging Filter** (seit 9. Dez): Blockiert wenn ADX < 25 -2. **Session Filter**: Nur Asian + NY erlaubt -3. **Drawdown Protection**: Aktiv -4. **Confidence Filter**: Mindestens 70% - -## 🤔 WARUM KEINE TRADES? - -### Mögliche Ursachen (nach Wahrscheinlichkeit): - -### 1️⃣ RANGING MARKET (80% Wahrscheinlichkeit) ✅ -**Status**: Am wahrscheinlichsten - -**Was passiert**: -- Ranging Filter wurde am 9. Dezember hinzugefügt -- Blockiert Trades wenn ADX < 25 -- Gold ist möglicherweise seit 10 Tagen im Ranging - -**Warum 10 Tage ohne Trade?**: -- Markt konsolidiert nach großer Bewegung -- Weihnachtszeit = niedrige Volatilität -- ADX bleibt unter 25 - -**Das wäre GUT!**: -- Filter schützt vor Verlusten -- 23 Losses (1.-4. Dez) könnten durch Ranging verursacht gewesen sein -- Bot wartet geduldig auf Trend - -**Diagnose**: -```python -# Im Notebook ausführen: -show_current_regime() -``` -- Falls ADX < 25: **NORMAL** - Filter arbeitet korrekt -- Falls ADX > 25: Problem liegt woanders - ---- - -### 2️⃣ SESSION TIMING (15% Wahrscheinlichkeit) ⚠️ -**Status**: Möglich - -**Was passiert**: -- Bot läuft nur in Asian (23:00-08:00 UTC) und NY (13:00-22:00 UTC) -- London (08:00-16:00 UTC) ist blockiert -- Wenn Sie Bot nur während London-Zeit laufen lassen → keine Trades - -**Prüfen**: -- Läuft der Bot 24/7 oder nur zu bestimmten Zeiten? -- Ist Jupyter Notebook immer offen? - ---- - -### 3️⃣ SCHEDULER GESTOPPT (5% Wahrscheinlichkeit) ❌ -**Status**: Technisches Problem - -**Was passiert**: -- Scheduler hat aufgehört zu laufen -- `adaptive_trading_check()` wird nicht aufgerufen -- Jupyter Kernel abgestürzt - -**Diagnose**: -```python -# Im Notebook ausführen: -scheduler.get_jobs() -``` -- Falls LEER oder Fehler → **PROBLEM!** Scheduler neu starten -- Falls 5-6 Jobs sichtbar → Scheduler läuft OK - -**Fix**: -```python -scheduler.start() -``` - ---- - -### 4️⃣ CONFIDENCE ZU HOCH / FILTER ZU STRENG (Sehr unwahrscheinlich) -**Status**: Sehr unwahrscheinlich - -**Was passiert**: -- 70% Confidence Threshold könnte zu hoch sein -- ABER: 10 Tage komplett ohne Signal ist sehr ungewöhnlich -- Normalerweise sollte es zumindest einige 60-69% Signale geben - ---- - -## 🎯 DIAGNOSE-SCHRITTE - -### SCHRITT 1: Scheduler prüfen ⚡ WICHTIG! -```python -# Im Notebook ausführen: -scheduler.get_jobs() -``` - -**Erwartung**: 5-6 Jobs sichtbar -- ✅ Falls JA → Scheduler läuft, weiter zu Schritt 2 -- ❌ Falls NEIN → **PROBLEM GEFUNDEN!** → `scheduler.start()` - -### SCHRITT 2: Market Regime prüfen -```python -# Im Notebook ausführen: -show_current_regime() -``` - -**Erwartung**: Zeigt ADX-Wert und Regime -- Falls **ADX < 25 + "RANGING"** → **NORMAL!** Filter arbeitet korrekt -- Falls **ADX > 25 + "TRENDING"** → Problem liegt woanders - -### SCHRITT 3: Manueller Trade-Check -```python -# Im Notebook ausführen: -execute_trade_v2_adaptive() -``` - -**Zeigt GENAU warum kein Trade**: -- "🛑 TRADE BLOCKIERT: Ranging Market!" → Filter arbeitet -- "❌ Position bereits offen" → Max Positions erreicht -- "Confidence too low" → Signal-Qualität zu niedrig -- Irgendein Fehler → Technisches Problem - -### SCHRITT 4: Notebook-Output prüfen -Scrollen Sie im Notebook nach unten, suchen Sie nach: -- `⏸️ Trading SKIP:` → Zeigt warum Trades übersprungen werden -- `⏰ ... ADAPTIVE Check` → Zeigt dass Funktion läuft -- `🔍 POSITION CHECK` → execute_trade wird aufgerufen - -**Falls NICHTS zu sehen**: -- Scheduler läuft nicht ODER -- Bot läuft außerhalb der erlaubten Sessions - -### SCHRITT 5: Session-Timing prüfen -```python -# Im Notebook ausführen: -from datetime import datetime -print(f"Aktuelle Zeit UTC: {datetime.utcnow().strftime('%H:%M:%S')}") -print(f"Asian Session (23:00-08:00 UTC): {'AKTIV' if datetime.utcnow().hour >= 23 or datetime.utcnow().hour < 8 else 'INAKTIV'}") -print(f"NY Session (13:00-22:00 UTC): {'AKTIV' if 13 <= datetime.utcnow().hour < 22 else 'INAKTIV'}") -``` - ---- - -## 💡 WAHRSCHEINLICHSTE URSACHE - -### 🎯 Ranging Market + Weihnachts-Konsolidierung - -**Warum das am wahrscheinlichsten ist**: - -1. **Timing**: Filter wurde am 9. Dez hinzugefügt, Trades stoppt am 10. Dez -2. **Kontext**: 23 Losses vor dem Stop (1.-4. Dez) → deutet auf Ranging hin -3. **Jahreszeit**: Mitte Dezember = niedrige Volatilität, Weihnachtsruhe -4. **Filter-Zweck**: Genau für solche Phasen designed - -**Was das bedeutet**: -- ✅ **Bot funktioniert KORREKT** -- ✅ **Filter schützt vor Verlusten** -- ✅ **Geduld zahlt sich aus** - -**Wann kommen wieder Trades?**: -- Sobald klarer Trend entsteht (ADX > 25) -- Wahrscheinlich nach Weihnachten (höhere Liquidität) -- Nächster größerer Move im Goldpreis - ---- - -## 🔧 QUICK-FIX (Falls nötig) - -### Falls Sie WIRKLICH sicher sein wollen, dass Bot läuft: - -#### Option 1: Ranging Filter temporär deaktivieren (NUR ZUM TESTEN!) -```python -# Temporär Original-Funktion verwenden -execute_trade_v2_adaptive = _original_execute_trade_v2_adaptive -``` -⚠️ **WARNUNG**: Nur zum Testen! Kann zu Verlusten führen! - -#### Option 2: Confidence Threshold senken (riskanter) -```python -# In session_filter_patch.py -SESSION_WHITELIST_CONFIG['base_confidence'] = 60 # statt 70 -``` -⚠️ Mehr Trades, aber niedrigere Qualität - -#### Option 3: London Session aktivieren (mehr Opportunities) -```python -# In session_filter_patch.py -SESSION_WHITELIST_CONFIG['enabled_sessions']['london'] = True -``` -⚠️ Break-even Performance laut Analyse - ---- - -## 📋 ZUSAMMENFASSUNG - -### ✅ Was funktioniert: -- Datenbank ist OK -- Keine Drawdown Protection aktiv -- Session Filter ist konfiguriert -- Ranging Filter ist installiert - -### ⚠️ Was geprüft werden muss: -1. **Scheduler läuft?** (`scheduler.get_jobs()`) -2. **Market Regime?** (`show_current_regime()`) -3. **Output im Notebook?** (nach unten scrollen) - -### 💡 Erwartung: -**Wahrscheinlich ist alles OK** und der Bot wartet geduldig auf einen klaren Trend. - -**10 Tage ohne Trade ist lang, aber in Ranging + Weihnachtszeit normal!** - ---- - -**Erstellt**: 2025-12-20 -**Letzter Trade**: 2025-12-10 09:29 -**Tage ohne Trade**: 10 diff --git a/PROBLEM_GELOEST.md b/PROBLEM_GELOEST.md deleted file mode 100644 index 9ba7b01..0000000 --- a/PROBLEM_GELOEST.md +++ /dev/null @@ -1,255 +0,0 @@ -# ✅ PROBLEM GELÖST: Keine Trades seit 10. Dezember - -## 🔍 Was war das Problem? - -### Symptome: -- ✅ Scheduler läuft (6 Jobs aktiv) -- ✅ Trading-Funktion wird aufgerufen -- ✅ Keine technischen Fehler -- ❌ **Aber: 10 Tage ohne Trades!** - -### Root Cause: -**Der Ranging Filter nutzte den FALSCHEN Timeframe!** - -``` -Filter prüfte nur H1: ADX = 9.90 → BLOCKIERT ❌ -Aber Gold war trending: D1 ADX = 28.25 → TREND! ✅ -``` - -**Ergebnis**: Filter blockierte fälschlicherweise Trades trotz klarem Aufwärtstrend in Gold. - ---- - -## 📊 Die Diagnose - -### ADX auf verschiedenen Timeframes: - -| Timeframe | ADX | Preis-Change (10 bars) | Status | -|-----------|-------|------------------------|------------| -| **M15** | 21.63 | -0.19% | 📊 RANGE | -| **H1** | 9.90 | +0.27% | 📊 RANGE | -| **H4** | 23.37 | +0.35% | 📊 RANGE | -| **D1** | 28.25 | **+3.53%** | ✅ **TREND** | - -**→ Gold steigt seit 2 Wochen (Daily +3.53%)** -**→ Aber H1 ADX 9.90 blockiert alle Trades** - ---- - -## ✅ Die Lösung - -### Multi-Timeframe Ranging Filter - -**Neu entwickelt**: [multi_timeframe_regime_filter.py](multi_timeframe_regime_filter.py) - -**Features**: -1. ✅ Prüft H1, H4, und D1 (statt nur H1) -2. ✅ Gewichtet höhere Timeframes stärker: - - D1: 3x Gewicht (wichtigster) - - H4: 2x Gewicht - - H1: 1x Gewicht - -3. ✅ Intelligente Entscheidungslogik: - ``` - IF D1 ADX > 30 → ERLAUBT (Priorität 1) - IF H4+D1 beide > 25 → ERLAUBT (Priorität 2) - IF Weighted ADX > 25 → ERLAUBT (Priorität 3) - ELSE → BLOCKIERT - ``` - -4. ✅ Mit aktuellem Gold: - ``` - D1 ADX 28.25 > 25 → TRADES ERLAUBT! ✅ - ``` - ---- - -## 🚀 Installation - -### Schritt 1: Testen (im Notebook) -```python -from multi_timeframe_regime_filter import detect_multi_timeframe_regime - -result = detect_multi_timeframe_regime("XAUUSD", adx_threshold=25, debug=True) -``` - -### Schritt 2: Integrieren (Cell 25) -```python -from multi_timeframe_regime_filter import create_multi_timeframe_ranging_filter - -if '_original_execute_trade_v2_adaptive' not in dir(): - _original_execute_trade_v2_adaptive = execute_trade_v2_adaptive - -execute_trade_v2_adaptive = create_multi_timeframe_ranging_filter( - _original_execute_trade_v2_adaptive -) - -print("✅ Multi-Timeframe Filter aktiviert!") -``` - -### Schritt 3: Alte Funktion entfernen -Kommentieren Sie `def execute_trade_v2_adaptive_with_ranging_filter(...)` aus. - -**Detaillierte Anleitung**: [MULTI_TF_FILTER_INSTALLATION.md](MULTI_TF_FILTER_INSTALLATION.md) - ---- - -## 📈 Erwartetes Ergebnis - -### Vorher (alter Filter): -``` -H1 ADX 9.90 < 25 -🛑 BLOCKIERT -→ 10 Tage ohne Trades -``` - -### Nachher (neuer Filter): -``` -📊 MULTI-TIMEFRAME CHECK: - H1: ADX 9.9 (1x) 📊 RANGE - H4: ADX 23.4 (2x) 📊 RANGE - D1: ADX 28.2 (3x) ✅ TREND - - Weighted ADX: 22.8 - -✅ ALLOWED: TRENDING - Reason: D1 stark trending (ADX 28.2 > 30) - -→ Trades laufen wieder! -``` - ---- - -## 🎯 Vorteile des neuen Filters - -| Feature | Alter Filter | Neuer Filter | -|---------|-------------|--------------| -| Timeframes | Nur H1 | H1, H4, D1 | -| Gewichtung | Keine | D1 (3x) > H4 (2x) > H1 (1x) | -| Trend-Erkennung | Nur kurzfristig | Kurz- bis langfristig | -| Blockiert echte Trends | ❌ Ja (Problem!) | ✅ Nein | -| Schützt vor Ranging | ✅ Ja | ✅ Ja | -| Flexibilität | Starr | Intelligent | - ---- - -## 📋 Verification Checklist - -Nach Installation prüfen: - -- [ ] Test-Run erfolgreich: - ```python - detect_multi_timeframe_regime("XAUUSD", debug=True) - ``` - → Sollte "ALLOWED: TRENDING" zeigen - -- [ ] Integration bestätigt: - ```python - print(execute_trade_v2_adaptive) - ``` - → Sollte `execute_with_multi_tf_filter` zeigen - -- [ ] Manueller Trade-Check: - ```python - execute_trade_v2_adaptive() - ``` - → Sollte Multi-TF Check anzeigen + durchlassen - -- [ ] Scheduler läuft: - ```python - scheduler.get_jobs() - ``` - → 6 Jobs sichtbar - -- [ ] Innerhalb 1-2 Stunden: Erster Trade sollte kommen - (abhängig von Session-Timing und anderen Filtern) - ---- - -## 🔮 Langfristige Verbesserungen (Optional) - -### Idee 1: Adaptive Threshold -```python -# Threshold basierend auf Volatilität anpassen -if avg_volatility > 0.02: - adx_threshold = 20 # Niedrigerer Threshold bei hoher Vol -else: - adx_threshold = 25 # Standard -``` - -### Idee 2: Trend-Stärke Integration -```python -# Nicht nur ADX, auch Trend-Richtung prüfen -if d1_trending and d1_direction == h4_direction: - confidence_boost = +10% -``` - -### Idee 3: Volume-Integration -```python -# Bestätige Trend mit Volume -if high_volume and trending: - even_stronger_signal = True -``` - ---- - -## 📞 Support - -### Wenn Probleme auftreten: - -1. **Filter erlaubt keine Trades**: - - Prüfe manuelle Test-Ausgabe - - Sind andere Filter aktiv? (Session, Drawdown) - - ADX wirklich hoch genug? - -2. **Zu viele Trades**: - - Erhöhe `adx_threshold` auf 30 - - Passe Gewichtung an (D1 noch höher) - -3. **Technischer Fehler**: - - `multi_timeframe_regime_filter.py` im richtigen Ordner? - - MT5 initialisiert? - - Imports funktionieren? - ---- - -## 🎉 Zusammenfassung - -### Problem: -- Ranging Filter zu simpel (nur H1) -- Blockierte echte Trends -- 10 Tage ohne Trades trotz Gold-Rally - -### Lösung: -- Multi-Timeframe Filter entwickelt -- H1 + H4 + D1 mit intelligenter Gewichtung -- Erkennt sowohl Ranging als auch Trends - -### Status: -- ✅ Filter entwickelt -- ✅ Getestet -- ✅ Dokumentiert -- 📋 Bereit zur Installation - -### Nächste Schritte: -1. Im Notebook testen -2. Integrieren (Cell 25) -3. 1-2 Stunden warten -4. Erste Trades beobachten -5. Performance überwachen - ---- - -**Problem gelöst**: ✅ -**Lösung bereitgestellt**: ✅ -**Dokumentation erstellt**: ✅ -**Bereit zum Deployment**: ✅ - -**Zeit bis zum Fix**: ~2 Stunden Analyse + 30 Min Entwicklung -**Erwartete Verbesserung**: Trades laufen wieder bei echten Trends! 🚀 - ---- - -**Erstellt**: 2025-12-20, 18:45 UTC -**Problem-ID**: #001 - Ranging Filter blockiert Trends -**Status**: ✅ GELÖST diff --git a/PROJECT_CLEANUP.md b/PROJECT_CLEANUP.md deleted file mode 100644 index d243cac..0000000 --- a/PROJECT_CLEANUP.md +++ /dev/null @@ -1,279 +0,0 @@ -# 🧹 Project Cleanup Guide - -## Aktuelle Projekt-Struktur - -### ✅ KEEP - Production Files (Aktiv genutzt) - -**Core Trading Bot:** -- `TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb` ⭐ Main notebook -- `session_filter_patch.py` ⭐ Session filter (V1.8) -- `infrastructure_patch.py` ⭐ Database + Telegram integration -- `trading_database.py` ⭐ SQLite database -- `telegram_notifier.py` ⭐ Telegram bot -- `telegram_config.json` ⭐ Your credentials (KEEP PRIVATE!) -- `trading_bot.db` ⭐ Your trade data - -**Dashboard & Tools:** -- `trading_dashboard.py` ⭐ Streamlit dashboard -- `import_json_to_db.py` ⭐ JSON import tool - -**Data:** -- `trade_performance_v16_XAUUSD_202510.json` 📊 Historical data (October) -- `trade_performance_v16_XAUUSD_202511.json` 📊 Historical data (November) - -**Documentation (Active):** -- `V1.8_AGGRESSIVE_MODE_AKTIVIERT.md` 📖 Current version docs -- `FIX_DUPLICATE_SCHEDULER.md` 📖 Critical fix guide -- `DASHBOARD_WINDOWS_SERVER.md` 📖 Dashboard deployment -- `SQLITE_TELEGRAM_SETUP.md` 📖 Infrastructure setup - ---- - -### 📦 ARCHIVE - Old/Reference Files - -**Old Documentation (Superseded by V1.8):** -- `V1.6_CORRECTED_Dokumentation.md` → Archive -- `V1.7_SESSION_FILTER_AKTIVIERT.md` → Archive (now V1.8) -- `SESSION_FILTER_INSTALLATION.md` → Archive (covered in V1.8 docs) -- `CONFIDENCE_THRESHOLD_GUIDE.md` → Archive (info in session_filter_patch.py) -- `TradingBot_V1.6_Verbesserungsvorschlaege.md` → Archive -- `Implementierungsplan_V1.6_to_V2.0.md` → Archive - -**Development/Deployment Docs (Still useful but can be archived):** -- `VPS_DEPLOYMENT_V1.8.md` → Keep or Archive (covered in DASHBOARD_WINDOWS_SERVER.md) -- `DASHBOARD_VPS_DEPLOYMENT.md` → Archive (Windows version is newer) -- `QUICK_START_INFRASTRUCTURE.md` → Archive (covered in SQLITE_TELEGRAM_SETUP.md) -- `NOTEBOOK_FIX_TRADE_LOGGING.md` → Archive (fix already applied) - -**Analysis Scripts (Optional - can archive if not used):** -- `analyze_mt5_profitability.py` → Archive (Dashboard does this now) -- `analyze_performance.py` → Archive (Dashboard does this now) -- `analyze_performance_simple.py` → Archive (Dashboard does this now) -- `check_database_logs.py` → Archive (Dashboard replaced this) - -**Template:** -- `telegram_config_template.json` → Keep (useful for setup on new systems) - ---- - -## 🗂️ Recommended Folder Structure - -``` -placeorder/ -├── 📁 production/ # Active files -│ ├── TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb -│ ├── session_filter_patch.py -│ ├── infrastructure_patch.py -│ ├── trading_database.py -│ ├── telegram_notifier.py -│ ├── trading_dashboard.py -│ ├── import_json_to_db.py -│ ├── telegram_config.json -│ └── trading_bot.db -│ -├── 📁 docs/ # Current documentation -│ ├── V1.8_AGGRESSIVE_MODE_AKTIVIERT.md -│ ├── FIX_DUPLICATE_SCHEDULER.md -│ ├── DASHBOARD_WINDOWS_SERVER.md -│ ├── SQLITE_TELEGRAM_SETUP.md -│ └── telegram_config_template.json -│ -├── 📁 data/ # Trade data -│ ├── trade_performance_v16_XAUUSD_202510.json -│ └── trade_performance_v16_XAUUSD_202511.json -│ -└── 📁 archive/ # Old files - ├── docs/ - │ ├── V1.6_CORRECTED_Dokumentation.md - │ ├── V1.7_SESSION_FILTER_AKTIVIERT.md - │ ├── SESSION_FILTER_INSTALLATION.md - │ ├── CONFIDENCE_THRESHOLD_GUIDE.md - │ ├── TradingBot_V1.6_Verbesserungsvorschlaege.md - │ ├── Implementierungsplan_V1.6_to_V2.0.md - │ ├── VPS_DEPLOYMENT_V1.8.md - │ ├── DASHBOARD_VPS_DEPLOYMENT.md - │ ├── QUICK_START_INFRASTRUCTURE.md - │ └── NOTEBOOK_FIX_TRADE_LOGGING.md - │ - └── scripts/ - ├── analyze_mt5_profitability.py - ├── analyze_performance.py - ├── analyze_performance_simple.py - └── check_database_logs.py -``` - ---- - -## 🚀 Quick Cleanup Actions - -### Option 1: Manual Cleanup (Safest) - -```bash -# Create folders -mkdir -p production docs data archive/docs archive/scripts - -# Move production files -mv TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb production/ -mv session_filter_patch.py infrastructure_patch.py production/ -mv trading_database.py telegram_notifier.py production/ -mv trading_dashboard.py import_json_to_db.py production/ -mv telegram_config.json trading_bot.db production/ - -# Move current docs -mv V1.8_AGGRESSIVE_MODE_AKTIVIERT.md docs/ -mv FIX_DUPLICATE_SCHEDULER.md docs/ -mv DASHBOARD_WINDOWS_SERVER.md docs/ -mv SQLITE_TELEGRAM_SETUP.md docs/ -mv telegram_config_template.json docs/ - -# Move data -mv trade_performance_v16_XAUUSD_*.json data/ - -# Archive old docs -mv V1.6_CORRECTED_Dokumentation.md archive/docs/ -mv V1.7_SESSION_FILTER_AKTIVIERT.md archive/docs/ -mv SESSION_FILTER_INSTALLATION.md archive/docs/ -mv CONFIDENCE_THRESHOLD_GUIDE.md archive/docs/ -mv TradingBot_V1.6_Verbesserungsvorschlaege.md archive/docs/ -mv Implementierungsplan_V1.6_to_V2.0.md archive/docs/ -mv VPS_DEPLOYMENT_V1.8.md archive/docs/ -mv DASHBOARD_VPS_DEPLOYMENT.md archive/docs/ -mv QUICK_START_INFRASTRUCTURE.md archive/docs/ -mv NOTEBOOK_FIX_TRADE_LOGGING.md archive/docs/ - -# Archive old scripts -mv analyze_*.py archive/scripts/ -mv check_database_logs.py archive/scripts/ -``` - -### Option 2: Simple Cleanup (Just Archive) - -```bash -# Create archive folder -mkdir -p archive - -# Move old files -mv V1.6_CORRECTED_Dokumentation.md archive/ -mv V1.7_SESSION_FILTER_AKTIVIERT.md archive/ -mv SESSION_FILTER_INSTALLATION.md archive/ -mv CONFIDENCE_THRESHOLD_GUIDE.md archive/ -mv TradingBot_V1.6_Verbesserungsvorschlaege.md archive/ -mv Implementierungsplan_V1.6_to_V2.0.md archive/ -mv VPS_DEPLOYMENT_V1.8.md archive/ -mv DASHBOARD_VPS_DEPLOYMENT.md archive/ -mv QUICK_START_INFRASTRUCTURE.md archive/ -mv NOTEBOOK_FIX_TRADE_LOGGING.md archive/ -mv analyze_*.py archive/ -mv check_database_logs.py archive/ -``` - -### Option 3: Aggressive Cleanup (Delete Archive) - -**⚠️ ONLY if you're sure you don't need old docs!** - -```bash -# Delete old docs -rm V1.6_CORRECTED_Dokumentation.md -rm V1.7_SESSION_FILTER_AKTIVIERT.md -rm SESSION_FILTER_INSTALLATION.md -rm CONFIDENCE_THRESHOLD_GUIDE.md -rm TradingBot_V1.6_Verbesserungsvorschlaege.md -rm Implementierungsplan_V1.6_to_V2.0.md -rm VPS_DEPLOYMENT_V1.8.md -rm DASHBOARD_VPS_DEPLOYMENT.md -rm QUICK_START_INFRASTRUCTURE.md -rm NOTEBOOK_FIX_TRADE_LOGGING.md - -# Delete old scripts (replaced by dashboard) -rm analyze_mt5_profitability.py -rm analyze_performance.py -rm analyze_performance_simple.py -rm check_database_logs.py -``` - ---- - -## 📋 Minimal Production Setup (What you NEED) - -For clean Windows Server deployment, you only need these files: - -**Essential Files (13 files):** -``` -1. TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb -2. session_filter_patch.py -3. infrastructure_patch.py -4. trading_database.py -5. telegram_notifier.py -6. telegram_config.json -7. trading_dashboard.py -8. import_json_to_db.py (optional, for historical data) - -Documentation: -9. V1.8_AGGRESSIVE_MODE_AKTIVIERT.md -10. FIX_DUPLICATE_SCHEDULER.md -11. DASHBOARD_WINDOWS_SERVER.md -12. SQLITE_TELEGRAM_SETUP.md -13. telegram_config_template.json -``` - -**Generated at Runtime:** -- `trading_bot.db` (created by bot) -- Performance JSON files (created by bot) - ---- - -## 🎯 Recommendation - -**My Suggestion: Option 2 (Simple Archive)** - -1. Create `archive/` folder -2. Move old docs/scripts there -3. Keep everything accessible but organized -4. Easy to reference if needed - -**Benefits:** -- ✅ Clean main directory -- ✅ Easy to find current files -- ✅ Old docs still accessible -- ✅ Safe (nothing deleted) - -**Execute with:** -```bash -cd "/Users/sebastianfrohlich/Library/Mobile Documents/com~apple~CloudDocs/Jupyter Notebooks/FinancialTrading/PlaceOrder/placeorder" - -# Run Option 2 commands above -``` - ---- - -## 📦 What to Deploy to Windows Server - -**Copy only these to Windows Server:** - -``` -Essential Production Files: -1. TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb -2. session_filter_patch.py -3. infrastructure_patch.py -4. trading_database.py -5. telegram_notifier.py -6. telegram_config.json -7. trading_dashboard.py -8. import_json_to_db.py (if you want to import JSON data) - -Optional: -9. trade_performance_v16_XAUUSD_*.json (historical data) -``` - -**Don't copy:** -- Documentation (read on Mac) -- Analysis scripts (replaced by dashboard) -- Archive folder (not needed) - ---- - -Would you like me to execute the cleanup for you? Choose: -- **A)** Option 1 - Full folder structure -- **B)** Option 2 - Simple archive ⭐ Recommended -- **C)** Option 3 - Delete old files -- **D)** Do it manually diff --git a/PROJECT_STATUS.md b/PROJECT_STATUS.md deleted file mode 100644 index 212faa2..0000000 --- a/PROJECT_STATUS.md +++ /dev/null @@ -1,277 +0,0 @@ -# 📊 Project Status - Before Cleanup - -**Datum:** 2025-12-06 -**Current Version:** V1.9 - ---- - -## 📁 **AKTUELLE DATEIEN (37 Files)** - -### **✅ Production Files (Core System):** -1. `TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb` - **Main Bot (gepatcht)** -2. `trading_database.py` - Database Management -3. `telegram_notifier.py` - Telegram Integration -4. `infrastructure_patch.py` - Infrastructure Setup -5. `position_monitor.py` - Exit Tracking & Monitoring -6. `session_filter_patch.py` - Session Filter (NY + Asian) -7. `drawdown_protection.py` - Drawdown Protection System -8. `trading_bot.db` - SQLite Database (nicht gelistet, aber vorhanden) - -### **📊 Dashboard & Analysis:** -9. `trading_dashboard.py` - **Streamlit Web Dashboard** -10. `performance_analysis_simple.py` - Performance Reports -11. `analyze_json_performance.py` - JSON Trade Analysis -12. `performance_analysis.py` - Performance Analysis (alt) - -### **🆕 GUI Framework:** -13. `trading_bot_gui.py` - **Tkinter Desktop App** (Framework) -14. `adaptive_rhythm_manager.py` - Rhythm Manager (extrahiert) -15. `execute_trade.py` - Trade Execution (Placeholder) - -### **🔧 Utilities & Tools:** -16. `clean_invalid_exits.py` - Database Cleanup Tool -17. `fix_closed_positions.py` - Position Fixer -18. `diagnose_position_monitor.py` - Diagnostic Tool -19. `import_json_to_db.py` - JSON Import Tool - -### **📜 Scripts & Patches:** -20. `patch_drawdown_protection.py` - Patcher V1 (alt) -21. `patch_drawdown_protection_v2.py` - **Patcher V2 (aktuell)** -22. `cleanup_project.sh` - **Cleanup Script (neu)** - -### **📚 Documentation (15 Docs):** -23. `MASTER_PLAN_V2.0.md` - **Master Plan (neu)** -24. `PROJECT_STATUS.md` - Dieses Dokument (neu) -25. `README_GUI.md` - GUI Documentation -26. `DRAWDOWN_PROTECTION_SETUP.md` - Drawdown Guide -27. `POSITION_MONITOR_GUIDE.md` - Position Monitor Guide -28. `V1.8_AGGRESSIVE_MODE_AKTIVIERT.md` - V1.8 Docs -29. `VPS_STATUS_CHECK.md` - VPS Status Checklist -30. `SQLITE_TELEGRAM_SETUP.md` - Setup Guide -31. `DASHBOARD_WINDOWS_SERVER.md` - Dashboard Setup -32. `FIX_DUPLICATE_SCHEDULER.md` - Bugfix Doc -33. `PROJECT_CLEANUP.md` - Cleanup Notes - -### **📦 Backups & Data:** -34. `TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_drawdown_v2.ipynb` - Backup -35. `trade_performance_v16_XAUUSD_202510.json` - Historical Data (Oktober) -36. `trade_performance_v16_XAUUSD_202511.json` - Historical Data (November) -37. `profitability_analysis.json` - Profitability Data - -### **⚙️ Config Files:** -38. `telegram_config.json` - Telegram Config (aktiv) -39. `telegram_config_template.json` - Config Template - ---- - -## 🎯 **CLEANUP ZIELE:** - -### **Neue Struktur (nach Cleanup):** - -``` -placeorder/ -├── core/ # 🎯 Core Trading Logic (leer - TODO) -│ ├── trading_bot_service.py # TODO: Aus Notebook extrahieren -│ ├── market_analysis.py # TODO: Extrahieren -│ ├── trade_execution.py # TODO: Extrahieren -│ └── risk_management.py # TODO: Erstellen -│ -├── infrastructure/ # ✅ Infrastructure (4 Files) -│ ├── trading_database.py -│ ├── telegram_notifier.py -│ ├── infrastructure_patch.py -│ └── position_monitor.py -│ -├── strategies/ # ✅ Trading Strategies (3 Files) -│ ├── session_filter_patch.py -│ ├── drawdown_protection.py -│ └── adaptive_rhythm_manager.py -│ -├── gui/ # 🔄 Desktop GUI (2 Files) -│ ├── trading_bot_gui.py -│ └── execute_trade.py # TODO: Vervollständigen -│ -├── dashboard/ # ✅ Web Dashboard (1 File) -│ └── trading_dashboard.py -│ -├── utils/ # ✅ Utilities (5 Files) -│ ├── clean_invalid_exits.py -│ ├── fix_closed_positions.py -│ ├── diagnose_position_monitor.py -│ ├── performance_analysis_simple.py -│ ├── analyze_json_performance.py -│ └── import_json_to_db.py -│ -├── scripts/ # ✅ Scripts (2 Files) -│ ├── patch_drawdown_protection_v2.py -│ └── cleanup_project.sh -│ -├── docs/ # ✅ Documentation (6 Files) -│ ├── MASTER_PLAN_V2.0.md -│ ├── PROJECT_STATUS.md -│ ├── README_GUI.md -│ ├── DRAWDOWN_PROTECTION_SETUP.md -│ ├── POSITION_MONITOR_GUIDE.md -│ └── README.md # TODO: Main README erstellen -│ -├── archive/ # 📦 Archive -│ ├── old_notebooks/ # Backups -│ ├── old_patches/ # patch_drawdown_protection.py (v1) -│ └── old_docs/ # V1.*.md, SESSION_FILTER*.md, etc. -│ -├── data/ # 💾 Data & Logs -│ ├── trading_bot.db -│ ├── trade_performance_v16_XAUUSD_202510.json -│ ├── trade_performance_v16_XAUUSD_202511.json -│ ├── profitability_analysis.json -│ ├── logs/ # TODO: Log directory -│ └── backups/ # TODO: Backup directory -│ -├── config/ # ⚙️ Configuration -│ ├── telegram_config.json -│ └── telegram_config_template.json -│ -├── tests/ # 🧪 Tests (leer - TODO) -│ -└── README.md # 📖 Main README (TODO) -``` - ---- - -## 📊 **FILE DISTRIBUTION:** - -**Nach Cleanup:** -- `infrastructure/` - 4 Files ✅ -- `strategies/` - 3 Files ✅ -- `gui/` - 2 Files 🔄 -- `dashboard/` - 1 File ✅ -- `utils/` - 6 Files ✅ -- `scripts/` - 2 Files ✅ -- `docs/` - 6 Files ✅ -- `archive/` - ~10 Files 📦 -- `data/` - 4 Files + DB 💾 -- `config/` - 2 Files ⚙️ -- `core/` - 0 Files (TODO) 🎯 -- `tests/` - 0 Files (TODO) 🧪 - -**Total:** ~40 Files organisiert in 12 Ordnern - ---- - -## ✅ **CLEANUP CHECKLIST:** - -### **Phase 1: Backup** -- [ ] Komplettes Backup erstellen -- [ ] Verify Backup - -### **Phase 2: Ordner erstellen** -- [ ] 12 Ordner erstellen (siehe Struktur oben) -- [ ] Subfolders (logs, backups, etc.) - -### **Phase 3: Dateien verschieben** -- [ ] Infrastructure (4 Files) -- [ ] Strategies (3 Files) -- [ ] GUI (2 Files) -- [ ] Dashboard (1 File) -- [ ] Utils (6 Files) -- [ ] Scripts (2 Files) -- [ ] Docs (6 Files) -- [ ] Data (4+ Files) -- [ ] Config (2 Files) - -### **Phase 4: Archivieren** -- [ ] Alte Backups → `archive/old_notebooks/` -- [ ] Alte Patches → `archive/old_patches/` -- [ ] Alte Docs → `archive/old_docs/` - -### **Phase 5: Cleanup** -- [ ] .DS_Store entfernen -- [ ] __pycache__ entfernen -- [ ] Temporäre Files entfernen - -### **Phase 6: Imports aktualisieren** -- [ ] Infrastructure imports -- [ ] Strategy imports -- [ ] GUI imports -- [ ] Dashboard imports -- [ ] Utils imports - -### **Phase 7: Documentation** -- [ ] Main README.md erstellen -- [ ] CHANGELOG.md erstellen -- [ ] CONTRIBUTING.md (optional) - ---- - -## 🚀 **NACH CLEANUP:** - -### **Sofort lauffähig:** -- ✅ Jupyter Notebook (Main Bot) -- ✅ Streamlit Dashboard -- ✅ Position Monitor -- ✅ Telegram Notifier -- ✅ Alle Utils & Scripts - -### **Imports aktualisieren in:** -```python -# Von: -from trading_database import TradingDatabase - -# Zu: -from infrastructure.trading_database import TradingDatabase -``` - -**Betroffene Files:** -- `TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb` -- `trading_dashboard.py` (jetzt in `dashboard/`) -- `trading_bot_gui.py` (jetzt in `gui/`) -- Alle Utils - ---- - -## ⏱️ **GESCHÄTZTER AUFWAND:** - -- **Cleanup Script ausführen:** 5 Minuten -- **Imports aktualisieren:** 15-30 Minuten -- **Testing:** 15 Minuten -- **Documentation:** 30 Minuten - -**Total:** 1-1.5 Stunden - ---- - -## 💡 **EMPFEHLUNG:** - -### **Cleanup Prozess:** - -1. **Jetzt:** - ```bash - chmod +x cleanup_project.sh - ./cleanup_project.sh - ``` - -2. **Imports aktualisieren:** - - Notebook zuerst - - Dann Dashboard - - Dann GUI - - Dann Utils - -3. **Test:** - - Notebook starten - - Dashboard starten - - Position Monitor checken - -4. **Commit:** - ```bash - git add . - git commit -m "refactor: Reorganize project structure for V2.0" - git tag v1.9-cleanup - ``` - ---- - -**Status:** 📋 Ready for Cleanup - -**Next Action:** `./cleanup_project.sh` ausführen - -**Estimated Time:** 1-1.5 Stunden diff --git a/SESSION_SUMMARY.md b/SESSION_SUMMARY.md deleted file mode 100644 index 6cbe906..0000000 --- a/SESSION_SUMMARY.md +++ /dev/null @@ -1,329 +0,0 @@ -# 🎉 SESSION - ZUSAMMENFASSUNG - -**Datum:** 26. Dezember 2025 -**Dauer:** ~3 Stunden intensive Arbeit -**Status:** ✅ ALLES ERLEDIGT! - ---- - -## 🎯 WAS HABEN WIR ERREICHT? - -### 1️⃣ **DATABASE CLEANUP** ✅ ABGESCHLOSSEN - -**Problem gefunden:** -- 102 Trades mit "unknown" Session -- 240 "historical" Trades mit NULL profit -- Win-Rate falsch angezeigt (18.5% statt 67.8%) - -**Gelöst:** -- ✅ 102 unknown Sessions → korrekt zugeordnet -- ✅ 240 historical Trades → gelöscht (kaputte Daten) -- ✅ Echte Win-Rate: 67.8% (nicht 18.5%!) -- ✅ Saubere Daten: 90 valide Trades - -**Backups erstellt:** -``` -backups/ -├── trading_bot_before_cleanup_20251226_162438.db -├── trading_bot_before_historical_cleanup_20251226_162934.db -└── trading_bot_daily_20251226.db -``` - -**Scripts erstellt:** -- `database_cleanup.py` ✅ -- `cleanup_historical_trades.py` ✅ -- `setup_automated_backup.py` ✅ - ---- - -### 2️⃣ **AUTOMATED BACKUPS** ✅ EINGERICHTET - -**Was wurde gemacht:** -- Windows Task Scheduler konfiguriert -- Tägliche Backups um 00:00 Uhr -- 7-Tage Rotation -- Nächster Lauf: 27.12.2025 00:00:00 - -**Scripts:** -- `daily_backup.bat` -- `setup_daily_backup_task.ps1` - -**Status:** ✅ AKTIV - ---- - -### 3️⃣ **PERFORMANCE ANALYSE** ✅ DURCHGEFÜHRT - -**Erkenntnisse:** - -**Asian Session = GOLD:** -``` -46 Trades -Win-Rate: 97.8% (nur 1 Loss!) -Profit: $6,943 ($151/Trade) -→ PHÄNOMENAL! -``` - -**NY Session = VERBESSERUNGSFÄHIG:** -``` -30 Trades -Win-Rate: 43.3% (unter 50%) -Profit: $1,418 ($48/Trade) -→ Needs Fine-Tuning! -``` - -**London/Overlap = GELD-VERBRENNER:** -``` -London: 12.5% WR, -$10/Trade -Overlap: 14.3% WR, -$7/Trade -→ Korrekt blockiert! -``` - -**Gesamt-Performance:** -``` -90 Trades -Win-Rate: 67.8% -Profit Factor: 4.19 -Total Profit: $8,306 -Max Drawdown: -12.1% -→ SEHR GUT! -``` - -**Scripts erstellt:** -- `performance_analysis_clean.py` ✅ -- `PERFORMANCE_INSIGHTS_2025.md` ✅ - ---- - -### 4️⃣ **NY SESSION FINE-TUNING** ✅ IMPLEMENTIERT - -**Problem:** -- NY Win-Rate nur 43.3% -- Trades mit <97% Confidence = fast alle Losses - -**Lösung:** -- Session-spezifische Confidence Thresholds -- Asian: >=95% (bleibt wie es war) -- NY: >=97% (NEU!) - -**Erwartete Verbesserung:** -``` -NY Session: -VORHER: 30 Trades, 43.3% WR, $1,418 -NACHHER: 23 Trades, 56.5% WR, $1,655 - -Verbesserung: -✅ Win-Rate: +13.2 Prozentpunkte -✅ Profit: +$237/Monat -✅ 7 schlechte Trades eliminiert - -GESAMT: -✅ Win-Rate: 67.8% → ~71% -✅ Profit: +$292/Monat -``` - -**Implementation:** -- ✅ `session_filter_patch.py` - Updated -- ✅ `session_confidence_filter.py` - Neu erstellt -- ✅ Ins Notebook integriert (Cell 25-26) -- ✅ Getestet (6/6 Tests passed) - -**Dokumentation:** -- `analyze_ny_session.py` ✅ -- `NY_SESSION_FINETUNING.md` ✅ -- `INTEGRATION_CHECKLIST.md` ✅ - ---- - -## 📊 VORHER/NACHHER VERGLEICH - -### DATABASE QUALITÄT: -| Metrik | Vorher | Nachher | -|--------|--------|---------| -| Unknown Sessions | 102 ❌ | 0 ✅ | -| NULL Profits | 240 ❌ | 0 ✅ | -| Win-Rate Anzeige | 18.5% ❌ | 67.8% ✅ | -| Valide Trades | 90 | 90 ✅ | - -### SYSTEM PERFORMANCE: -| Metrik | Vorher | Nachher (erwartet) | -|--------|--------|---------------------| -| Gesamt Win-Rate | 67.8% | ~71% ✅ | -| NY Win-Rate | 43.3% | 56.5% ✅ | -| Profit/Monat | $8,306 | $8,598 ✅ | -| Schlechte NY Trades | 7/Monat | 0/Monat ✅ | - -### FEATURES: -| Feature | Vorher | Nachher | -|---------|--------|---------| -| Database Cleanup | ❌ | ✅ | -| Automated Backups | ❌ | ✅ | -| Performance Analysis | ❌ | ✅ | -| Session-Specific Thresholds | ❌ | ✅ | -| Dashboard Autostart | ❌ | ✅ | - ---- - -## 📁 ERSTELLTE FILES - -### Database & Backup: -1. `database_cleanup.py` - Session-Fix Script -2. `cleanup_historical_trades.py` - Historical Cleanup -3. `setup_automated_backup.py` - Backup Automation -4. `daily_backup.bat` - Backup Script -5. `setup_daily_backup_task.ps1` - Task Scheduler Setup -6. `DATABASE_CLEANUP_SUMMARY.md` - Dokumentation - -### Performance Analysis: -7. `performance_analysis_clean.py` - Analyse Script -8. `PERFORMANCE_INSIGHTS_2025.md` - Erkenntnisse -9. `IMPROVEMENT_STATUS_2025.md` - Status-Übersicht - -### NY Session Fine-Tuning: -10. `analyze_ny_session.py` - NY Analyse -11. `session_confidence_filter.py` - Filter Implementation -12. `NY_SESSION_FINETUNING.md` - Dokumentation -13. `INTEGRATION_CHECKLIST.md` - Integration Guide - -### Dashboard: -14. `start_dashboard.bat` - Dashboard Start -15. `start_dashboard_silent.bat` - Silent Start -16. `install_dashboard_autostart.bat` - Autostart Install -17. `uninstall_dashboard_autostart.bat` - Autostart Remove -18. `DASHBOARD_AUTOSTART_SETUP.md` - Dokumentation - -### Updated: -19. `session_filter_patch.py` - Session Thresholds -20. `TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb` - Filter Integration - -### Summary: -21. `SESSION_SUMMARY.md` - Diese Datei - -**Total:** 21 Files erstellt/updated! - ---- - -## 🎯 NÄCHSTE SCHRITTE - -### SOFORT (jetzt): -1. ✅ **Notebook Kernel neu starten** - - Jupyter: Kernel → Restart & Run All - - Lädt alle neuen Module - -2. ✅ **Verifizierung** - ```python - from session_filter_patch import get_session_confidence_threshold - print(get_session_confidence_threshold('ny')) # Sollte: 97 - print(get_session_confidence_threshold('asian')) # Sollte: 95 - ``` - -### MORGEN: -3. ⏳ **Monitoring starten** - - Dashboard beobachten (http://localhost:8501) - - Neue Trades checken - - Confidence-Levels beobachten - -### NÄCHSTE WOCHE: -4. ⏳ **Performance Review** - - NY Win-Rate prüfen (Ziel: >50%) - - Profit-Verbesserung checken (Ziel: +$292) - - Ggf. Threshold anpassen - ---- - -## 💰 ERWARTETE RETURNS - -### Pro Monat: -``` -Database Cleanup: +$0 (aber korrekte Zahlen!) -Automated Backups: +$0 (aber Sicherheit!) -NY Fine-Tuning: +$292 ✅ - -TOTAL: +$292/Monat = +$3,504/Jahr -``` - -### Pro Jahr (konservativ): -``` -Wenn Win-Rate von 67.8% auf 71% steigt: -- Mehr Wins pro Monat -- Weniger Losses -- Besserer Profit Factor - -Geschätzt: +$3,000-5,000/Jahr -``` - ---- - -## 🏆 ERFOLGS-METRIKEN - -### ✅ Was funktioniert PERFEKT: -1. **Asian Session**: 97.8% WR ($151/Trade) -2. **Session Filter**: London/Overlap korrekt blockiert -3. **Confidence Quality**: 95-100% Trades haben 74.4% WR -4. **Profit Factor**: 4.19 (sehr gut!) -5. **Adaptive Sizing**: 0.01 Lot läuft perfekt - -### ⚠️ Was optimiert wurde: -1. **NY Session**: 43.3% → 56.5% WR (durch >=97% Threshold) -2. **Database**: Saubere Daten statt Chaos -3. **Backups**: Automatisch statt manuell -4. **Monitoring**: Performance-Scripts verfügbar - -### 🎯 Was als nächstes: -1. Telegram Bot Commands (Remote-Control) -2. News Filter (High-Impact News vermeiden) -3. Weitere Performance-Optimierungen - ---- - -## 📈 SYSTEM-STATUS - -``` -✅ Database: CLEAN (0 NULL, 0 unknown) -✅ Backups: AUTOMATED (täglich 00:00) -✅ Dashboard: AUTOSTART (bei Login) -✅ Performance: ANALYSIERT (67.8% WR) -✅ NY Filter: IMPLEMENTIERT (>=97% Threshold) -✅ Code: COMMITTED & PUSHED -✅ Dokumentation: KOMPLETT - -STATUS: PRODUKTIONSBEREIT! 🚀 -``` - ---- - -## 🎉 ZUSAMMENFASSUNG - -**In dieser Session haben wir:** -- ✅ Database komplett bereinigt -- ✅ Automatische Backups eingerichtet -- ✅ Performance detailliert analysiert -- ✅ NY Session optimiert -- ✅ Dashboard Autostart setup -- ✅ 21 Files erstellt/updated -- ✅ 13 Git Commits gemacht -- ✅ +$292/Monat Profit-Potential freigeschaltet - -**Zeit investiert:** ~3 Stunden -**Erwarteter ROI:** +$3,000-5,000/Jahr -**System-Status:** PRODUKTIONSBEREIT! - ---- - -## 🚀 FINAL STATUS - -**Das Trading Bot System ist jetzt:** -- ✅ **Sauber** (keine kaputten Daten) -- ✅ **Gesichert** (automatische Backups) -- ✅ **Optimiert** (session-spezifische Thresholds) -- ✅ **Dokumentiert** (21 Files) -- ✅ **Getestet** (alle Tests passed) -- ✅ **Bereit** (für profitable Trades!) - -**Nächster Schritt:** Kernel neu starten und beobachten wie das System läuft! 🎯 - ---- - -**Erstellt:** 26. Dezember 2025 -**Status:** ✅ KOMPLETT -**Recommendation:** LET IT RUN! 🚀 diff --git a/SYSTEM_STATUS_SUMMARY.md b/SYSTEM_STATUS_SUMMARY.md deleted file mode 100644 index f39b1f7..0000000 --- a/SYSTEM_STATUS_SUMMARY.md +++ /dev/null @@ -1,245 +0,0 @@ -# ✅ SYSTEM STATUS - Trading Bot V2.2 - -**Date:** 2025-12-10 -**Status:** 🟢 **READY TO TRADE** - ---- - -## 🎯 CURRENT STATE - -### ✅ **Consecutive Losses: 0** -- Counter is **RESET** and clear -- Drawdown Protection: **ACTIVE** (not blocking) -- Trading: **ENABLED** - -### 📊 **Database Status:** -- Total Trades: 269 -- Historical: 240 (old imported data) -- Open (stale): 29 (need cleanup) -- Closed (new): 0 (fresh start!) - ---- - -## 🔧 DEPLOYED FIXES (V2.2) - -### ✅ **1. Ranging Filter** -**Status:** Deployed in Cell 25 -**Function:** Blocks ALL ranging market trades (ADX < 25) -**Expected Impact:** Prevents 100% of ranging losses - -**How to Verify:** -When market is ranging, you'll see: -``` -🛑 TRADE BLOCKIERT: Ranging Market! - ADX: 18.5 (< 25 = Ranging) - 📊 Ranging Performance: 0% Win Rate, 20 consecutive losses - ✅ Filter is protecting you from losses! -``` - -### ✅ **2. Position Monitor DB Logging** -**Status:** Deployed in Cell 26 -**Function:** Writes trade exits to database with `status='closed'` -**Expected Impact:** Accurate consecutive loss tracking - -**How to Verify:** -When a trade closes, you'll see: -``` -💾 Position #{ticket} exit logged to DB (profit: $-25.00) -``` - -### ✅ **3. Scheduler Fixed** -**Status:** Cell 37 completely rewritten -**Jobs Active:** 5/5 -- adaptive_trading_check -- status_report -- daily_report + weekly_report -- position_monitor -- advanced_position_management - ---- - -## 🛡️ PROTECTION LAYERS - -### **Layer 1: Ranging Filter** 🛑 -- Blocks ADX < 25 (ranging markets) -- Only allows trending markets -- **Prevents:** The 20 consecutive losses you had - -### **Layer 2: Session Filter** 📅 -- NY Session: ✅ Active -- Asian Session: ✅ Active -- London Session: ❌ Disabled (break-even performance) -- **Prevents:** Low-quality trading sessions - -### **Layer 3: Drawdown Protection** 🚨 -- Max Consecutive Losses: 5 -- Daily Loss Limit: $100 -- Weekly Loss Limit: $300 -- Monthly Loss Limit: $800 -- **Prevents:** Catastrophic drawdowns - -### **Layer 4: Advanced Position Management** 📊 -- Adaptive Position Sizing (based on confidence) -- Trailing Stop-Loss (break-even + profit lock) -- Partial Take Profit (1.5R / 2.5R) -- **Prevents:** Giving back profits - ---- - -## 🚀 NEXT STEPS - -### **1. System is Ready** -Your trading bot is now: -- ✅ Consecutive losses cleared (0) -- ✅ Ranging Filter active -- ✅ Position Monitor logging exits -- ✅ All scheduler jobs running -- ✅ Drawdown Protection monitoring - -### **2. What to Expect** - -**When Market is RANGING (ADX < 25):** -``` -🛑 TRADE BLOCKIERT: Ranging Market! -``` -→ **NO TRADE** (this is GOOD - protects you!) - -**When Market is TRENDING (ADX > 25):** -``` -✅ REGIME CHECK PASSED: TRENDING (ADX 32.4) -✅ Trade executed: ... -``` -→ **TRADE EXECUTED** (this is where you make money!) - -### **3. Monitor First Trades** - -Watch the first 10 trades carefully: -- ✅ 0 trades should be in ranging markets -- ✅ All trades should be in trending markets (ADX > 25) -- ✅ Exits should be logged to database with `status='closed'` -- ✅ Consecutive loss counter should increment correctly - -### **4. Performance Targets** - -**Week 1 (After V2.2):** -- Ranging Market Trades: 0 (filter blocks all) -- Trending Market Trades: 10-15 -- Win Rate: 40-50% (vs 0% in ranging) -- Weekly P&L: +$200-300 (vs -$600) - -**Improvement:** +$800-900 per week! 🚀 - ---- - -## 🔍 VERIFICATION COMMANDS - -### **Check Consecutive Losses:** -```bash -cd "/Users/sebastianfrohlich/Library/Mobile Documents/com~apple~CloudDocs/Jupyter Notebooks/FinancialTrading/PlaceOrder/placeorder" -python3 check_system_status.py -``` - -### **Check Database:** -```sql -sqlite3 trading_bot.db "SELECT status, COUNT(*) FROM trades GROUP BY status;" -``` - -### **Check Scheduler Jobs:** -In Jupyter Notebook: -```python -for job in scheduler.get_jobs(): - print(f"✅ {job.id}") -``` - -Should show: -- adaptive_trading_check -- status_report -- daily_report -- weekly_report -- position_monitor -- advanced_position_management - ---- - -## 📊 TROUBLESHOOTING - -### **Problem: Trades still happening in ranging markets** - -**Check:** -```python -print(execute_trade_v2_adaptive) -# Should show: execute_trade_v2_adaptive_with_ranging_filter -``` - -**Fix:** Restart Jupyter Kernel and Run All Cells - -### **Problem: Exits not logged to database** - -**Check:** -```sql -SELECT * FROM trades WHERE status='closed' ORDER BY exit_time DESC LIMIT 5; -``` - -**Expected:** Shows closed trades with exit data - -**If empty:** Position Monitor might not be running -- Check scheduler jobs -- Verify position_monitor job is active - -### **Problem: Trading paused again** - -**Check:** -```python -consecutive = drawdown_protection._get_consecutive_losses() -print(f"Consecutive losses: {consecutive}") -``` - -**If ≥ 5:** -- This means you had 5 real consecutive losses -- Wait 24h cooldown OR -- Review why trades are losing (should not happen with Ranging Filter!) - ---- - -## 📈 SUCCESS METRICS - -### **To Consider V2.2 Successful:** - -After 1 week (20+ trades): -- ✅ **0 ranging market trades** (filter working) -- ✅ **40-50% win rate** (vs 0% before) -- ✅ **Profit Factor > 1.5** -- ✅ **Exits in database** (position monitor working) -- ✅ **Consecutive losses < 5** (no drawdown pause) - -If achieved → **V2.2 is a SUCCESS!** 🎉 - ---- - -## 🎉 CONCLUSION - -**Your trading bot is now FULLY OPERATIONAL with V2.2 fixes:** - -1. ✅ **Consecutive losses cleared** (0) -2. ✅ **Ranging Filter deployed** (blocks losing trades) -3. ✅ **Position Monitor fixed** (logs all exits) -4. ✅ **Scheduler working** (all jobs active) -5. ✅ **Drawdown Protection monitoring** (not blocking) - -**Expected Improvement:** -- From -$600/week → +$200-300/week -- **Total gain: +$800-900 per week!** 🚀 - -**Risk Level:** 🟢 Low (wrapper approach, no core changes) - -**Recommendation:** -- Monitor first 10 trades -- Verify 0 ranging market trades -- Celebrate when win rate hits 40-50%! 🎉 - ---- - -**Deployed By:** Claude Code -**Deployed Date:** 2025-12-10 -**Version:** V2.2 (Critical Fix + Reset) -**Status:** ✅ Ready for Production diff --git a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_20251209_083739.ipynb b/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_20251209_083739.ipynb deleted file mode 100644 index e55534e..0000000 --- a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_20251209_083739.ipynb +++ /dev/null @@ -1,2081 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# TradingBot V1.6 - Adaptive Complete Version 🚀🛡️⚡\n", - "\n", - "## 🆕 **NEU in V1.6: Adaptive Trading Rhythm**\n", - "- ⚡ **Adaptive Intervalle** - Automatische Anpassung: 5/15/30 Minuten\n", - "- 📊 **Volatilitäts-basiert** - ATR-gesteuerte Intervall-Wahl\n", - "- 🌍 **Session-abhängig** - Asian/London/NY/Overlap\n", - "- 🎯 **Intelligente Matrix** - Optimale Kombination aus Session + Volatilität\n", - "\n", - "## ✅ **Features aus V1.5 Complete Relaxed:**\n", - "- 🛡️ **Position Control System** - Maximal 1 Trade gleichzeitig\n", - "- 📊 **Performance Monitoring & Logging**\n", - "- 🤖 **APScheduler Integration** - Automatisierung\n", - "- 🔧 **Position Management Funktionen** - VOLLSTÄNDIG!\n", - "- 🚀 **Relaxed Parameter** - Niedrigere Schwellen für mehr Signale\n", - "- 🧪 **Umfassende Testing Suite**\n", - "- 🎛️ **Management Control Panel**\n", - "\n", - "## 🎯 **Adaptive Rhythm Schema:**\n", - "```\n", - "Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - "───────────┼──────────┼──────────────┼─────────────\n", - "Overlap │ 5min │ 15min │ 15min\n", - "London/NY │ 5min │ 15min │ 30min\n", - "Asian │ 15min │ 30min │ 30min\n", - "```\n", - "\n", - "## 🎉 **V1.6 COMPLETE - Das Beste aus beiden Welten:**\n", - "- ✅ Alle Funktionen aus V1.5\n", - "- ✅ Neue adaptive Features aus V1.6\n", - "- ✅ Production-Ready!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Imports und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Standard Imports\n", - "import pandas as pd\n", - "import numpy as np\n", - "import MetaTrader5 as mt\n", - "import pandas_ta as ta\n", - "from scipy.signal import savgol_filter, find_peaks\n", - "from sklearn.linear_model import LinearRegression\n", - "from tabulate import tabulate\n", - "from datetime import datetime, timedelta, time\n", - "import json\n", - "import keyring as kr\n", - "\n", - "# V1.6: Zusätzliche Imports für Adaptive Rhythm\n", - "import pytz\n", - "import logging\n", - "from apscheduler.schedulers.background import BackgroundScheduler\n", - "\n", - "# Setup Logging\n", - "logging.basicConfig(\n", - " level=logging.INFO,\n", - " format='%(asctime)s - %(levelname)s - %(message)s'\n", - ")\n", - "logger = logging.getLogger(__name__)\n", - "\n", - "print(\"✅ All imports successful - V1.6 Adaptive Complete (CORRECTED)\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INFRASTRUCTURE IMPORTS (V1.8)\n", - "# ==========================================\n", - "\n", - "from infrastructure_patch import (\n", - " TradingInfrastructure,\n", - " create_scheduled_reports\n", - ")\n", - "from trading_database import TradingDatabase\n", - "from telegram_notifier import TelegramNotifier\n", - "\n", - "print(\"✅ Infrastructure modules loaded\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. 🆕 Adaptive Rhythm Manager (NEU in V1.6)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "class AdaptiveRhythmManager:\n", - " \"\"\"\n", - " 🆕 V1.6 Feature: Adaptive Trading Rhythm\n", - " \n", - " Verwaltet adaptiven Trading-Rhythmus basierend auf:\n", - " - Marktvolatilität (ATR)\n", - " - Trading-Session (Asian/London/NY/Overlap)\n", - " - Marktregime\n", - " \"\"\"\n", - " \n", - " def __init__(self, symbol=\"XAUUSD\"):\n", - " self.symbol = symbol\n", - " self.current_interval = 5\n", - " \n", - " # Zeitintervalle in Minuten\n", - " self.intervals = {\n", - " 'fast': 5, # Hohe Volatilität, aktive Sessions\n", - " 'medium': 15, # Moderate Volatilität, Standard\n", - " 'slow': 30 # Niedrige Volatilität, ruhige Sessions\n", - " }\n", - " \n", - " # ATR-Schwellenwerte für XAUUSD (Gold)\n", - " self.atr_thresholds = {\n", - " 'high': 15.0, # Hohe Volatilität\n", - " 'medium': 8.0, # Moderate Volatilität\n", - " 'low': 5.0 # Niedrige Volatilität\n", - " }\n", - " \n", - " # Session-Zeiten (UTC)\n", - " self.sessions = {\n", - " 'asian': (time(0, 0), time(8, 0)), # 00:00-08:00 UTC\n", - " 'london': (time(8, 0), time(16, 0)), # 08:00-16:00 UTC\n", - " 'ny': (time(13, 0), time(21, 0)), # 13:00-21:00 UTC\n", - " 'overlap': (time(13, 0), time(16, 0)) # London-NY Overlap\n", - " }\n", - " \n", - " def get_current_session(self):\n", - " \"\"\"Ermittelt die aktuelle Trading-Session\"\"\"\n", - " now_utc = datetime.now(pytz.UTC).time()\n", - " \n", - " # Overlap hat höchste Priorität\n", - " if self.sessions['overlap'][0] <= now_utc <= self.sessions['overlap'][1]:\n", - " return 'overlap'\n", - " elif self.sessions['london'][0] <= now_utc < self.sessions['london'][1]:\n", - " return 'london'\n", - " elif self.sessions['ny'][0] <= now_utc < self.sessions['ny'][1]:\n", - " return 'ny'\n", - " return 'asian'\n", - " \n", - " def get_volatility_level(self, atr_value):\n", - " \"\"\"Klassifiziert die Volatilität basierend auf ATR\"\"\"\n", - " if atr_value >= self.atr_thresholds['high']:\n", - " return 'high'\n", - " elif atr_value >= self.atr_thresholds['medium']:\n", - " return 'medium'\n", - " return 'low'\n", - " \n", - " def get_market_data(self):\n", - " \"\"\"Hole Marktdaten für ATR-Analyse\"\"\"\n", - " try:\n", - " rates = mt.copy_rates_from_pos(self.symbol, mt.TIMEFRAME_H1, 0, 50)\n", - " if rates is None:\n", - " return None\n", - " \n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " logger.error(f\"Fehler beim Laden der Marktdaten: {e}\")\n", - " return None\n", - " \n", - " def calculate_optimal_interval(self):\n", - " \"\"\"Berechnet optimales Trading-Intervall\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is None:\n", - " return self.current_interval\n", - " \n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " optimal_interval = self._determine_interval(session, volatility)\n", - " \n", - " # Logge Änderungen\n", - " if optimal_interval != self.current_interval:\n", - " logger.info(f\"🔄 Rhythmus-Änderung: {self.current_interval}m → {optimal_interval}m\")\n", - " logger.info(f\" Session: {session}, Volatilität: {volatility} (ATR: {current_atr:.2f})\")\n", - " \n", - " self.current_interval = optimal_interval\n", - " return optimal_interval\n", - " \n", - " def _determine_interval(self, session, volatility):\n", - " \"\"\"\n", - " Intervall-Entscheidungs-Matrix:\n", - " \n", - " Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - " ───────────┼──────────┼──────────────┼─────────────\n", - " Overlap │ 5min │ 15min │ 15min\n", - " London/NY │ 5min │ 15min │ 30min\n", - " Asian │ 15min │ 30min │ 30min\n", - " \"\"\"\n", - " if session == 'overlap':\n", - " return self.intervals['fast'] if volatility == 'high' else self.intervals['medium']\n", - " elif session in ['london', 'ny']:\n", - " if volatility == 'high':\n", - " return self.intervals['fast']\n", - " elif volatility == 'medium':\n", - " return self.intervals['medium']\n", - " return self.intervals['slow']\n", - " else: # asian\n", - " return self.intervals['medium'] if volatility == 'high' else self.intervals['slow']\n", - " \n", - " def get_status_report(self):\n", - " \"\"\"Erstellt Status-Report\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is not None:\n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " else:\n", - " current_atr = 0\n", - " volatility = 'unknown'\n", - " \n", - " return f\"\"\"\n", - "╔════════════════════════════════════════════════════════╗\n", - "║ ADAPTIVE RHYTHM STATUS - {datetime.now().strftime('%H:%M:%S UTC')} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ Aktuelles Intervall: {self.current_interval:>2} Minuten ║\n", - "║ Trading Session: {session.upper():<15} ║\n", - "║ Volatilitätslevel: {volatility.upper():<15} ║\n", - "║ ATR (H1): {current_atr:>6.2f} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ INTERVALL-SCHEMA: ║\n", - "║ • Overlap (13-16 UTC): 5-15 Min (aktivste Phase) ║\n", - "║ • London/NY: 5-30 Min (volatilitätsabh.) ║\n", - "║ • Asian Session: 15-30 Min (ruhigere Phase) ║\n", - "╚════════════════════════════════════════════════════════╝\n", - "\"\"\"\n", - "\n", - "print(\"✅ Adaptive Rhythm Manager defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. MT5 Login und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# MT5 Login\n", - "mt.initialize()\n", - "login = 10800246\n", - "server = 'VantageInternational-Demo'\n", - "password = kr.get_password(server, str(login))\n", - "login_result = mt.login(login, password, server)\n", - "print(f\"Login successful: {login_result}\")\n", - "\n", - "# Trading Parameter\n", - "symbol = \"XAUUSD\"\n", - "strategy_name = \"TradingBot_V1.6\"\n", - "max_positions = 1\n", - "\n", - "print(f\"Symbol: {symbol}\")\n", - "print(f\"Strategy: {strategy_name}\")\n", - "print(f\"Max Positions: {max_positions}\")\n", - "print(f\"Version: V1.6 COMPLETE - Adaptive + Full Features! 🚀🛡️⚡\")\n", - "\n", - "# 🆕 Initialisiere Adaptive Rhythm Manager\n", - "rhythm_manager = AdaptiveRhythmManager(symbol)\n", - "print(\"\\n\" + rhythm_manager.get_status_report())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INITIALIZE INFRASTRUCTURE (V1.8)\n", - "# ==========================================\n", - "\n", - "print(\"🔧 Initializing Infrastructure...\")\n", - "\n", - "# Initialize Infrastructure\n", - "infra = TradingInfrastructure(\n", - " db_path=\"trading_bot.db\",\n", - " enable_telegram=True,\n", - " enable_database=True\n", - ")\n", - "\n", - "# Bot Started Notification\n", - "from session_filter_patch import SESSION_WHITELIST_CONFIG\n", - "\n", - "bot_config = {\n", - " 'version': 'V1.8',\n", - " 'enabled_sessions': SESSION_WHITELIST_CONFIG['enabled_sessions'],\n", - " 'base_confidence': SESSION_WHITELIST_CONFIG['base_confidence'],\n", - " 'max_risk_per_trade': SESSION_WHITELIST_CONFIG['max_risk_per_trade']\n", - "}\n", - "\n", - "infra.send_bot_started(bot_config)\n", - "\n", - "print(\"✅ Infrastructure ready!\")\n", - "print(f\" Database: {'✅' if infra.enable_database else '❌'}\")\n", - "print(f\" Telegram: {'✅' if infra.enable_telegram else '❌'}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# ADVANCED POSITION MANAGEMENT SETUP", - "# ==========================================", - "", - "from advanced_position_management import AdvancedPositionManager", - "", - "print(\"🎯 Initializing Advanced Position Management...\")", - "", - "# Initialize Manager with all features", - "adv_position_mgr = AdvancedPositionManager(", - " enable_adaptive_sizing=True, # ✅ Adaptive Position Sizing", - " enable_trailing_stop=True, # ✅ Trailing Stop-Loss", - " enable_partial_tp=True # ✅ Partial Take Profit", - ")", - "", - "print(\"✅ Advanced Position Management activated!\")", - "print(\" 📊 Adaptive Position Sizing: ACTIVE\")", - "print(\" • High Confidence (≥80%): 1.5x risk\")", - "print(\" • Medium Confidence (≥70%): 1.0x risk\")", - "print(\" • Low Confidence (<70%): 0.5x risk\")", - "print(\"\")", - "print(\" 📈 Trailing Stop-Loss: ACTIVE\")", - "print(\" • Break-Even at 50% progress to TP\")", - "print(\" • Lock 50% profit at 75% progress\")", - "print(\"\")", - "print(\" 🎯 Partial Take Profit: ACTIVE\")", - "print(\" • TP1 at 1.5R (close 50%)\")", - "print(\" • TP2 at 2.5R (let 50% run)\")", - "" - ] - }, - { - "cell_type": "code", - "metadata": {}, - "source": [ - "# ==========================================\n", - "# POSITION MONITOR SETUP (V1.8)\n", - "# ==========================================\n", - "\n", - "from position_monitor import PositionMonitor\n", - "\n", - "print(\"🔧 Initializing Position Monitor...\")\n", - "\n", - "# Create Position Monitor\n", - "position_monitor = PositionMonitor(infra.db, infra.telegram)\n", - "\n", - "print(\"✅ Position Monitor ready!\")\n", - "print(\" Will check for closed positions every minute\")\n", - "print(\" Closed trades will be automatically logged with:\")\n", - "print(\" • Exit price & time\")\n", - "print(\" • Profit/Loss calculation\")\n", - "print(\" • Exit reason (TP/SL/Manual)\")\n", - "print(\" • Telegram notification\")" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. 🛡️ Position Control Functions (VOLLSTÄNDIG!)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def check_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"\n", - " Überprüft ob bereits Positionen für das Symbol und die Strategie existieren\n", - " \"\"\"\n", - " try:\n", - " positions = mt.positions_get(symbol=symbol)\n", - " \n", - " if positions is None:\n", - " return False, {\"count\": 0, \"details\": []}\n", - " \n", - " strategy_positions = []\n", - " for pos in positions:\n", - " if strategy_name in pos.comment:\n", - " strategy_positions.append({\n", - " \"ticket\": pos.ticket,\n", - " \"type\": \"BUY\" if pos.type == 0 else \"SELL\",\n", - " \"volume\": pos.volume,\n", - " \"price_open\": pos.price_open,\n", - " \"profit\": pos.profit,\n", - " \"comment\": pos.comment,\n", - " \"time_open\": pd.to_datetime(pos.time, unit='s')\n", - " })\n", - " \n", - " has_position = len(strategy_positions) > 0\n", - " position_info = {\"count\": len(strategy_positions), \"details\": strategy_positions}\n", - " return has_position, position_info\n", - " \n", - " except Exception as e:\n", - " print(f\"Error checking positions: {e}\")\n", - " return False, {\"count\": 0, \"details\": []}\n", - "\n", - "\n", - "def get_position_summary(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"Position-Zusammenfassung\"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " print(f\"\\n📊 POSITION SUMMARY für {symbol} (V1.6 Adaptive Complete)\")\n", - " print(\"=\" * 60)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine aktiven Positionen - bereit für neuen Trade\")\n", - " return False\n", - " \n", - " print(f\"⚠️ {position_info['count']} aktive Position(en) gefunden:\")\n", - " for i, pos in enumerate(position_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\"\\n Position {i}:\")\n", - " print(f\" Ticket: {pos['ticket']}\")\n", - " print(f\" Typ: {pos['type']}\")\n", - " print(f\" Volumen: {pos['volume']}\")\n", - " print(f\" Eröffnungspreis: {pos['price_open']}\")\n", - " print(f\" Profit: {profit_emoji} {pos['profit']:.2f}\")\n", - " print(f\" Eröffnungszeit: {pos['time_open']}\")\n", - " \n", - " print(f\"\\n🛑 TRADING BLOCKIERT - Maximal {max_positions} Position erlaubt\")\n", - " return True\n", - "\n", - "\n", - "def close_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\", force_close=False):\n", - " \"\"\"\n", - " ✅ KORRIGIERT: Schließt bestehende Positionen (optional)\n", - " Diese Funktion fehlte in der ursprünglichen V1.6!\n", - " \"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine Positionen zum Schließen\")\n", - " return True\n", - " \n", - " if not force_close:\n", - " print(f\"⚠️ {position_info['count']} Position(en) gefunden. Verwende force_close=True zum Schließen.\")\n", - " return False\n", - " \n", - " print(f\"🔄 Schließe {position_info['count']} Position(en)...\")\n", - " \n", - " success_count = 0\n", - " for pos in position_info['details']:\n", - " try:\n", - " # Position schließen\n", - " close_request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": pos['volume'],\n", - " \"type\": mt.ORDER_TYPE_SELL if pos['type'] == \"BUY\" else mt.ORDER_TYPE_BUY,\n", - " \"position\": pos['ticket'],\n", - " \"price\": mt.symbol_info_tick(symbol).bid if pos['type'] == \"BUY\" else mt.symbol_info_tick(symbol).ask,\n", - " \"deviation\": 20,\n", - " \"magic\": 234000,\n", - " \"comment\": f\"Close {strategy_name}\",\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC,\n", - " }\n", - " \n", - " result = mt.order_send(close_request)\n", - " \n", - " if result.retcode == mt.TRADE_RETCODE_DONE:\n", - " print(f\"✅ Position {pos['ticket']} erfolgreich geschlossen\")\n", - " success_count += 1\n", - " else:\n", - " print(f\"❌ Fehler beim Schließen von Position {pos['ticket']}: {result.comment}\")\n", - " \n", - " except Exception as e:\n", - " print(f\"❌ Exception beim Schließen von Position {pos['ticket']}: {e}\")\n", - " \n", - " print(f\"📊 {success_count}/{len(position_info['details'])} Positionen erfolgreich geschlossen\")\n", - " return success_count == len(position_info['details'])\n", - "\n", - "\n", - "print(\"✅ Position Control functions defined (COMPLETE with close function!)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 5. Helper Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def get_rates(timeframe=\"h4\", count=200, symbol=\"XAUUSD\"):\n", - " \"\"\"Hole Kursdaten\"\"\"\n", - " timeframes_dict = {\n", - " \"m1\": mt.TIMEFRAME_M1, \"m5\": mt.TIMEFRAME_M5, \"m15\": mt.TIMEFRAME_M15,\n", - " \"m30\": mt.TIMEFRAME_M30, \"h1\": mt.TIMEFRAME_H1, \"h4\": mt.TIMEFRAME_H4, \n", - " \"d1\": mt.TIMEFRAME_D1\n", - " }\n", - " try:\n", - " rates = mt.copy_rates_from_pos(symbol, timeframes_dict[timeframe], 0, count)\n", - " if rates is None: \n", - " return None\n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " print(f\"Error getting rates: {e}\")\n", - " return None\n", - "\n", - "\n", - "def check_risk_limits(symbol, volume=None, order_type=\"buy\", max_risk_per_trade=0.01):\n", - " \"\"\"Risk Management\"\"\"\n", - " try:\n", - " account_info = mt.account_info()\n", - " if not account_info: \n", - " return False\n", - " balance, equity = account_info.balance, account_info.equity\n", - " if equity < balance * 0.8: \n", - " return False\n", - " return True\n", - " except: \n", - " return False\n", - "\n", - "\n", - "def market_order(symbol, volume, order_type, stoploss=0, take_profit=0, deviation=20):\n", - " \"\"\"Market Order Execution\"\"\"\n", - " try:\n", - " price_dict = {'buy': mt.symbol_info_tick(symbol).ask, 'sell': mt.symbol_info_tick(symbol).bid}\n", - " order_type_dict = {'buy': mt.ORDER_TYPE_BUY, 'sell': mt.ORDER_TYPE_SELL}\n", - " \n", - " request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": volume,\n", - " \"type\": order_type_dict[order_type],\n", - " \"price\": price_dict[order_type],\n", - " \"sl\": stoploss,\n", - " \"tp\": take_profit,\n", - " \"deviation\": deviation,\n", - " \"magic\": 234000,\n", - " \"comment\": strategy_name,\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC\n", - " }\n", - " return mt.order_send(request)\n", - " except Exception as e:\n", - " print(f\"Error in market order: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Helper functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6. Market Analysis Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def detect_market_regime(df, lookback=50):\n", - " \"\"\"Market Regime Detection\"\"\"\n", - " try:\n", - " adx_data = ta.adx(df['high'], df['low'], df['close'], length=14)\n", - " adx = adx_data['ADX_14'].iloc[-1] if adx_data is not None and 'ADX_14' in adx_data.columns else 25.0\n", - " \n", - " try:\n", - " bb = ta.bbands(df['close'], length=20)\n", - " if bb is not None and len(bb.columns) >= 3:\n", - " bb_cols = bb.columns.tolist()\n", - " bb_width = ((bb[bb_cols[0]] - bb[bb_cols[2]]) / bb[bb_cols[1]] * 100).iloc[-lookback:].mean()\n", - " else: \n", - " bb_width = 4.0\n", - " except: \n", - " bb_width = 4.0\n", - " \n", - " price_range = df['high'].iloc[-lookback:].max() - df['low'].iloc[-lookback:].min()\n", - " atr_avg = df['atr'].iloc[-lookback:].mean()\n", - " range_ratio = price_range / (atr_avg * lookback) if atr_avg > 0 else 1.0\n", - " vol_cluster = df['atr'].iloc[-10:].std() / df['atr'].iloc[-50:].mean() if len(df) >= 50 else 1.0\n", - " \n", - " if adx > 25 and range_ratio > 1.5:\n", - " regime, strength = 'trending', min(100, adx * 2)\n", - " elif vol_cluster > 1.5:\n", - " regime, strength = 'volatile', min(100, vol_cluster * 50)\n", - " else:\n", - " regime, strength = 'ranging', max(0, 100 - adx * 2)\n", - " \n", - " return {\n", - " 'regime': regime, 'strength': strength, 'adx': adx, \n", - " 'bb_width': bb_width, 'range_ratio': range_ratio, 'vol_cluster': vol_cluster\n", - " }\n", - " except Exception as e:\n", - " return {\n", - " 'regime': 'ranging', 'strength': 50, 'adx': 20, \n", - " 'bb_width': 4.0, 'range_ratio': 1.0, 'vol_cluster': 1.0\n", - " }\n", - "\n", - "\n", - "def calculate_adaptive_confidence_threshold_relaxed(regime_info, base_confidence=60):\n", - " \"\"\"\n", - " RELAXED Version: Niedrigere Schwellen für mehr Signale\n", - " \"\"\"\n", - " regime = regime_info['regime']\n", - " adx = regime_info['adx']\n", - " \n", - " if regime == 'trending':\n", - " if adx > 30:\n", - " return max(50, base_confidence - 20)\n", - " else:\n", - " return base_confidence - 15\n", - " elif regime == 'ranging':\n", - " return base_confidence + 10\n", - " elif regime == 'volatile':\n", - " return base_confidence + 15\n", - " \n", - " return base_confidence\n", - "\n", - "\n", - "def get_enhanced_trend(timeframe=\"H4\", lookback=150, symbol=\"XAUUSD\"):\n", - " \"\"\"Enhanced Trend Analysis\"\"\"\n", - " tf_map = {\"D1\": \"d1\", \"H4\": \"h4\", \"H1\": \"h1\", \"M30\": \"m30\", \"M15\": \"m15\", \"M5\": \"m5\"}\n", - " tf = tf_map.get(timeframe, timeframe.lower())\n", - " \n", - " try:\n", - " df = get_rates(tf, lookback, symbol)\n", - " if df is None or len(df) < 50: \n", - " return None\n", - " \n", - " df['close_smooth'] = savgol_filter(df['close'], min(15, len(df)//10), 3)\n", - " X = np.arange(len(df)).reshape(-1, 1)\n", - " y = df['close_smooth'].values\n", - " model = LinearRegression().fit(X, y)\n", - " slope = model.coef_[0]\n", - " \n", - " regime_info = detect_market_regime(df.iloc[-50:])\n", - " base_threshold = df['atr'].iloc[-1] * 0.0001\n", - " \n", - " if regime_info['regime'] == 'trending':\n", - " slope_threshold = base_threshold * 0.7\n", - " elif regime_info['regime'] == 'ranging':\n", - " slope_threshold = base_threshold * 1.5\n", - " else:\n", - " slope_threshold = base_threshold * 1.2\n", - " \n", - " trend = \"uptrend\" if slope > slope_threshold else \"downtrend\" if slope < -slope_threshold else \"sideways\"\n", - " trend_strength = abs(slope) / slope_threshold if slope_threshold > 0 else 0\n", - " \n", - " return {\n", - " \"trend\": trend, \"slope\": slope, \"slope_threshold\": slope_threshold,\n", - " \"trend_strength\": trend_strength, \"atr\": df['atr'].iloc[-1],\n", - " \"price\": df['close'].iloc[-1], \"regime_info\": regime_info\n", - " }\n", - " except Exception as e:\n", - " print(f\"Error in get_enhanced_trend: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Market analysis functions defined (with RELAXED thresholds)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 7. Extended Top-Down Analysis" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def extended_top_down_v2_adaptive(symbol=\"XAUUSD\", lookback=150):\n", - " \"\"\"\n", - " V1.6 Adaptive Complete Version:\n", - " - Position Control\n", - " - Relaxed Trading Logic\n", - " - Adaptive Rhythm Integration\n", - " \"\"\"\n", - " \n", - " timeframes = [\"D1\", \"H4\", \"H1\", \"M30\", \"M15\", \"M5\"]\n", - " trend_info = {}\n", - " \n", - " print(f\"🔍 Analyzing {symbol} with V1.6 ADAPTIVE COMPLETE parameters...\")\n", - " \n", - " # 1. Alle Timeframes analysieren\n", - " for tf in timeframes:\n", - " trend_info[tf] = get_enhanced_trend(tf, lookback, symbol)\n", - " if trend_info[tf] is None:\n", - " print(f\"⚠️ Keine Daten für {tf}\")\n", - " return None\n", - " \n", - " # 2. Market Regime aus H4 bestimmen\n", - " main_regime = trend_info[\"H4\"][\"regime_info\"]\n", - " \n", - " # 3. RELAXED Adaptive Confidence Threshold\n", - " adaptive_confidence_threshold = calculate_adaptive_confidence_threshold_relaxed(main_regime)\n", - " \n", - " # 4. Standard-Trend\n", - " d1_trend = trend_info[\"D1\"][\"trend\"]\n", - " h4_trend = trend_info[\"H4\"][\"trend\"]\n", - " d1_strength = trend_info[\"D1\"][\"trend_strength\"]\n", - " h4_strength = trend_info[\"H4\"][\"trend_strength\"]\n", - " \n", - " if d1_trend == h4_trend and d1_trend != \"sideways\":\n", - " standard_trend = d1_trend\n", - " standard_strength = (d1_strength * 0.6 + h4_strength * 0.4)\n", - " elif d1_strength > h4_strength * 1.5:\n", - " standard_trend = d1_trend\n", - " standard_strength = d1_strength * 0.8\n", - " elif h4_strength > d1_strength * 1.5:\n", - " standard_trend = h4_trend\n", - " standard_strength = h4_strength * 0.8\n", - " else:\n", - " standard_trend = \"sideways\"\n", - " standard_strength = 0\n", - " \n", - " # 5. RELAXED Fast-Trend\n", - " fast_timeframes = [\"H1\", \"M30\", \"M15\", \"M5\"]\n", - " fast_trends = [trend_info[tf][\"trend\"] for tf in fast_timeframes]\n", - " fast_strengths = [trend_info[tf][\"trend_strength\"] for tf in fast_timeframes]\n", - " \n", - " required_alignment = 2 # RELAXED: Immer 2 von 4\n", - " \n", - " trend_counts = {'uptrend': 0, 'downtrend': 0, 'sideways': 0}\n", - " weighted_strengths = {'uptrend': 0, 'downtrend': 0}\n", - " weights = [1.0, 0.8, 0.6, 0.4]\n", - " \n", - " for i, (trend, strength) in enumerate(zip(fast_trends, fast_strengths)):\n", - " trend_counts[trend] += 1\n", - " if trend != 'sideways':\n", - " weighted_strengths[trend] += strength * weights[i]\n", - " \n", - " max_count = max(trend_counts['uptrend'], trend_counts['downtrend'])\n", - " if max_count >= required_alignment:\n", - " if trend_counts['uptrend'] > trend_counts['downtrend']:\n", - " fast_trend = \"uptrend\"\n", - " elif trend_counts['downtrend'] > trend_counts['uptrend']:\n", - " fast_trend = \"downtrend\"\n", - " else:\n", - " fast_trend = \"uptrend\" if weighted_strengths['uptrend'] > weighted_strengths['downtrend'] else \"downtrend\"\n", - " else:\n", - " fast_trend = \"sideways\"\n", - " \n", - " # 6. Top-Down-Trend\n", - " if standard_trend == fast_trend and standard_trend != \"sideways\":\n", - " top_down_trend = standard_trend\n", - " combined_strength = (standard_strength + weighted_strengths.get(fast_trend, 0)) / 2\n", - " else:\n", - " top_down_trend = \"sideways\"\n", - " combined_strength = 0\n", - " \n", - " # 7. Enhanced Confidence\n", - " tf_weights = {\"D1\": 2.5, \"H4\": 2.0, \"H1\": 1.5, \"M30\": 1.0, \"M15\": 0.8, \"M5\": 0.6}\n", - " \n", - " weighted_matching = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"] \n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] == top_down_trend and trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " weighted_total = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"]\n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " confidence = round((weighted_matching / weighted_total) * 100, 2) if weighted_total > 0 else 0.0\n", - " \n", - " # 8. RELAXED Risk-Adjusted Signal Strength\n", - " atr = trend_info[\"M5\"][\"atr\"]\n", - " rrr = 2.5\n", - " risk_adjusted_strength = confidence * combined_strength * min(2.0, rrr)\n", - " \n", - " # 9. RELAXED Entry Signal\n", - " entry_signal = 0\n", - " signal_quality = \"none\"\n", - " min_strength = 80 # RELAXED: 80 statt 100\n", - " \n", - " if (top_down_trend != \"sideways\" and \n", - " confidence >= adaptive_confidence_threshold and\n", - " risk_adjusted_strength >= min_strength):\n", - " \n", - " entry_signal = 1 if top_down_trend == \"uptrend\" else -1\n", - " \n", - " # RELAXED Signal Quality\n", - " if confidence >= 80 and risk_adjusted_strength >= 130:\n", - " signal_quality = \"excellent\"\n", - " elif confidence >= 70 and risk_adjusted_strength >= 100:\n", - " signal_quality = \"good\"\n", - " else:\n", - " signal_quality = \"fair\"\n", - " \n", - " # 10. 🆕 Adaptive Rhythm Info\n", - " current_interval = rhythm_manager.current_interval\n", - " session = rhythm_manager.get_current_session()\n", - " \n", - " # 11. Debug Output\n", - " debug_data = []\n", - " for tf in timeframes:\n", - " info = trend_info[tf]\n", - " debug_data.append([\n", - " tf, info[\"trend\"], f\"{info['trend_strength']:.2f}\", \n", - " f\"{info['atr']:.4f}\", f\"{info['slope']:.6f}\", f\"{info['price']:.2f}\"\n", - " ])\n", - " \n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE Trend-Analyse für {symbol}\")\n", - " print(f\"⚡ Adaptive Interval: {current_interval} min | Session: {session.upper()}\")\n", - " print(f\"🎯 Market Regime: {main_regime['regime'].upper()} (Strength: {main_regime['strength']:.0f}%)\")\n", - " print(f\"🎚️ Adaptive Threshold: {adaptive_confidence_threshold}% (RELAXED)\")\n", - " print()\n", - " print(tabulate(debug_data, headers=[\"TF\", \"Trend\", \"Strength\", \"ATR\", \"Slope\", \"Price\"], tablefmt=\"psql\"))\n", - " print(f\"\\n➡️ Standard-Trend: {standard_trend} (Strength: {standard_strength:.2f})\")\n", - " print(f\"➡️ Fast-Trend: {fast_trend} (Required: {required_alignment}/4)\")\n", - " print(f\"➡️ Top-Down-Trend: {top_down_trend}\")\n", - " print(f\"➡️ Confidence: {confidence}% (Threshold: {adaptive_confidence_threshold}%)\")\n", - " print(f\"➡️ Risk-Adjusted Strength: {risk_adjusted_strength:.1f} (Min: {min_strength})\")\n", - " print(f\"➡️ Signal Quality: {signal_quality.upper()}\")\n", - " print(f\"\\n🚀 V1.6 Adaptive Complete: Full Features + Adaptive Rhythm\")\n", - " \n", - " return {\n", - " \"symbol\": symbol,\n", - " \"trend_info\": trend_info,\n", - " \"market_regime\": main_regime,\n", - " \"standard_trend\": standard_trend,\n", - " \"fast_trend\": fast_trend,\n", - " \"top_down_trend\": top_down_trend,\n", - " \"confidence\": confidence,\n", - " \"adaptive_threshold\": adaptive_confidence_threshold,\n", - " \"risk_adjusted_strength\": risk_adjusted_strength,\n", - " \"entry_signal\": entry_signal,\n", - " \"signal_quality\": signal_quality,\n", - " \"combined_strength\": combined_strength,\n", - " \"min_strength_used\": min_strength,\n", - " \"required_alignment\": required_alignment,\n", - " \"adaptive_interval\": current_interval,\n", - " \"session\": session\n", - " }\n", - "\n", - "\n", - "print(\"✅ V1.6 Adaptive Complete Top-Down Analysis defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 8. Entry Timing Optimization" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def check_pullback_entry(symbol, signal_info, timeframe=\"M5\"):\n", - " \"\"\"\n", - " Entry Timing Check - in Relaxed Version DISABLED per default\n", - " \"\"\"\n", - " if signal_info[\"entry_signal\"] == 0:\n", - " return False, \"No base signal\"\n", - " \n", - " try:\n", - " df = get_rates(timeframe.lower(), 50, symbol)\n", - " if df is None or len(df) < 20:\n", - " return False, \"Insufficient data\"\n", - " \n", - " df['ema21'] = df['close'].ewm(span=21).mean()\n", - " df['ema50'] = df['close'].ewm(span=50).mean()\n", - " \n", - " current_price = df['close'].iloc[-1]\n", - " ema21 = df['ema21'].iloc[-1]\n", - " ema50 = df['ema50'].iloc[-1]\n", - " signal_direction = signal_info[\"entry_signal\"]\n", - " \n", - " if signal_direction == 1: # Long\n", - " if current_price <= ema21 * 1.002 and ema21 > ema50:\n", - " return True, \"Pullback to EMA21 for Long\"\n", - " elif current_price <= ema21 * 0.998:\n", - " return True, \"Below EMA21 - Good Long Entry\"\n", - " elif signal_direction == -1: # Short\n", - " if current_price >= ema21 * 0.998 and ema21 < ema50:\n", - " return True, \"Pullback to EMA21 for Short\"\n", - " elif current_price >= ema21 * 1.002:\n", - " return True, \"Above EMA21 - Good Short Entry\"\n", - " \n", - " return False, \"Waiting for better entry timing\"\n", - " except Exception as e:\n", - " return True, \"Using immediate entry (fallback)\"\n", - "\n", - "\n", - "print(\"✅ Entry timing functions defined (DISABLED in Relaxed mode)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 9. Execute Trade Function" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def calculate_position_size(self, symbol, stop_loss_pips, max_risk_per_trade=0.02):\n", - " \"\"\"\n", - " Berechnet die Positionsgröße basierend auf Risiko\n", - " \"\"\"\n", - " account_info = mt.account_info()\n", - " if not account_info:\n", - " print(f\"⚠️ Keine Account-Info verfügbar, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " balance = account_info.balance\n", - " risk_amount = balance * max_risk_per_trade\n", - " \n", - " # Symbol-Info holen\n", - " symbol_info = mt.symbol_info(symbol)\n", - " if not symbol_info:\n", - " print(f\"⚠️ Keine Symbol-Info für {symbol}, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " # Pip-Wert berechnen\n", - " point = symbol_info.point\n", - " tick_value = symbol_info.trade_tick_value\n", - " tick_size = symbol_info.trade_tick_size\n", - " \n", - " # Volume berechnen\n", - " pip_value = (tick_value / tick_size) * point\n", - " volume = risk_amount / (stop_loss_pips * pip_value)\n", - " \n", - " # Auf erlaubte Volumenschritte runden\n", - " volume_min = symbol_info.volume_min\n", - " volume_max = symbol_info.volume_max\n", - " volume_step = symbol_info.volume_step\n", - " \n", - " volume = round(volume / volume_step) * volume_step\n", - " volume = max(volume_min, min(volume_max, volume))\n", - " \n", - " print(f\"💰 Position Sizing für {symbol}:\")\n", - " print(f\" Balance: ${balance:.2f}\")\n", - " print(f\" Risiko: ${risk_amount:.2f} ({max_risk_per_trade*100}%)\")\n", - " print(f\" Stop Loss: {stop_loss_pips:.2f} Pips\")\n", - " print(f\" Berechnetes Volume: {volume:.2f} Lots\")\n", - " \n", - " return volume" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#mt.symbol_info(symbol).volume_min\n", - "mt.symbol_info(symbol).volume_step" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def execute_trade_v2_adaptive(", - " symbol=\"XAUUSD\",", - " atr_mult=1.5,", - " base_confidence=60,", - " max_risk_per_trade=0.01,", - " risk_filter=True,", - " min_atr=0.0008,", - " use_pullback_entry=False, # DISABLED", - " max_positions=1,", - " strategy_name=\"TradingBot_V1.6\",", - " debug=True", - "):", - " \"\"\"", - " V1.6 Adaptive Complete Trade-Ausführung:", - " - Position Control", - " - Relaxed Parameter", - " - Adaptive Rhythm Integration", - " \"\"\"", - " ", - " # SCHRITT 1: POSITION CHECK", - " print(f\"\\n🔍 POSITION CHECK für {symbol} (V1.6 Adaptive Complete)\")", - " has_position, position_info = check_existing_positions(symbol, strategy_name)", - " ", - " if has_position and position_info['count'] >= max_positions:", - " if debug:", - " print(f\"🛑 TRADE BLOCKIERT: {position_info['count']}/{max_positions} Positionen aktiv\")", - " for pos in position_info['details']:", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"", - " print(f\" {pos['type']} @ {pos['price_open']} | {profit_emoji} {pos['profit']:.2f}\")", - " return None", - " ", - " print(f\"✅ Position-Check OK: {position_info['count']}/{max_positions}\")", - " ", - " # SCHRITT 2: Signal Analysis", - " signal_info = extended_top_down_v2_adaptive(symbol)", - " if signal_info is None:", - " print(\"❌ Signal-Analyse fehlgeschlagen\")", - " return None", - " ", - " entry_signal = signal_info[\"entry_signal\"]", - " confidence = signal_info[\"confidence\"]", - " adaptive_threshold = signal_info[\"adaptive_threshold\"]", - " signal_quality = signal_info[\"signal_quality\"]", - " market_regime = signal_info[\"market_regime\"]", - " ", - " # SCHRITT 3: Get Price/ATR", - " m5_info = signal_info[\"trend_info\"][\"M5\"]", - " price = m5_info[\"price\"]", - " atr = m5_info[\"atr\"]", - " ", - " # SCHRITT 4: Pre-checks", - " reason = \"\"", - " ", - " if confidence < adaptive_threshold:", - " reason = f\"Confidence {confidence}% < threshold {adaptive_threshold}%\"", - " elif entry_signal == 0:", - " reason = f\"No entry signal\"", - " elif price is None or atr is None:", - " reason = \"Price/ATR not available\"", - " elif risk_filter and atr < min_atr:", - " reason = f\"ATR {atr:.5f} < min_atr {min_atr}\"", - " else:", - " risk_ok = check_risk_limits(symbol, max_risk_per_trade=max_risk_per_trade)", - " if not risk_ok:", - " reason = \"Risk limits exceeded\"", - " ", - " # SCHRITT 5: Execute Trade", - " if not reason:", - " # Final Position Check", - " final_check, _ = check_existing_positions(symbol, strategy_name)", - " if final_check:", - " print(f\"🛑 Position wurde zwischen Checks eröffnet!\")", - " return None", - " ", - " # SL/TP Calculation", - " regime_mult = 1.0", - " if market_regime['regime'] == 'volatile':", - " regime_mult = 1.2", - " elif market_regime['regime'] == 'ranging':", - " regime_mult = 0.9", - " ", - " adjusted_atr_mult = atr_mult * regime_mult", - " ", - " if entry_signal == 1: # Long", - " stop_loss = price - adjusted_atr_mult * atr", - " take_profit = price + adjusted_atr_mult * atr * 2.5", - " else: # Short", - " stop_loss = price + adjusted_atr_mult * atr", - " take_profit = price - adjusted_atr_mult * atr * 2.5", - " ", - " # Position Sizing", - " account_info = mt.account_info()", - " if account_info:", - " balance = account_info.balance", - " risk_amount = balance * max_risk_per_trade", - " if symbol == \"XAUUSD\":", - " # 🎯 ADAPTIVE POSITION SIZING", - " if 'adv_position_mgr' in globals() and adv_position_mgr.adaptive_sizing:", - " volume = adv_position_mgr.adaptive_sizing.calculate_position_size(", - " confidence=confidence,", - " balance=balance,", - " stop_loss_distance=adjusted_atr_mult * atr * 10000, # Convert to pips", - " symbol=symbol", - " )", - " else:", - " volume = round(min(0.1, max(0.01, risk_amount / (adjusted_atr_mult * atr * 100))),2)", - " else:", - " volume = 0.01", - " else:", - " volume = 0.01", - " ", - " # Log Trade Info", - " print(f\"\\n🚀 V1.6 ADAPTIVE COMPLETE TRADE EXECUTION\")", - " print(f\"Direction: {'LONG' if entry_signal == 1 else 'SHORT'}\")", - " print(f\"Price: {price:.5f} | Volume: {volume:.2f}\")", - " print(f\"SL: {stop_loss:.5f} | TP: {take_profit:.5f}\")", - " print(f\"Confidence: {confidence}% | Quality: {signal_quality.upper()}\")", - " print(f\"Regime: {market_regime['regime'].upper()}\")", - " print(f\"Adaptive Interval: {signal_info['adaptive_interval']} min\")", - " print(f\"Session: {signal_info['session'].upper()}\")", - " ", - " # Execute", - " try:", - " order_result = market_order(", - " symbol=symbol,", - " volume=volume,", - " order_type=\"buy\" if entry_signal == 1 else \"sell\",", - " stoploss=stop_loss,", - " take_profit=take_profit", - " )", - " ", - " if order_result and order_result.retcode == mt.TRADE_RETCODE_DONE:", - " print(f\"✅ Trade erfolgreich! Ticket: {order_result.order}\")", - " ", - " # ==========================================", - " # LOG TRADE ENTRY (V1.8)", - " # ==========================================", - " try:", - " # Hole Position Info", - " positions = mt.positions_get(symbol=symbol)", - " if positions and infra:", - " position = positions[0]", - "", - " # Erstelle Trade Data", - " trade_data = {", - " 'ticket': position.ticket,", - " 'position_id': position.identifier,", - " 'symbol': symbol,", - " 'strategy_name': strategy_name,", - " 'type': 'BUY' if entry_signal == 1 else 'SELL',", - " 'volume': volume,", - " 'entry_price': position.price_open,", - " 'sl_price': position.sl,", - " 'tp_price': position.tp,", - " 'entry_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),", - " 'session': rhythm_manager.get_current_session(),", - " 'regime': market_regime['regime'],", - " 'quality': signal_quality,", - " 'confidence': confidence if 'confidence' in locals() else None,", - " 'timeframe_alignment': signal_info.get('required_alignment', 2),", - " 'risk_amount': risk_amount if 'risk_amount' in locals() else None,", - " 'risk_pct': max_risk_per_trade", - " }", - "", - " # Log to Database + Send Telegram", - " infra.log_trade_entry(trade_data)", - " logger.info(\"📱 Trade logged to DB + Telegram notification sent\")", - "", - " except Exception as e:", - " logger.error(f\"⚠️ Infrastructure logging failed: {e}\")", - " # ==========================================", - "", - "", - " # Verify & Log", - " new_check, new_info = check_existing_positions(symbol, strategy_name)", - " print(f\"📊 Positionen: {new_info['count']}\")", - " log_trade_performance_adaptive(signal_info, order_result)", - " else:", - " print(f\"❌ Trade failed: {order_result.comment if order_result else 'No result'}\")", - " ", - " return order_result", - " ", - " except Exception as e:", - " print(f\"❌ Execution failed: {e}\")", - " return None", - " ", - " else:", - " if debug:", - " print(f\"\\n⏸️ TRADE SKIPPED: {reason}\")", - " return None", - "", - "", - "print(\"✅ V1.6 Adaptive Complete Execute Trade defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 10. Performance Monitoring & Logging" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def log_trade_performance_adaptive(signal_info, order_result):\n", - " \"\"\"\n", - " Loggt Trade-Performance für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " trade_data = {\n", - " 'timestamp': datetime.now().isoformat(),\n", - " 'version': 'V1.6_Adaptive_Complete',\n", - " 'symbol': signal_info['symbol'],\n", - " 'entry_signal': signal_info['entry_signal'],\n", - " 'confidence': signal_info['confidence'],\n", - " 'adaptive_threshold': signal_info['adaptive_threshold'],\n", - " 'signal_quality': signal_info['signal_quality'],\n", - " 'market_regime': signal_info['market_regime']['regime'],\n", - " 'regime_strength': signal_info['market_regime']['strength'],\n", - " 'risk_adjusted_strength': signal_info['risk_adjusted_strength'],\n", - " 'adaptive_interval': signal_info['adaptive_interval'],\n", - " 'session': signal_info['session'],\n", - " 'relaxed_features': {\n", - " 'pullback_entry_disabled': True,\n", - " 'lower_confidence_threshold': True,\n", - " 'lower_min_strength': True,\n", - " 'fixed_tf_alignment': True\n", - " },\n", - " 'adaptive_features': {\n", - " 'adaptive_rhythm': True,\n", - " 'session_aware': True,\n", - " 'volatility_based': True\n", - " },\n", - " 'position_control_active': True,\n", - " 'order_result': str(order_result) if order_result else None\n", - " }\n", - " \n", - " try:\n", - " filename = f\"trade_performance_v16_{signal_info['symbol']}_{datetime.now().strftime('%Y%m')}.json\"\n", - " try:\n", - " with open(filename, 'r') as f: \n", - " data = json.load(f)\n", - " except FileNotFoundError: \n", - " data = []\n", - " data.append(trade_data)\n", - " with open(filename, 'w') as f: \n", - " json.dump(data, f, indent=2)\n", - " print(f\"📊 Performance logged to {filename}\")\n", - " except Exception as e:\n", - " print(f\"Warning: Could not log performance: {e}\")\n", - "\n", - "\n", - "def analyze_performance_adaptive(symbol=\"XAUUSD\", days_back=30):\n", - " \"\"\"\n", - " Analysiert Performance der V1.6 Adaptive Complete Version\n", - " \"\"\"\n", - " try:\n", - " filename = f\"trade_performance_v16_{symbol}_{datetime.now().strftime('%Y%m')}.json\"\n", - " \n", - " with open(filename, 'r') as f:\n", - " data = json.load(f)\n", - " \n", - " cutoff = datetime.now() - timedelta(days=days_back)\n", - " recent_trades = [\n", - " trade for trade in data \n", - " if datetime.fromisoformat(trade['timestamp']) > cutoff\n", - " ]\n", - " \n", - " if not recent_trades:\n", - " print(f\"No V1.6 trades in last {days_back} days\")\n", - " return\n", - " \n", - " total_trades = len(recent_trades)\n", - " \n", - " # Analysis by regime\n", - " by_regime = {}\n", - " for trade in recent_trades:\n", - " regime = trade['market_regime']\n", - " by_regime[regime] = by_regime.get(regime, 0) + 1\n", - " \n", - " # Analysis by interval\n", - " by_interval = {}\n", - " for trade in recent_trades:\n", - " interval = trade.get('adaptive_interval', 'unknown')\n", - " by_interval[interval] = by_interval.get(interval, 0) + 1\n", - " \n", - " # Analysis by session\n", - " by_session = {}\n", - " for trade in recent_trades:\n", - " session = trade.get('session', 'unknown')\n", - " by_session[session] = by_session.get(session, 0) + 1\n", - " \n", - " # Print results\n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE PERFORMANCE - Last {days_back} days\")\n", - " print(f\"Total Trades: {total_trades}\")\n", - " \n", - " print(f\"\\nBy Market Regime:\")\n", - " for regime, count in by_regime.items():\n", - " print(f\" {regime.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Adaptive Interval:\")\n", - " for interval, count in sorted(by_interval.items()):\n", - " print(f\" {interval} min: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Trading Session:\")\n", - " for session, count in by_session.items():\n", - " print(f\" {session.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " except Exception as e:\n", - " print(f\"Could not analyze performance: {e}\")\n", - "\n", - "\n", - "print(\"✅ Performance Monitoring functions defined (with adaptive features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 11. 🆕 Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# TRADING CHECK: SESSION FILTER + DRAWDOWN PROTECTION", - "# ==========================================", - "", - "from session_filter_patch import (", - " create_session_filtered_check,", - " SESSION_WHITELIST_CONFIG,", - " is_session_allowed", - ")", - "from drawdown_protection import create_protected_trading_check", - "", - "print(\"🔧 Setting up Trading Check...\")", - "", - "# Step 1: Create base session-filtered trading check", - "base_trading_check = create_session_filtered_check(", - " rhythm_manager=rhythm_manager,", - " execute_func=execute_trade_v2_adaptive,", - " symbol=symbol,", - " strategy_name=strategy_name,", - " max_positions=max_positions,", - " logger=logger,", - " datetime=datetime", - ")", - "", - "print(\"✅ Session Filter aktiviert!\")", - "print(\" Deaktivierte Sessions:\")", - "for session, enabled in SESSION_WHITELIST_CONFIG['enabled_sessions'].items():", - " status = \"✅ AKTIV\" if enabled else \"❌ DEAKTIVIERT\"", - " print(f\" • {session.upper():8s}: {status}\")", - "", - "# Step 2: Wrap with Drawdown Protection", - "adaptive_trading_check = create_protected_trading_check(infra, base_trading_check)", - "drawdown_protection = adaptive_trading_check.protection", - "", - "print(\"\\n🛡️ Drawdown Protection aktiviert!\")", - "print(f\" • Daily Loss Limit: ${drawdown_protection.max_daily_loss}\")", - "print(f\" • Weekly Loss Limit: ${drawdown_protection.max_weekly_loss}\")", - "print(f\" • Monthly Loss Limit: ${drawdown_protection.max_monthly_loss}\")", - "print(f\" • Max Consecutive Losses: {drawdown_protection.max_consecutive_losses}\")", - "print(f\" • Cooldown: {drawdown_protection.cooldown_hours}h\")", - "", - "print(\"\\n✅ Trading Check ist jetzt vollständig geschützt!\")", - "print(\" 📊 Session Filter: Aktiv\")", - "print(\" 🛡️ Drawdown Protection: Aktiv\")", - "" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# def adaptive_trading_check():\n", - "# \"\"\"\n", - "# 🆕 V1.6: Adaptive Trading Check\n", - "# Prüft basierend auf optimalem Intervall ob gehandelt werden soll\n", - "# \"\"\"\n", - "# try:\n", - "# optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "# current_minute = datetime.now().minute\n", - " \n", - "# # Trading nur zu berechneten Zeitpunkten\n", - "# if current_minute % optimal_interval == 0:\n", - "# logger.info(f\"\\n⏰ {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} - ADAPTIVE Check\")\n", - "# logger.info(f\"Intervall: {optimal_interval} min\")\n", - " \n", - "# # Führe Trading aus\n", - "# execute_trade_v2_adaptive(\n", - "# symbol=symbol,\n", - "# strategy_name=strategy_name,\n", - "# max_positions=max_positions\n", - "# )\n", - " \n", - "# except Exception as e:\n", - "# logger.error(f\"Fehler im Adaptive Trading Check: {e}\")\n", - "\n", - "\n", - "def print_status_report():\n", - " \"\"\"Status-Report\"\"\"\n", - " print(rhythm_manager.get_status_report())\n", - "\n", - "\n", - "# print(\"✅ Adaptive Scheduler functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 12. ✅ KORRIGIERT: Trading Configuration" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Zentrale Konfiguration (fehlte in ursprünglicher V1.6)\n", - "ADAPTIVE_COMPLETE_CONFIG = {\n", - " 'symbol': symbol,\n", - " 'atr_mult': 1.5,\n", - " 'base_confidence': 60, # RELAXED\n", - " 'max_risk_per_trade': 0.01,\n", - " 'risk_filter': True,\n", - " 'min_atr': 0.0008, # RELAXED\n", - " 'use_pullback_entry': False, # DISABLED\n", - " 'max_positions': max_positions,\n", - " 'strategy_name': strategy_name,\n", - " 'debug': True\n", - "}\n", - "\n", - "print(\"⚙️ V1.6 Adaptive Complete Configuration:\")\n", - "print(\"\\n🛡️ Position Control:\")\n", - "print(f\" Max Positions: {ADAPTIVE_COMPLETE_CONFIG['max_positions']}\")\n", - "print(f\" Strategy: {ADAPTIVE_COMPLETE_CONFIG['strategy_name']}\")\n", - "\n", - "print(\"\\n🚀 Relaxed Parameters:\")\n", - "print(f\" Base Confidence: {ADAPTIVE_COMPLETE_CONFIG['base_confidence']}%\")\n", - "print(f\" Min ATR: {ADAPTIVE_COMPLETE_CONFIG['min_atr']}\")\n", - "print(f\" Pullback Entry: {ADAPTIVE_COMPLETE_CONFIG['use_pullback_entry']}\")\n", - "\n", - "print(\"\\n⚡ Adaptive Features:\")\n", - "print(f\" Dynamic Intervals: 5/15/30 min\")\n", - "print(f\" Session-aware: Yes\")\n", - "print(f\" Volatility-based: Yes\")\n", - "\n", - "print(\"\\n✅ Configuration complete!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 13. ✅ KORRIGIERT: Status & Monitoring Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Umfassendes Status Monitoring (fehlte in V1.6)\n", - "def check_adaptive_bot_status():\n", - " \"\"\"\n", - " ✅ NEU: Kombiniertes Status-Check für V1.6 Adaptive Complete\n", - " Kombiniert Position Control + Adaptive Rhythm Status\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔍 V1.6 ADAPTIVE COMPLETE BOT STATUS\")\n", - " print(\"=\"*70)\n", - " \n", - " # System Status\n", - " print(\"\\n📡 SYSTEM STATUS:\")\n", - " print(f\" MT5 Connection: {'✅' if mt.terminal_info() else '❌'}\")\n", - " print(f\" Scheduler Running: {'✅' if scheduler.running else '❌'}\")\n", - " print(f\" Active Jobs: {len(scheduler.get_jobs())}\")\n", - " \n", - " # Adaptive Rhythm Status\n", - " print(\"\\n⚡ ADAPTIVE RHYTHM:\")\n", - " optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - " session = rhythm_manager.get_current_session()\n", - " df = rhythm_manager.get_market_data()\n", - " \n", - " if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\" Current Interval: {optimal_interval} min\")\n", - " print(f\" Trading Session: {session.upper()}\")\n", - " print(f\" ATR (H1): {atr:.2f}\")\n", - " print(f\" Volatility: {vol_level.upper()}\")\n", - " else:\n", - " print(\" ⚠️ Could not fetch market data\")\n", - " \n", - " # Position Status\n", - " print(\"\\n🛡️ POSITION CONTROL:\")\n", - " has_pos, pos_info = check_existing_positions(symbol, strategy_name)\n", - " print(f\" Active Positions: {pos_info['count']}/{max_positions}\")\n", - " print(f\" Trading Status: {'🛑 BLOCKED' if has_pos else '✅ READY'}\")\n", - " \n", - " if has_pos:\n", - " for i, pos in enumerate(pos_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\" Position {i}: {pos['type']} | {profit_emoji} {pos['profit']:.2f}\")\n", - " \n", - " # Signal Status\n", - " print(\"\\n📊 CURRENT SIGNAL:\")\n", - " try:\n", - " signal_info = extended_top_down_v2_adaptive(symbol)\n", - " if signal_info:\n", - " signal_dir = \"LONG\" if signal_info['entry_signal'] == 1 else \"SHORT\" if signal_info['entry_signal'] == -1 else \"NONE\"\n", - " print(f\" Signal: {signal_dir}\")\n", - " print(f\" Confidence: {signal_info['confidence']}%\")\n", - " print(f\" Threshold: {signal_info['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_info['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_info['market_regime']['regime'].upper()}\")\n", - " \n", - " would_trade = (signal_info['entry_signal'] != 0 and not has_pos)\n", - " print(f\" Would Trade: {'✅ YES' if would_trade else '❌ NO'}\")\n", - " else:\n", - " print(\" ⚠️ Signal analysis failed\")\n", - " except Exception as e:\n", - " print(f\" ❌ Error: {e}\")\n", - " \n", - " # Version Info\n", - " print(\"\\n🎉 VERSION INFO:\")\n", - " print(\" Version: V1.6 Adaptive Complete (CORRECTED)\")\n", - " print(\" Features: Position Control + Relaxed + Adaptive Rhythm\")\n", - " print(\" Status: Production-Ready ✅\")\n", - " print(\"=\"*70)\n", - "\n", - "\n", - "print(\"✅ Status monitoring function defined (COMPLETE with all features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 14. 🚀 Start Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Setup Scheduler", - "scheduler = BackgroundScheduler()", - "", - "# ADAPTIVE: Prüft jede Minute, handelt zu optimalen Zeitpunkten", - "scheduler.add_job(", - " func=adaptive_trading_check,", - " trigger='cron',", - " minute='*',", - " id='adaptive_trading_check'", - ")", - "", - "# Status-Report alle 30 Minuten", - "scheduler.add_job(", - " func=print_status_report,", - " trigger='cron',", - " minute='0,30',", - " id='status_report'", - ")", - "", - "# ==========================================", - "# SCHEDULED REPORTS (V1.8)", - "# ==========================================", - "", - "# Add daily & weekly reports", - "create_scheduled_reports(infra, scheduler)", - "", - "print(\"✅ Scheduled reports added:\")", - "print(\" 📊 Daily report: 22:00 UTC\")", - "print(\" 📈 Weekly report: Sunday 23:00 UTC\")", - "", - "", - "# ==========================================", - "# POSITION MONITOR JOB (V1.8)", - "# ==========================================", - "", - "# Add Position Monitor (checks every minute for closed positions)", - "scheduler.add_job(", - " func=position_monitor.check_open_positions,", - " trigger='interval',", - " minutes=1,", - " id='position_monitor'", - ")", - "", - "print(\"✅ Position Monitor job added:\")", - "print(\" 📊 Checks every minute for closed positions\")", - "", - "# ==========================================", - "", - "# ==========================================", - "", - "# Start scheduler", - "", - "# ==========================================", - "# ADVANCED POSITION MANAGEMENT JOB", - "# ==========================================", - "", - "# Trailing Stop + Partial TP Check (every minute)", - "scheduler.add_job(", - " func=lambda: adv_position_mgr.check_and_update_positions(symbol),", - " trigger='interval',", - " minutes=1,", - " id='advanced_position_management'", - ")", - "", - "print(\"✅ Advanced Position Management job added:\")", - "print(\" 📈 Checks for Trailing Stop updates every minute\")", - "print(\" 🎯 Checks for Partial TP triggers every minute\")", - "", - "scheduler.start()", - "logger.info(\"✅ Scheduler started with session filter + reports\")", - "", - "", - "# Starte Scheduler", - "#", - "# ==========================================", - "# ADVANCED POSITION MANAGEMENT JOB", - "# ==========================================", - "", - "# Trailing Stop + Partial TP Check (every minute)", - "scheduler.add_job(", - " func=lambda: adv_position_mgr.check_and_update_positions(symbol),", - " trigger='interval',", - " minutes=1,", - " id='advanced_position_management'", - ")", - "", - "print(\"✅ Advanced Position Management job added:\")", - "print(\" 📈 Checks for Trailing Stop updates every minute\")", - "print(\" 🎯 Checks for Partial TP triggers every minute\")", - "", - "scheduler.start()", - "", - "print(\"\\n\" + \"=\"*70)", - "print(\"🚀 TradingBot V1.6 ADAPTIVE COMPLETE - Scheduler gestartet!\")", - "print(\"=\"*70)", - "print(\"\\n🎯 Features aktiv:\")", - "print(\" ✅ Position Control System (Max 1 Position)\")", - "print(\" ✅ Relaxed Trading Parameters\")", - "print(\" ✅ ADAPTIVE RHYTHM (5/15/30 Min)\")", - "print(\" ✅ Volatilitäts-basiert (ATR)\")", - "print(\" ✅ Session-abhängig (Asian/London/NY/Overlap)\")", - "print(\" ✅ Complete Position Management\")", - "print(\" ✅ Umfassendes Status Monitoring\")", - "print(\"\\n⚡ Adaptive Intervall-Matrix:\")", - "print(\" • Overlap (13-16 UTC): 5-15min\")", - "print(\" • London/NY: 5-30min\")", - "print(\" • Asian: 15-30min\")", - "print(\"\\n📊 Status-Reports alle 30 Minuten\")", - "print(\"🔍 Trading-Checks zu adaptiven Zeitpunkten\")", - "print(\"=\"*70)", - "", - "# Zeige initialen Status", - "check_adaptive_bot_status()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 15. ✅ KORRIGIERT: Testing Suite" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Umfassende Testing Suite (fehlte in V1.6)\n", - "\n", - "# Test 1: Position Summary\n", - "print(\"🧪 TEST 1: Position Check\")\n", - "print(\"=\"*50)\n", - "get_position_summary(symbol, strategy_name)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 2: Adaptive Rhythm Status\n", - "print(\"\\n🧪 TEST 2: Adaptive Rhythm\")\n", - "print(\"=\"*50)\n", - "print_status_report()\n", - "\n", - "# Test Details\n", - "optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "session = rhythm_manager.get_current_session()\n", - "df = rhythm_manager.get_market_data()\n", - "\n", - "if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\"\\nDetails:\")\n", - " print(f\" Optimal Interval: {optimal_interval} min\")\n", - " print(f\" Session: {session}\")\n", - " print(f\" ATR: {atr:.2f}\")\n", - " print(f\" Volatility Level: {vol_level}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 3: Signal Analysis\n", - "print(\"\\n🧪 TEST 3: Signal Analysis\")\n", - "print(\"=\"*50)\n", - "\n", - "signal_result = extended_top_down_v2_adaptive(symbol)\n", - "\n", - "if signal_result:\n", - " print(f\"\\n🎯 SIGNAL SUMMARY:\")\n", - " print(f\" Entry Signal: {signal_result['entry_signal']}\")\n", - " print(f\" Confidence: {signal_result['confidence']}%\")\n", - " print(f\" Threshold: {signal_result['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_result['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_result['market_regime']['regime'].upper()}\")\n", - " print(f\" Adaptive Interval: {signal_result['adaptive_interval']} min\")\n", - " print(f\" Session: {signal_result['session'].upper()}\")\n", - " \n", - " if signal_result['entry_signal'] != 0:\n", - " direction = \"LONG\" if signal_result['entry_signal'] == 1 else \"SHORT\"\n", - " print(f\"\\n✅ TRADING SIGNAL: {direction}\")\n", - " else:\n", - " print(f\"\\n⏸️ NO TRADING SIGNAL\")\n", - "else:\n", - " print(\"❌ Signal analysis failed\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 4: Complete Bot Status\n", - "print(\"\\n🧪 TEST 4: Complete Bot Status\")\n", - "print(\"=\"*50)\n", - "check_adaptive_bot_status()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 5: Trade Execution Test (DRY RUN)\n", - "print(\"\\n🧪 TEST 5: Trade Execution (DRY RUN)\")\n", - "print(\"=\"*50)\n", - "print(\"\\nTesting trading logic without actual order...\")\n", - "\n", - "# Dies führt die komplette Trading-Logik aus,\n", - "# führt aber nur dann wirklich einen Trade aus,\n", - "# wenn alle Bedingungen erfüllt sind\n", - "\n", - "test_result = execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)\n", - "\n", - "if test_result:\n", - " print(\"\\n✅ Trade würde ausgeführt!\")\n", - "else:\n", - " print(\"\\n⏸️ Kein Trade - Bedingungen nicht erfüllt\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 16. ✅ KORRIGIERT: Management Control Panel" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "scheduler.get_jobs()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Management Control Panel (fehlte in V1.6)\n", - "def show_adaptive_management_options():\n", - " \"\"\"\n", - " ✅ NEU: Management UI für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔧 V1.6 ADAPTIVE COMPLETE - MANAGEMENT CONTROL PANEL\")\n", - " print(\"=\"*70)\n", - " \n", - " print(\"\\n📊 MONITORING:\")\n", - " print(\" 1. check_adaptive_bot_status() - Complete Status\")\n", - " print(\" 2. get_position_summary() - Position Overview\")\n", - " print(\" 3. print_status_report() - Adaptive Rhythm Status\")\n", - " print(\" 4. analyze_performance_adaptive() - Performance Analysis\")\n", - " \n", - " print(\"\\n🎯 ANALYSIS:\")\n", - " print(\" 5. extended_top_down_v2_adaptive() - Signal Analysis\")\n", - " print(\" 6. rhythm_manager.calculate_optimal_interval() - Current Interval\")\n", - " \n", - " print(\"\\n💼 POSITION MANAGEMENT:\")\n", - " print(\" 7. close_existing_positions(force_close=True) - Close All Positions\")\n", - " \n", - " print(\"\\n🚀 TRADING:\")\n", - " print(\" 8. execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG) - Manual Trade\")\n", - " \n", - " print(\"\\n⚙️ SCHEDULER CONTROL:\")\n", - " print(\" 9. scheduler.get_jobs() - Show Active Jobs\")\n", - " print(\" 10. scheduler.pause() - Pause Scheduler\")\n", - " print(\" 11. scheduler.resume() - Resume Scheduler\")\n", - " print(\" 12. scheduler.shutdown() - Stop Scheduler\")\n", - " \n", - " print(\"\\n🔧 CONFIGURATION:\")\n", - " print(\" 13. ADAPTIVE_COMPLETE_CONFIG - View Config\")\n", - " print(\" 14. rhythm_manager.atr_thresholds - ATR Settings\")\n", - " \n", - " print(\"\\n📝 QUICK COMMANDS:\")\n", - " print(\" • Status: check_adaptive_bot_status()\")\n", - " print(\" • Close: close_existing_positions(symbol, strategy_name, force_close=True)\")\n", - " print(\" • Stop: scheduler.shutdown()\")\n", - " \n", - " print(\"=\"*70)\n", - "\n", - "\n", - "show_adaptive_management_options()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Optional: Close positions manually\n", - "# UNCOMMENT to use:\n", - "# close_existing_positions(symbol, strategy_name, force_close=True)\n", - "\n", - "print(\"💡 To close positions manually, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Optional: ATR-Schwellenwerte anpassen\n", - "# UNCOMMENT to use:\n", - "# rhythm_manager.atr_thresholds = {\n", - "# 'high': 18.0,\n", - "# 'medium': 10.0,\n", - "# 'low': 5.0\n", - "# }\n", - "# print(\"✅ ATR thresholds updated\")\n", - "\n", - "print(\"💡 To adjust ATR thresholds, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Scheduler Control\n", - "print(\"🎛️ SCHEDULER CONTROL\")\n", - "print(\"\\n💡 To pause trading:\")\n", - "print(\"scheduler.pause()\")\n", - "print(\"\\n💡 To resume trading:\")\n", - "print(\"scheduler.resume()\")\n", - "print(\"\\n💡 To stop completely:\")\n", - "print(\"scheduler.shutdown()\")\n", - "\n", - "# UNCOMMENT to stop:\n", - "# scheduler.shutdown()\n", - "# print(\"🔴 Trading Bot stopped\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 17. 📈 V1.6 ADAPTIVE COMPLETE - Summary" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "print(\"\\n\" + \"=\"*70)\n", - "print(\"📈 TRADINGBOT V1.6 ADAPTIVE COMPLETE - SUMMARY\")\n", - "print(\"=\"*70)\n", - "\n", - "print(\"\\n🎉 VERSION: V1.6 ADAPTIVE COMPLETE (CORRECTED & READY!)\")\n", - "\n", - "print(\"\\n✅ ALLE FEATURES INTEGRIERT:\")\n", - "\n", - "print(\"\\n🛡️ Position Control (aus V1.5):\")\n", - "print(\" • Maximal 1 Trade gleichzeitig\")\n", - "print(\" • check_existing_positions()\")\n", - "print(\" • get_position_summary()\")\n", - "print(\" • close_existing_positions() ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🚀 Relaxed Trading Parameters (aus V1.5):\")\n", - "print(\" • 10-20% niedrigere Confidence-Schwellen\")\n", - "print(\" • Disabled Pullback Entry\")\n", - "print(\" • Relaxed Signal-Quality-Filter\")\n", - "print(\" • Niedrigere Min Risk-Adjusted Strength (80)\")\n", - "print(\" • Fixed 2/4 Timeframe Alignment\")\n", - "\n", - "print(\"\\n⚡ Adaptive Rhythm (NEU in V1.6):\")\n", - "print(\" • Adaptive Intervalle: 5/15/30 Minuten\")\n", - "print(\" • Volatilitäts-basiert (ATR)\")\n", - "print(\" • Session-abhängig (Asian/London/NY/Overlap)\")\n", - "print(\" • Intelligente Entscheidungs-Matrix\")\n", - "\n", - "print(\"\\n📊 Monitoring & Management (aus V1.5, angepasst):\")\n", - "print(\" • Performance Logging\")\n", - "print(\" • Performance Analysis\")\n", - "print(\" • Complete Status Monitoring ✅ KORRIGIERT!\")\n", - "print(\" • Management Control Panel ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🤖 Automation:\")\n", - "print(\" • APScheduler Integration\")\n", - "print(\" • Adaptive Trading Checks (jede Minute)\")\n", - "print(\" • Status Reports (alle 30 Min)\")\n", - "\n", - "print(\"\\n🧪 Testing Suite (aus V1.5):\")\n", - "print(\" • Position Tests ✅ KORRIGIERT!\")\n", - "print(\" • Signal Analysis Tests ✅ KORRIGIERT!\")\n", - "print(\" • Adaptive Rhythm Tests\")\n", - "print(\" • Complete Status Tests ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n⚙️ Configuration:\")\n", - "print(\" • ADAPTIVE_COMPLETE_CONFIG ✅ KORRIGIERT!\")\n", - "print(\" • Zentrale Parameter-Verwaltung\")\n", - "\n", - "print(\"\\n🎯 VORTEILE VON V1.6 ADAPTIVE COMPLETE:\")\n", - "print(\" ✅ Maximale Sicherheit (Position Control)\")\n", - "print(\" ✅ Maximale Gelegenheiten (Relaxed Parameters)\")\n", - "print(\" ✅ Maximale Effizienz (Adaptive Rhythm)\")\n", - "print(\" ✅ Vollständige Kontrolle (Complete Management)\")\n", - "print(\" ✅ Production-Ready!\")\n", - "\n", - "print(\"\\n📊 TYPISCHER 24H-ZYKLUS:\")\n", - "print(\" 00:00-08:00 (Asian) → 15-30 min\")\n", - "print(\" 08:00-13:00 (London) → 5-30 min\")\n", - "print(\" 13:00-16:00 (Overlap) → 5-15 min 🔥\")\n", - "print(\" 16:00-21:00 (NY) → 5-30 min\")\n", - "print(\" 21:00-00:00 (After) → 15-30 min\")\n", - "\n", - "print(\"\\n💡 HAUPTFUNKTIONEN:\")\n", - "print(\" • Status: check_adaptive_bot_status()\")\n", - "print(\" • Analyze: extended_top_down_v2_adaptive()\")\n", - "print(\" • Trade: execute_trade_v2_adaptive()\")\n", - "print(\" • Manage: show_adaptive_management_options()\")\n", - "\n", - "print(\"\\n🏆 V1.6 ADAPTIVE COMPLETE - ALLE FUNKTIONEN INTEGRIERT!\")\n", - "print(\" 🛡️ Sicherheit + 🚀 Aggressivität + ⚡ Intelligenz\")\n", - "print(\" Production-Ready & Fully Tested! ✅\")\n", - "\n", - "print(\"\\n\" + \"=\"*70)\n", - "print(\"🎊 Ready for intelligent, safe, and adaptive trading!\")\n", - "print(\"=\"*70)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2025-11-26 11:37:00,014 - INFO - Running job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" (scheduled at 2025-11-26 11:37:00+01:00)\n", - "2025-11-26 11:37:00,014 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-11-26 11:37:00,014 - INFO - Job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" executed successfully\n", - "2025-11-26 11:37:00,102 - INFO - Running job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" (scheduled at 2025-11-26 11:37:00+01:00)\n", - "2025-11-26 11:37:00,103 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-11-26 11:37:00,103 - INFO - Job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" executed successfully\n" - ] - } - ], - "source": [ - "# Prüfe ob Filter aktiv ist\n", - "print(SESSION_WHITELIST_CONFIG)\n", - "\n", - "# Teste manuell verschiedene Sessions\n", - "for session in ['asian', 'london', 'overlap', 'ny']:\n", - " allowed, reason = is_session_allowed(session)\n", - " emoji = \"✅\" if allowed else \"❌\"\n", - " print(f\"{emoji} {session}: {reason}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} \ No newline at end of file diff --git a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_advanced_features.ipynb b/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_advanced_features.ipynb deleted file mode 100644 index e55534e..0000000 --- a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_advanced_features.ipynb +++ /dev/null @@ -1,2081 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# TradingBot V1.6 - Adaptive Complete Version 🚀🛡️⚡\n", - "\n", - "## 🆕 **NEU in V1.6: Adaptive Trading Rhythm**\n", - "- ⚡ **Adaptive Intervalle** - Automatische Anpassung: 5/15/30 Minuten\n", - "- 📊 **Volatilitäts-basiert** - ATR-gesteuerte Intervall-Wahl\n", - "- 🌍 **Session-abhängig** - Asian/London/NY/Overlap\n", - "- 🎯 **Intelligente Matrix** - Optimale Kombination aus Session + Volatilität\n", - "\n", - "## ✅ **Features aus V1.5 Complete Relaxed:**\n", - "- 🛡️ **Position Control System** - Maximal 1 Trade gleichzeitig\n", - "- 📊 **Performance Monitoring & Logging**\n", - "- 🤖 **APScheduler Integration** - Automatisierung\n", - "- 🔧 **Position Management Funktionen** - VOLLSTÄNDIG!\n", - "- 🚀 **Relaxed Parameter** - Niedrigere Schwellen für mehr Signale\n", - "- 🧪 **Umfassende Testing Suite**\n", - "- 🎛️ **Management Control Panel**\n", - "\n", - "## 🎯 **Adaptive Rhythm Schema:**\n", - "```\n", - "Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - "───────────┼──────────┼──────────────┼─────────────\n", - "Overlap │ 5min │ 15min │ 15min\n", - "London/NY │ 5min │ 15min │ 30min\n", - "Asian │ 15min │ 30min │ 30min\n", - "```\n", - "\n", - "## 🎉 **V1.6 COMPLETE - Das Beste aus beiden Welten:**\n", - "- ✅ Alle Funktionen aus V1.5\n", - "- ✅ Neue adaptive Features aus V1.6\n", - "- ✅ Production-Ready!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Imports und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Standard Imports\n", - "import pandas as pd\n", - "import numpy as np\n", - "import MetaTrader5 as mt\n", - "import pandas_ta as ta\n", - "from scipy.signal import savgol_filter, find_peaks\n", - "from sklearn.linear_model import LinearRegression\n", - "from tabulate import tabulate\n", - "from datetime import datetime, timedelta, time\n", - "import json\n", - "import keyring as kr\n", - "\n", - "# V1.6: Zusätzliche Imports für Adaptive Rhythm\n", - "import pytz\n", - "import logging\n", - "from apscheduler.schedulers.background import BackgroundScheduler\n", - "\n", - "# Setup Logging\n", - "logging.basicConfig(\n", - " level=logging.INFO,\n", - " format='%(asctime)s - %(levelname)s - %(message)s'\n", - ")\n", - "logger = logging.getLogger(__name__)\n", - "\n", - "print(\"✅ All imports successful - V1.6 Adaptive Complete (CORRECTED)\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INFRASTRUCTURE IMPORTS (V1.8)\n", - "# ==========================================\n", - "\n", - "from infrastructure_patch import (\n", - " TradingInfrastructure,\n", - " create_scheduled_reports\n", - ")\n", - "from trading_database import TradingDatabase\n", - "from telegram_notifier import TelegramNotifier\n", - "\n", - "print(\"✅ Infrastructure modules loaded\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. 🆕 Adaptive Rhythm Manager (NEU in V1.6)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "class AdaptiveRhythmManager:\n", - " \"\"\"\n", - " 🆕 V1.6 Feature: Adaptive Trading Rhythm\n", - " \n", - " Verwaltet adaptiven Trading-Rhythmus basierend auf:\n", - " - Marktvolatilität (ATR)\n", - " - Trading-Session (Asian/London/NY/Overlap)\n", - " - Marktregime\n", - " \"\"\"\n", - " \n", - " def __init__(self, symbol=\"XAUUSD\"):\n", - " self.symbol = symbol\n", - " self.current_interval = 5\n", - " \n", - " # Zeitintervalle in Minuten\n", - " self.intervals = {\n", - " 'fast': 5, # Hohe Volatilität, aktive Sessions\n", - " 'medium': 15, # Moderate Volatilität, Standard\n", - " 'slow': 30 # Niedrige Volatilität, ruhige Sessions\n", - " }\n", - " \n", - " # ATR-Schwellenwerte für XAUUSD (Gold)\n", - " self.atr_thresholds = {\n", - " 'high': 15.0, # Hohe Volatilität\n", - " 'medium': 8.0, # Moderate Volatilität\n", - " 'low': 5.0 # Niedrige Volatilität\n", - " }\n", - " \n", - " # Session-Zeiten (UTC)\n", - " self.sessions = {\n", - " 'asian': (time(0, 0), time(8, 0)), # 00:00-08:00 UTC\n", - " 'london': (time(8, 0), time(16, 0)), # 08:00-16:00 UTC\n", - " 'ny': (time(13, 0), time(21, 0)), # 13:00-21:00 UTC\n", - " 'overlap': (time(13, 0), time(16, 0)) # London-NY Overlap\n", - " }\n", - " \n", - " def get_current_session(self):\n", - " \"\"\"Ermittelt die aktuelle Trading-Session\"\"\"\n", - " now_utc = datetime.now(pytz.UTC).time()\n", - " \n", - " # Overlap hat höchste Priorität\n", - " if self.sessions['overlap'][0] <= now_utc <= self.sessions['overlap'][1]:\n", - " return 'overlap'\n", - " elif self.sessions['london'][0] <= now_utc < self.sessions['london'][1]:\n", - " return 'london'\n", - " elif self.sessions['ny'][0] <= now_utc < self.sessions['ny'][1]:\n", - " return 'ny'\n", - " return 'asian'\n", - " \n", - " def get_volatility_level(self, atr_value):\n", - " \"\"\"Klassifiziert die Volatilität basierend auf ATR\"\"\"\n", - " if atr_value >= self.atr_thresholds['high']:\n", - " return 'high'\n", - " elif atr_value >= self.atr_thresholds['medium']:\n", - " return 'medium'\n", - " return 'low'\n", - " \n", - " def get_market_data(self):\n", - " \"\"\"Hole Marktdaten für ATR-Analyse\"\"\"\n", - " try:\n", - " rates = mt.copy_rates_from_pos(self.symbol, mt.TIMEFRAME_H1, 0, 50)\n", - " if rates is None:\n", - " return None\n", - " \n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " logger.error(f\"Fehler beim Laden der Marktdaten: {e}\")\n", - " return None\n", - " \n", - " def calculate_optimal_interval(self):\n", - " \"\"\"Berechnet optimales Trading-Intervall\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is None:\n", - " return self.current_interval\n", - " \n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " optimal_interval = self._determine_interval(session, volatility)\n", - " \n", - " # Logge Änderungen\n", - " if optimal_interval != self.current_interval:\n", - " logger.info(f\"🔄 Rhythmus-Änderung: {self.current_interval}m → {optimal_interval}m\")\n", - " logger.info(f\" Session: {session}, Volatilität: {volatility} (ATR: {current_atr:.2f})\")\n", - " \n", - " self.current_interval = optimal_interval\n", - " return optimal_interval\n", - " \n", - " def _determine_interval(self, session, volatility):\n", - " \"\"\"\n", - " Intervall-Entscheidungs-Matrix:\n", - " \n", - " Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - " ───────────┼──────────┼──────────────┼─────────────\n", - " Overlap │ 5min │ 15min │ 15min\n", - " London/NY │ 5min │ 15min │ 30min\n", - " Asian │ 15min │ 30min │ 30min\n", - " \"\"\"\n", - " if session == 'overlap':\n", - " return self.intervals['fast'] if volatility == 'high' else self.intervals['medium']\n", - " elif session in ['london', 'ny']:\n", - " if volatility == 'high':\n", - " return self.intervals['fast']\n", - " elif volatility == 'medium':\n", - " return self.intervals['medium']\n", - " return self.intervals['slow']\n", - " else: # asian\n", - " return self.intervals['medium'] if volatility == 'high' else self.intervals['slow']\n", - " \n", - " def get_status_report(self):\n", - " \"\"\"Erstellt Status-Report\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is not None:\n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " else:\n", - " current_atr = 0\n", - " volatility = 'unknown'\n", - " \n", - " return f\"\"\"\n", - "╔════════════════════════════════════════════════════════╗\n", - "║ ADAPTIVE RHYTHM STATUS - {datetime.now().strftime('%H:%M:%S UTC')} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ Aktuelles Intervall: {self.current_interval:>2} Minuten ║\n", - "║ Trading Session: {session.upper():<15} ║\n", - "║ Volatilitätslevel: {volatility.upper():<15} ║\n", - "║ ATR (H1): {current_atr:>6.2f} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ INTERVALL-SCHEMA: ║\n", - "║ • Overlap (13-16 UTC): 5-15 Min (aktivste Phase) ║\n", - "║ • London/NY: 5-30 Min (volatilitätsabh.) ║\n", - "║ • Asian Session: 15-30 Min (ruhigere Phase) ║\n", - "╚════════════════════════════════════════════════════════╝\n", - "\"\"\"\n", - "\n", - "print(\"✅ Adaptive Rhythm Manager defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. MT5 Login und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# MT5 Login\n", - "mt.initialize()\n", - "login = 10800246\n", - "server = 'VantageInternational-Demo'\n", - "password = kr.get_password(server, str(login))\n", - "login_result = mt.login(login, password, server)\n", - "print(f\"Login successful: {login_result}\")\n", - "\n", - "# Trading Parameter\n", - "symbol = \"XAUUSD\"\n", - "strategy_name = \"TradingBot_V1.6\"\n", - "max_positions = 1\n", - "\n", - "print(f\"Symbol: {symbol}\")\n", - "print(f\"Strategy: {strategy_name}\")\n", - "print(f\"Max Positions: {max_positions}\")\n", - "print(f\"Version: V1.6 COMPLETE - Adaptive + Full Features! 🚀🛡️⚡\")\n", - "\n", - "# 🆕 Initialisiere Adaptive Rhythm Manager\n", - "rhythm_manager = AdaptiveRhythmManager(symbol)\n", - "print(\"\\n\" + rhythm_manager.get_status_report())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INITIALIZE INFRASTRUCTURE (V1.8)\n", - "# ==========================================\n", - "\n", - "print(\"🔧 Initializing Infrastructure...\")\n", - "\n", - "# Initialize Infrastructure\n", - "infra = TradingInfrastructure(\n", - " db_path=\"trading_bot.db\",\n", - " enable_telegram=True,\n", - " enable_database=True\n", - ")\n", - "\n", - "# Bot Started Notification\n", - "from session_filter_patch import SESSION_WHITELIST_CONFIG\n", - "\n", - "bot_config = {\n", - " 'version': 'V1.8',\n", - " 'enabled_sessions': SESSION_WHITELIST_CONFIG['enabled_sessions'],\n", - " 'base_confidence': SESSION_WHITELIST_CONFIG['base_confidence'],\n", - " 'max_risk_per_trade': SESSION_WHITELIST_CONFIG['max_risk_per_trade']\n", - "}\n", - "\n", - "infra.send_bot_started(bot_config)\n", - "\n", - "print(\"✅ Infrastructure ready!\")\n", - "print(f\" Database: {'✅' if infra.enable_database else '❌'}\")\n", - "print(f\" Telegram: {'✅' if infra.enable_telegram else '❌'}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# ADVANCED POSITION MANAGEMENT SETUP", - "# ==========================================", - "", - "from advanced_position_management import AdvancedPositionManager", - "", - "print(\"🎯 Initializing Advanced Position Management...\")", - "", - "# Initialize Manager with all features", - "adv_position_mgr = AdvancedPositionManager(", - " enable_adaptive_sizing=True, # ✅ Adaptive Position Sizing", - " enable_trailing_stop=True, # ✅ Trailing Stop-Loss", - " enable_partial_tp=True # ✅ Partial Take Profit", - ")", - "", - "print(\"✅ Advanced Position Management activated!\")", - "print(\" 📊 Adaptive Position Sizing: ACTIVE\")", - "print(\" • High Confidence (≥80%): 1.5x risk\")", - "print(\" • Medium Confidence (≥70%): 1.0x risk\")", - "print(\" • Low Confidence (<70%): 0.5x risk\")", - "print(\"\")", - "print(\" 📈 Trailing Stop-Loss: ACTIVE\")", - "print(\" • Break-Even at 50% progress to TP\")", - "print(\" • Lock 50% profit at 75% progress\")", - "print(\"\")", - "print(\" 🎯 Partial Take Profit: ACTIVE\")", - "print(\" • TP1 at 1.5R (close 50%)\")", - "print(\" • TP2 at 2.5R (let 50% run)\")", - "" - ] - }, - { - "cell_type": "code", - "metadata": {}, - "source": [ - "# ==========================================\n", - "# POSITION MONITOR SETUP (V1.8)\n", - "# ==========================================\n", - "\n", - "from position_monitor import PositionMonitor\n", - "\n", - "print(\"🔧 Initializing Position Monitor...\")\n", - "\n", - "# Create Position Monitor\n", - "position_monitor = PositionMonitor(infra.db, infra.telegram)\n", - "\n", - "print(\"✅ Position Monitor ready!\")\n", - "print(\" Will check for closed positions every minute\")\n", - "print(\" Closed trades will be automatically logged with:\")\n", - "print(\" • Exit price & time\")\n", - "print(\" • Profit/Loss calculation\")\n", - "print(\" • Exit reason (TP/SL/Manual)\")\n", - "print(\" • Telegram notification\")" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. 🛡️ Position Control Functions (VOLLSTÄNDIG!)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def check_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"\n", - " Überprüft ob bereits Positionen für das Symbol und die Strategie existieren\n", - " \"\"\"\n", - " try:\n", - " positions = mt.positions_get(symbol=symbol)\n", - " \n", - " if positions is None:\n", - " return False, {\"count\": 0, \"details\": []}\n", - " \n", - " strategy_positions = []\n", - " for pos in positions:\n", - " if strategy_name in pos.comment:\n", - " strategy_positions.append({\n", - " \"ticket\": pos.ticket,\n", - " \"type\": \"BUY\" if pos.type == 0 else \"SELL\",\n", - " \"volume\": pos.volume,\n", - " \"price_open\": pos.price_open,\n", - " \"profit\": pos.profit,\n", - " \"comment\": pos.comment,\n", - " \"time_open\": pd.to_datetime(pos.time, unit='s')\n", - " })\n", - " \n", - " has_position = len(strategy_positions) > 0\n", - " position_info = {\"count\": len(strategy_positions), \"details\": strategy_positions}\n", - " return has_position, position_info\n", - " \n", - " except Exception as e:\n", - " print(f\"Error checking positions: {e}\")\n", - " return False, {\"count\": 0, \"details\": []}\n", - "\n", - "\n", - "def get_position_summary(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"Position-Zusammenfassung\"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " print(f\"\\n📊 POSITION SUMMARY für {symbol} (V1.6 Adaptive Complete)\")\n", - " print(\"=\" * 60)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine aktiven Positionen - bereit für neuen Trade\")\n", - " return False\n", - " \n", - " print(f\"⚠️ {position_info['count']} aktive Position(en) gefunden:\")\n", - " for i, pos in enumerate(position_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\"\\n Position {i}:\")\n", - " print(f\" Ticket: {pos['ticket']}\")\n", - " print(f\" Typ: {pos['type']}\")\n", - " print(f\" Volumen: {pos['volume']}\")\n", - " print(f\" Eröffnungspreis: {pos['price_open']}\")\n", - " print(f\" Profit: {profit_emoji} {pos['profit']:.2f}\")\n", - " print(f\" Eröffnungszeit: {pos['time_open']}\")\n", - " \n", - " print(f\"\\n🛑 TRADING BLOCKIERT - Maximal {max_positions} Position erlaubt\")\n", - " return True\n", - "\n", - "\n", - "def close_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\", force_close=False):\n", - " \"\"\"\n", - " ✅ KORRIGIERT: Schließt bestehende Positionen (optional)\n", - " Diese Funktion fehlte in der ursprünglichen V1.6!\n", - " \"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine Positionen zum Schließen\")\n", - " return True\n", - " \n", - " if not force_close:\n", - " print(f\"⚠️ {position_info['count']} Position(en) gefunden. Verwende force_close=True zum Schließen.\")\n", - " return False\n", - " \n", - " print(f\"🔄 Schließe {position_info['count']} Position(en)...\")\n", - " \n", - " success_count = 0\n", - " for pos in position_info['details']:\n", - " try:\n", - " # Position schließen\n", - " close_request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": pos['volume'],\n", - " \"type\": mt.ORDER_TYPE_SELL if pos['type'] == \"BUY\" else mt.ORDER_TYPE_BUY,\n", - " \"position\": pos['ticket'],\n", - " \"price\": mt.symbol_info_tick(symbol).bid if pos['type'] == \"BUY\" else mt.symbol_info_tick(symbol).ask,\n", - " \"deviation\": 20,\n", - " \"magic\": 234000,\n", - " \"comment\": f\"Close {strategy_name}\",\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC,\n", - " }\n", - " \n", - " result = mt.order_send(close_request)\n", - " \n", - " if result.retcode == mt.TRADE_RETCODE_DONE:\n", - " print(f\"✅ Position {pos['ticket']} erfolgreich geschlossen\")\n", - " success_count += 1\n", - " else:\n", - " print(f\"❌ Fehler beim Schließen von Position {pos['ticket']}: {result.comment}\")\n", - " \n", - " except Exception as e:\n", - " print(f\"❌ Exception beim Schließen von Position {pos['ticket']}: {e}\")\n", - " \n", - " print(f\"📊 {success_count}/{len(position_info['details'])} Positionen erfolgreich geschlossen\")\n", - " return success_count == len(position_info['details'])\n", - "\n", - "\n", - "print(\"✅ Position Control functions defined (COMPLETE with close function!)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 5. Helper Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def get_rates(timeframe=\"h4\", count=200, symbol=\"XAUUSD\"):\n", - " \"\"\"Hole Kursdaten\"\"\"\n", - " timeframes_dict = {\n", - " \"m1\": mt.TIMEFRAME_M1, \"m5\": mt.TIMEFRAME_M5, \"m15\": mt.TIMEFRAME_M15,\n", - " \"m30\": mt.TIMEFRAME_M30, \"h1\": mt.TIMEFRAME_H1, \"h4\": mt.TIMEFRAME_H4, \n", - " \"d1\": mt.TIMEFRAME_D1\n", - " }\n", - " try:\n", - " rates = mt.copy_rates_from_pos(symbol, timeframes_dict[timeframe], 0, count)\n", - " if rates is None: \n", - " return None\n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " print(f\"Error getting rates: {e}\")\n", - " return None\n", - "\n", - "\n", - "def check_risk_limits(symbol, volume=None, order_type=\"buy\", max_risk_per_trade=0.01):\n", - " \"\"\"Risk Management\"\"\"\n", - " try:\n", - " account_info = mt.account_info()\n", - " if not account_info: \n", - " return False\n", - " balance, equity = account_info.balance, account_info.equity\n", - " if equity < balance * 0.8: \n", - " return False\n", - " return True\n", - " except: \n", - " return False\n", - "\n", - "\n", - "def market_order(symbol, volume, order_type, stoploss=0, take_profit=0, deviation=20):\n", - " \"\"\"Market Order Execution\"\"\"\n", - " try:\n", - " price_dict = {'buy': mt.symbol_info_tick(symbol).ask, 'sell': mt.symbol_info_tick(symbol).bid}\n", - " order_type_dict = {'buy': mt.ORDER_TYPE_BUY, 'sell': mt.ORDER_TYPE_SELL}\n", - " \n", - " request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": volume,\n", - " \"type\": order_type_dict[order_type],\n", - " \"price\": price_dict[order_type],\n", - " \"sl\": stoploss,\n", - " \"tp\": take_profit,\n", - " \"deviation\": deviation,\n", - " \"magic\": 234000,\n", - " \"comment\": strategy_name,\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC\n", - " }\n", - " return mt.order_send(request)\n", - " except Exception as e:\n", - " print(f\"Error in market order: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Helper functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6. Market Analysis Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def detect_market_regime(df, lookback=50):\n", - " \"\"\"Market Regime Detection\"\"\"\n", - " try:\n", - " adx_data = ta.adx(df['high'], df['low'], df['close'], length=14)\n", - " adx = adx_data['ADX_14'].iloc[-1] if adx_data is not None and 'ADX_14' in adx_data.columns else 25.0\n", - " \n", - " try:\n", - " bb = ta.bbands(df['close'], length=20)\n", - " if bb is not None and len(bb.columns) >= 3:\n", - " bb_cols = bb.columns.tolist()\n", - " bb_width = ((bb[bb_cols[0]] - bb[bb_cols[2]]) / bb[bb_cols[1]] * 100).iloc[-lookback:].mean()\n", - " else: \n", - " bb_width = 4.0\n", - " except: \n", - " bb_width = 4.0\n", - " \n", - " price_range = df['high'].iloc[-lookback:].max() - df['low'].iloc[-lookback:].min()\n", - " atr_avg = df['atr'].iloc[-lookback:].mean()\n", - " range_ratio = price_range / (atr_avg * lookback) if atr_avg > 0 else 1.0\n", - " vol_cluster = df['atr'].iloc[-10:].std() / df['atr'].iloc[-50:].mean() if len(df) >= 50 else 1.0\n", - " \n", - " if adx > 25 and range_ratio > 1.5:\n", - " regime, strength = 'trending', min(100, adx * 2)\n", - " elif vol_cluster > 1.5:\n", - " regime, strength = 'volatile', min(100, vol_cluster * 50)\n", - " else:\n", - " regime, strength = 'ranging', max(0, 100 - adx * 2)\n", - " \n", - " return {\n", - " 'regime': regime, 'strength': strength, 'adx': adx, \n", - " 'bb_width': bb_width, 'range_ratio': range_ratio, 'vol_cluster': vol_cluster\n", - " }\n", - " except Exception as e:\n", - " return {\n", - " 'regime': 'ranging', 'strength': 50, 'adx': 20, \n", - " 'bb_width': 4.0, 'range_ratio': 1.0, 'vol_cluster': 1.0\n", - " }\n", - "\n", - "\n", - "def calculate_adaptive_confidence_threshold_relaxed(regime_info, base_confidence=60):\n", - " \"\"\"\n", - " RELAXED Version: Niedrigere Schwellen für mehr Signale\n", - " \"\"\"\n", - " regime = regime_info['regime']\n", - " adx = regime_info['adx']\n", - " \n", - " if regime == 'trending':\n", - " if adx > 30:\n", - " return max(50, base_confidence - 20)\n", - " else:\n", - " return base_confidence - 15\n", - " elif regime == 'ranging':\n", - " return base_confidence + 10\n", - " elif regime == 'volatile':\n", - " return base_confidence + 15\n", - " \n", - " return base_confidence\n", - "\n", - "\n", - "def get_enhanced_trend(timeframe=\"H4\", lookback=150, symbol=\"XAUUSD\"):\n", - " \"\"\"Enhanced Trend Analysis\"\"\"\n", - " tf_map = {\"D1\": \"d1\", \"H4\": \"h4\", \"H1\": \"h1\", \"M30\": \"m30\", \"M15\": \"m15\", \"M5\": \"m5\"}\n", - " tf = tf_map.get(timeframe, timeframe.lower())\n", - " \n", - " try:\n", - " df = get_rates(tf, lookback, symbol)\n", - " if df is None or len(df) < 50: \n", - " return None\n", - " \n", - " df['close_smooth'] = savgol_filter(df['close'], min(15, len(df)//10), 3)\n", - " X = np.arange(len(df)).reshape(-1, 1)\n", - " y = df['close_smooth'].values\n", - " model = LinearRegression().fit(X, y)\n", - " slope = model.coef_[0]\n", - " \n", - " regime_info = detect_market_regime(df.iloc[-50:])\n", - " base_threshold = df['atr'].iloc[-1] * 0.0001\n", - " \n", - " if regime_info['regime'] == 'trending':\n", - " slope_threshold = base_threshold * 0.7\n", - " elif regime_info['regime'] == 'ranging':\n", - " slope_threshold = base_threshold * 1.5\n", - " else:\n", - " slope_threshold = base_threshold * 1.2\n", - " \n", - " trend = \"uptrend\" if slope > slope_threshold else \"downtrend\" if slope < -slope_threshold else \"sideways\"\n", - " trend_strength = abs(slope) / slope_threshold if slope_threshold > 0 else 0\n", - " \n", - " return {\n", - " \"trend\": trend, \"slope\": slope, \"slope_threshold\": slope_threshold,\n", - " \"trend_strength\": trend_strength, \"atr\": df['atr'].iloc[-1],\n", - " \"price\": df['close'].iloc[-1], \"regime_info\": regime_info\n", - " }\n", - " except Exception as e:\n", - " print(f\"Error in get_enhanced_trend: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Market analysis functions defined (with RELAXED thresholds)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 7. Extended Top-Down Analysis" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def extended_top_down_v2_adaptive(symbol=\"XAUUSD\", lookback=150):\n", - " \"\"\"\n", - " V1.6 Adaptive Complete Version:\n", - " - Position Control\n", - " - Relaxed Trading Logic\n", - " - Adaptive Rhythm Integration\n", - " \"\"\"\n", - " \n", - " timeframes = [\"D1\", \"H4\", \"H1\", \"M30\", \"M15\", \"M5\"]\n", - " trend_info = {}\n", - " \n", - " print(f\"🔍 Analyzing {symbol} with V1.6 ADAPTIVE COMPLETE parameters...\")\n", - " \n", - " # 1. Alle Timeframes analysieren\n", - " for tf in timeframes:\n", - " trend_info[tf] = get_enhanced_trend(tf, lookback, symbol)\n", - " if trend_info[tf] is None:\n", - " print(f\"⚠️ Keine Daten für {tf}\")\n", - " return None\n", - " \n", - " # 2. Market Regime aus H4 bestimmen\n", - " main_regime = trend_info[\"H4\"][\"regime_info\"]\n", - " \n", - " # 3. RELAXED Adaptive Confidence Threshold\n", - " adaptive_confidence_threshold = calculate_adaptive_confidence_threshold_relaxed(main_regime)\n", - " \n", - " # 4. Standard-Trend\n", - " d1_trend = trend_info[\"D1\"][\"trend\"]\n", - " h4_trend = trend_info[\"H4\"][\"trend\"]\n", - " d1_strength = trend_info[\"D1\"][\"trend_strength\"]\n", - " h4_strength = trend_info[\"H4\"][\"trend_strength\"]\n", - " \n", - " if d1_trend == h4_trend and d1_trend != \"sideways\":\n", - " standard_trend = d1_trend\n", - " standard_strength = (d1_strength * 0.6 + h4_strength * 0.4)\n", - " elif d1_strength > h4_strength * 1.5:\n", - " standard_trend = d1_trend\n", - " standard_strength = d1_strength * 0.8\n", - " elif h4_strength > d1_strength * 1.5:\n", - " standard_trend = h4_trend\n", - " standard_strength = h4_strength * 0.8\n", - " else:\n", - " standard_trend = \"sideways\"\n", - " standard_strength = 0\n", - " \n", - " # 5. RELAXED Fast-Trend\n", - " fast_timeframes = [\"H1\", \"M30\", \"M15\", \"M5\"]\n", - " fast_trends = [trend_info[tf][\"trend\"] for tf in fast_timeframes]\n", - " fast_strengths = [trend_info[tf][\"trend_strength\"] for tf in fast_timeframes]\n", - " \n", - " required_alignment = 2 # RELAXED: Immer 2 von 4\n", - " \n", - " trend_counts = {'uptrend': 0, 'downtrend': 0, 'sideways': 0}\n", - " weighted_strengths = {'uptrend': 0, 'downtrend': 0}\n", - " weights = [1.0, 0.8, 0.6, 0.4]\n", - " \n", - " for i, (trend, strength) in enumerate(zip(fast_trends, fast_strengths)):\n", - " trend_counts[trend] += 1\n", - " if trend != 'sideways':\n", - " weighted_strengths[trend] += strength * weights[i]\n", - " \n", - " max_count = max(trend_counts['uptrend'], trend_counts['downtrend'])\n", - " if max_count >= required_alignment:\n", - " if trend_counts['uptrend'] > trend_counts['downtrend']:\n", - " fast_trend = \"uptrend\"\n", - " elif trend_counts['downtrend'] > trend_counts['uptrend']:\n", - " fast_trend = \"downtrend\"\n", - " else:\n", - " fast_trend = \"uptrend\" if weighted_strengths['uptrend'] > weighted_strengths['downtrend'] else \"downtrend\"\n", - " else:\n", - " fast_trend = \"sideways\"\n", - " \n", - " # 6. Top-Down-Trend\n", - " if standard_trend == fast_trend and standard_trend != \"sideways\":\n", - " top_down_trend = standard_trend\n", - " combined_strength = (standard_strength + weighted_strengths.get(fast_trend, 0)) / 2\n", - " else:\n", - " top_down_trend = \"sideways\"\n", - " combined_strength = 0\n", - " \n", - " # 7. Enhanced Confidence\n", - " tf_weights = {\"D1\": 2.5, \"H4\": 2.0, \"H1\": 1.5, \"M30\": 1.0, \"M15\": 0.8, \"M5\": 0.6}\n", - " \n", - " weighted_matching = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"] \n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] == top_down_trend and trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " weighted_total = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"]\n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " confidence = round((weighted_matching / weighted_total) * 100, 2) if weighted_total > 0 else 0.0\n", - " \n", - " # 8. RELAXED Risk-Adjusted Signal Strength\n", - " atr = trend_info[\"M5\"][\"atr\"]\n", - " rrr = 2.5\n", - " risk_adjusted_strength = confidence * combined_strength * min(2.0, rrr)\n", - " \n", - " # 9. RELAXED Entry Signal\n", - " entry_signal = 0\n", - " signal_quality = \"none\"\n", - " min_strength = 80 # RELAXED: 80 statt 100\n", - " \n", - " if (top_down_trend != \"sideways\" and \n", - " confidence >= adaptive_confidence_threshold and\n", - " risk_adjusted_strength >= min_strength):\n", - " \n", - " entry_signal = 1 if top_down_trend == \"uptrend\" else -1\n", - " \n", - " # RELAXED Signal Quality\n", - " if confidence >= 80 and risk_adjusted_strength >= 130:\n", - " signal_quality = \"excellent\"\n", - " elif confidence >= 70 and risk_adjusted_strength >= 100:\n", - " signal_quality = \"good\"\n", - " else:\n", - " signal_quality = \"fair\"\n", - " \n", - " # 10. 🆕 Adaptive Rhythm Info\n", - " current_interval = rhythm_manager.current_interval\n", - " session = rhythm_manager.get_current_session()\n", - " \n", - " # 11. Debug Output\n", - " debug_data = []\n", - " for tf in timeframes:\n", - " info = trend_info[tf]\n", - " debug_data.append([\n", - " tf, info[\"trend\"], f\"{info['trend_strength']:.2f}\", \n", - " f\"{info['atr']:.4f}\", f\"{info['slope']:.6f}\", f\"{info['price']:.2f}\"\n", - " ])\n", - " \n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE Trend-Analyse für {symbol}\")\n", - " print(f\"⚡ Adaptive Interval: {current_interval} min | Session: {session.upper()}\")\n", - " print(f\"🎯 Market Regime: {main_regime['regime'].upper()} (Strength: {main_regime['strength']:.0f}%)\")\n", - " print(f\"🎚️ Adaptive Threshold: {adaptive_confidence_threshold}% (RELAXED)\")\n", - " print()\n", - " print(tabulate(debug_data, headers=[\"TF\", \"Trend\", \"Strength\", \"ATR\", \"Slope\", \"Price\"], tablefmt=\"psql\"))\n", - " print(f\"\\n➡️ Standard-Trend: {standard_trend} (Strength: {standard_strength:.2f})\")\n", - " print(f\"➡️ Fast-Trend: {fast_trend} (Required: {required_alignment}/4)\")\n", - " print(f\"➡️ Top-Down-Trend: {top_down_trend}\")\n", - " print(f\"➡️ Confidence: {confidence}% (Threshold: {adaptive_confidence_threshold}%)\")\n", - " print(f\"➡️ Risk-Adjusted Strength: {risk_adjusted_strength:.1f} (Min: {min_strength})\")\n", - " print(f\"➡️ Signal Quality: {signal_quality.upper()}\")\n", - " print(f\"\\n🚀 V1.6 Adaptive Complete: Full Features + Adaptive Rhythm\")\n", - " \n", - " return {\n", - " \"symbol\": symbol,\n", - " \"trend_info\": trend_info,\n", - " \"market_regime\": main_regime,\n", - " \"standard_trend\": standard_trend,\n", - " \"fast_trend\": fast_trend,\n", - " \"top_down_trend\": top_down_trend,\n", - " \"confidence\": confidence,\n", - " \"adaptive_threshold\": adaptive_confidence_threshold,\n", - " \"risk_adjusted_strength\": risk_adjusted_strength,\n", - " \"entry_signal\": entry_signal,\n", - " \"signal_quality\": signal_quality,\n", - " \"combined_strength\": combined_strength,\n", - " \"min_strength_used\": min_strength,\n", - " \"required_alignment\": required_alignment,\n", - " \"adaptive_interval\": current_interval,\n", - " \"session\": session\n", - " }\n", - "\n", - "\n", - "print(\"✅ V1.6 Adaptive Complete Top-Down Analysis defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 8. Entry Timing Optimization" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def check_pullback_entry(symbol, signal_info, timeframe=\"M5\"):\n", - " \"\"\"\n", - " Entry Timing Check - in Relaxed Version DISABLED per default\n", - " \"\"\"\n", - " if signal_info[\"entry_signal\"] == 0:\n", - " return False, \"No base signal\"\n", - " \n", - " try:\n", - " df = get_rates(timeframe.lower(), 50, symbol)\n", - " if df is None or len(df) < 20:\n", - " return False, \"Insufficient data\"\n", - " \n", - " df['ema21'] = df['close'].ewm(span=21).mean()\n", - " df['ema50'] = df['close'].ewm(span=50).mean()\n", - " \n", - " current_price = df['close'].iloc[-1]\n", - " ema21 = df['ema21'].iloc[-1]\n", - " ema50 = df['ema50'].iloc[-1]\n", - " signal_direction = signal_info[\"entry_signal\"]\n", - " \n", - " if signal_direction == 1: # Long\n", - " if current_price <= ema21 * 1.002 and ema21 > ema50:\n", - " return True, \"Pullback to EMA21 for Long\"\n", - " elif current_price <= ema21 * 0.998:\n", - " return True, \"Below EMA21 - Good Long Entry\"\n", - " elif signal_direction == -1: # Short\n", - " if current_price >= ema21 * 0.998 and ema21 < ema50:\n", - " return True, \"Pullback to EMA21 for Short\"\n", - " elif current_price >= ema21 * 1.002:\n", - " return True, \"Above EMA21 - Good Short Entry\"\n", - " \n", - " return False, \"Waiting for better entry timing\"\n", - " except Exception as e:\n", - " return True, \"Using immediate entry (fallback)\"\n", - "\n", - "\n", - "print(\"✅ Entry timing functions defined (DISABLED in Relaxed mode)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 9. Execute Trade Function" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def calculate_position_size(self, symbol, stop_loss_pips, max_risk_per_trade=0.02):\n", - " \"\"\"\n", - " Berechnet die Positionsgröße basierend auf Risiko\n", - " \"\"\"\n", - " account_info = mt.account_info()\n", - " if not account_info:\n", - " print(f\"⚠️ Keine Account-Info verfügbar, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " balance = account_info.balance\n", - " risk_amount = balance * max_risk_per_trade\n", - " \n", - " # Symbol-Info holen\n", - " symbol_info = mt.symbol_info(symbol)\n", - " if not symbol_info:\n", - " print(f\"⚠️ Keine Symbol-Info für {symbol}, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " # Pip-Wert berechnen\n", - " point = symbol_info.point\n", - " tick_value = symbol_info.trade_tick_value\n", - " tick_size = symbol_info.trade_tick_size\n", - " \n", - " # Volume berechnen\n", - " pip_value = (tick_value / tick_size) * point\n", - " volume = risk_amount / (stop_loss_pips * pip_value)\n", - " \n", - " # Auf erlaubte Volumenschritte runden\n", - " volume_min = symbol_info.volume_min\n", - " volume_max = symbol_info.volume_max\n", - " volume_step = symbol_info.volume_step\n", - " \n", - " volume = round(volume / volume_step) * volume_step\n", - " volume = max(volume_min, min(volume_max, volume))\n", - " \n", - " print(f\"💰 Position Sizing für {symbol}:\")\n", - " print(f\" Balance: ${balance:.2f}\")\n", - " print(f\" Risiko: ${risk_amount:.2f} ({max_risk_per_trade*100}%)\")\n", - " print(f\" Stop Loss: {stop_loss_pips:.2f} Pips\")\n", - " print(f\" Berechnetes Volume: {volume:.2f} Lots\")\n", - " \n", - " return volume" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#mt.symbol_info(symbol).volume_min\n", - "mt.symbol_info(symbol).volume_step" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def execute_trade_v2_adaptive(", - " symbol=\"XAUUSD\",", - " atr_mult=1.5,", - " base_confidence=60,", - " max_risk_per_trade=0.01,", - " risk_filter=True,", - " min_atr=0.0008,", - " use_pullback_entry=False, # DISABLED", - " max_positions=1,", - " strategy_name=\"TradingBot_V1.6\",", - " debug=True", - "):", - " \"\"\"", - " V1.6 Adaptive Complete Trade-Ausführung:", - " - Position Control", - " - Relaxed Parameter", - " - Adaptive Rhythm Integration", - " \"\"\"", - " ", - " # SCHRITT 1: POSITION CHECK", - " print(f\"\\n🔍 POSITION CHECK für {symbol} (V1.6 Adaptive Complete)\")", - " has_position, position_info = check_existing_positions(symbol, strategy_name)", - " ", - " if has_position and position_info['count'] >= max_positions:", - " if debug:", - " print(f\"🛑 TRADE BLOCKIERT: {position_info['count']}/{max_positions} Positionen aktiv\")", - " for pos in position_info['details']:", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"", - " print(f\" {pos['type']} @ {pos['price_open']} | {profit_emoji} {pos['profit']:.2f}\")", - " return None", - " ", - " print(f\"✅ Position-Check OK: {position_info['count']}/{max_positions}\")", - " ", - " # SCHRITT 2: Signal Analysis", - " signal_info = extended_top_down_v2_adaptive(symbol)", - " if signal_info is None:", - " print(\"❌ Signal-Analyse fehlgeschlagen\")", - " return None", - " ", - " entry_signal = signal_info[\"entry_signal\"]", - " confidence = signal_info[\"confidence\"]", - " adaptive_threshold = signal_info[\"adaptive_threshold\"]", - " signal_quality = signal_info[\"signal_quality\"]", - " market_regime = signal_info[\"market_regime\"]", - " ", - " # SCHRITT 3: Get Price/ATR", - " m5_info = signal_info[\"trend_info\"][\"M5\"]", - " price = m5_info[\"price\"]", - " atr = m5_info[\"atr\"]", - " ", - " # SCHRITT 4: Pre-checks", - " reason = \"\"", - " ", - " if confidence < adaptive_threshold:", - " reason = f\"Confidence {confidence}% < threshold {adaptive_threshold}%\"", - " elif entry_signal == 0:", - " reason = f\"No entry signal\"", - " elif price is None or atr is None:", - " reason = \"Price/ATR not available\"", - " elif risk_filter and atr < min_atr:", - " reason = f\"ATR {atr:.5f} < min_atr {min_atr}\"", - " else:", - " risk_ok = check_risk_limits(symbol, max_risk_per_trade=max_risk_per_trade)", - " if not risk_ok:", - " reason = \"Risk limits exceeded\"", - " ", - " # SCHRITT 5: Execute Trade", - " if not reason:", - " # Final Position Check", - " final_check, _ = check_existing_positions(symbol, strategy_name)", - " if final_check:", - " print(f\"🛑 Position wurde zwischen Checks eröffnet!\")", - " return None", - " ", - " # SL/TP Calculation", - " regime_mult = 1.0", - " if market_regime['regime'] == 'volatile':", - " regime_mult = 1.2", - " elif market_regime['regime'] == 'ranging':", - " regime_mult = 0.9", - " ", - " adjusted_atr_mult = atr_mult * regime_mult", - " ", - " if entry_signal == 1: # Long", - " stop_loss = price - adjusted_atr_mult * atr", - " take_profit = price + adjusted_atr_mult * atr * 2.5", - " else: # Short", - " stop_loss = price + adjusted_atr_mult * atr", - " take_profit = price - adjusted_atr_mult * atr * 2.5", - " ", - " # Position Sizing", - " account_info = mt.account_info()", - " if account_info:", - " balance = account_info.balance", - " risk_amount = balance * max_risk_per_trade", - " if symbol == \"XAUUSD\":", - " # 🎯 ADAPTIVE POSITION SIZING", - " if 'adv_position_mgr' in globals() and adv_position_mgr.adaptive_sizing:", - " volume = adv_position_mgr.adaptive_sizing.calculate_position_size(", - " confidence=confidence,", - " balance=balance,", - " stop_loss_distance=adjusted_atr_mult * atr * 10000, # Convert to pips", - " symbol=symbol", - " )", - " else:", - " volume = round(min(0.1, max(0.01, risk_amount / (adjusted_atr_mult * atr * 100))),2)", - " else:", - " volume = 0.01", - " else:", - " volume = 0.01", - " ", - " # Log Trade Info", - " print(f\"\\n🚀 V1.6 ADAPTIVE COMPLETE TRADE EXECUTION\")", - " print(f\"Direction: {'LONG' if entry_signal == 1 else 'SHORT'}\")", - " print(f\"Price: {price:.5f} | Volume: {volume:.2f}\")", - " print(f\"SL: {stop_loss:.5f} | TP: {take_profit:.5f}\")", - " print(f\"Confidence: {confidence}% | Quality: {signal_quality.upper()}\")", - " print(f\"Regime: {market_regime['regime'].upper()}\")", - " print(f\"Adaptive Interval: {signal_info['adaptive_interval']} min\")", - " print(f\"Session: {signal_info['session'].upper()}\")", - " ", - " # Execute", - " try:", - " order_result = market_order(", - " symbol=symbol,", - " volume=volume,", - " order_type=\"buy\" if entry_signal == 1 else \"sell\",", - " stoploss=stop_loss,", - " take_profit=take_profit", - " )", - " ", - " if order_result and order_result.retcode == mt.TRADE_RETCODE_DONE:", - " print(f\"✅ Trade erfolgreich! Ticket: {order_result.order}\")", - " ", - " # ==========================================", - " # LOG TRADE ENTRY (V1.8)", - " # ==========================================", - " try:", - " # Hole Position Info", - " positions = mt.positions_get(symbol=symbol)", - " if positions and infra:", - " position = positions[0]", - "", - " # Erstelle Trade Data", - " trade_data = {", - " 'ticket': position.ticket,", - " 'position_id': position.identifier,", - " 'symbol': symbol,", - " 'strategy_name': strategy_name,", - " 'type': 'BUY' if entry_signal == 1 else 'SELL',", - " 'volume': volume,", - " 'entry_price': position.price_open,", - " 'sl_price': position.sl,", - " 'tp_price': position.tp,", - " 'entry_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),", - " 'session': rhythm_manager.get_current_session(),", - " 'regime': market_regime['regime'],", - " 'quality': signal_quality,", - " 'confidence': confidence if 'confidence' in locals() else None,", - " 'timeframe_alignment': signal_info.get('required_alignment', 2),", - " 'risk_amount': risk_amount if 'risk_amount' in locals() else None,", - " 'risk_pct': max_risk_per_trade", - " }", - "", - " # Log to Database + Send Telegram", - " infra.log_trade_entry(trade_data)", - " logger.info(\"📱 Trade logged to DB + Telegram notification sent\")", - "", - " except Exception as e:", - " logger.error(f\"⚠️ Infrastructure logging failed: {e}\")", - " # ==========================================", - "", - "", - " # Verify & Log", - " new_check, new_info = check_existing_positions(symbol, strategy_name)", - " print(f\"📊 Positionen: {new_info['count']}\")", - " log_trade_performance_adaptive(signal_info, order_result)", - " else:", - " print(f\"❌ Trade failed: {order_result.comment if order_result else 'No result'}\")", - " ", - " return order_result", - " ", - " except Exception as e:", - " print(f\"❌ Execution failed: {e}\")", - " return None", - " ", - " else:", - " if debug:", - " print(f\"\\n⏸️ TRADE SKIPPED: {reason}\")", - " return None", - "", - "", - "print(\"✅ V1.6 Adaptive Complete Execute Trade defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 10. Performance Monitoring & Logging" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def log_trade_performance_adaptive(signal_info, order_result):\n", - " \"\"\"\n", - " Loggt Trade-Performance für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " trade_data = {\n", - " 'timestamp': datetime.now().isoformat(),\n", - " 'version': 'V1.6_Adaptive_Complete',\n", - " 'symbol': signal_info['symbol'],\n", - " 'entry_signal': signal_info['entry_signal'],\n", - " 'confidence': signal_info['confidence'],\n", - " 'adaptive_threshold': signal_info['adaptive_threshold'],\n", - " 'signal_quality': signal_info['signal_quality'],\n", - " 'market_regime': signal_info['market_regime']['regime'],\n", - " 'regime_strength': signal_info['market_regime']['strength'],\n", - " 'risk_adjusted_strength': signal_info['risk_adjusted_strength'],\n", - " 'adaptive_interval': signal_info['adaptive_interval'],\n", - " 'session': signal_info['session'],\n", - " 'relaxed_features': {\n", - " 'pullback_entry_disabled': True,\n", - " 'lower_confidence_threshold': True,\n", - " 'lower_min_strength': True,\n", - " 'fixed_tf_alignment': True\n", - " },\n", - " 'adaptive_features': {\n", - " 'adaptive_rhythm': True,\n", - " 'session_aware': True,\n", - " 'volatility_based': True\n", - " },\n", - " 'position_control_active': True,\n", - " 'order_result': str(order_result) if order_result else None\n", - " }\n", - " \n", - " try:\n", - " filename = f\"trade_performance_v16_{signal_info['symbol']}_{datetime.now().strftime('%Y%m')}.json\"\n", - " try:\n", - " with open(filename, 'r') as f: \n", - " data = json.load(f)\n", - " except FileNotFoundError: \n", - " data = []\n", - " data.append(trade_data)\n", - " with open(filename, 'w') as f: \n", - " json.dump(data, f, indent=2)\n", - " print(f\"📊 Performance logged to {filename}\")\n", - " except Exception as e:\n", - " print(f\"Warning: Could not log performance: {e}\")\n", - "\n", - "\n", - "def analyze_performance_adaptive(symbol=\"XAUUSD\", days_back=30):\n", - " \"\"\"\n", - " Analysiert Performance der V1.6 Adaptive Complete Version\n", - " \"\"\"\n", - " try:\n", - " filename = f\"trade_performance_v16_{symbol}_{datetime.now().strftime('%Y%m')}.json\"\n", - " \n", - " with open(filename, 'r') as f:\n", - " data = json.load(f)\n", - " \n", - " cutoff = datetime.now() - timedelta(days=days_back)\n", - " recent_trades = [\n", - " trade for trade in data \n", - " if datetime.fromisoformat(trade['timestamp']) > cutoff\n", - " ]\n", - " \n", - " if not recent_trades:\n", - " print(f\"No V1.6 trades in last {days_back} days\")\n", - " return\n", - " \n", - " total_trades = len(recent_trades)\n", - " \n", - " # Analysis by regime\n", - " by_regime = {}\n", - " for trade in recent_trades:\n", - " regime = trade['market_regime']\n", - " by_regime[regime] = by_regime.get(regime, 0) + 1\n", - " \n", - " # Analysis by interval\n", - " by_interval = {}\n", - " for trade in recent_trades:\n", - " interval = trade.get('adaptive_interval', 'unknown')\n", - " by_interval[interval] = by_interval.get(interval, 0) + 1\n", - " \n", - " # Analysis by session\n", - " by_session = {}\n", - " for trade in recent_trades:\n", - " session = trade.get('session', 'unknown')\n", - " by_session[session] = by_session.get(session, 0) + 1\n", - " \n", - " # Print results\n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE PERFORMANCE - Last {days_back} days\")\n", - " print(f\"Total Trades: {total_trades}\")\n", - " \n", - " print(f\"\\nBy Market Regime:\")\n", - " for regime, count in by_regime.items():\n", - " print(f\" {regime.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Adaptive Interval:\")\n", - " for interval, count in sorted(by_interval.items()):\n", - " print(f\" {interval} min: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Trading Session:\")\n", - " for session, count in by_session.items():\n", - " print(f\" {session.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " except Exception as e:\n", - " print(f\"Could not analyze performance: {e}\")\n", - "\n", - "\n", - "print(\"✅ Performance Monitoring functions defined (with adaptive features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 11. 🆕 Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# TRADING CHECK: SESSION FILTER + DRAWDOWN PROTECTION", - "# ==========================================", - "", - "from session_filter_patch import (", - " create_session_filtered_check,", - " SESSION_WHITELIST_CONFIG,", - " is_session_allowed", - ")", - "from drawdown_protection import create_protected_trading_check", - "", - "print(\"🔧 Setting up Trading Check...\")", - "", - "# Step 1: Create base session-filtered trading check", - "base_trading_check = create_session_filtered_check(", - " rhythm_manager=rhythm_manager,", - " execute_func=execute_trade_v2_adaptive,", - " symbol=symbol,", - " strategy_name=strategy_name,", - " max_positions=max_positions,", - " logger=logger,", - " datetime=datetime", - ")", - "", - "print(\"✅ Session Filter aktiviert!\")", - "print(\" Deaktivierte Sessions:\")", - "for session, enabled in SESSION_WHITELIST_CONFIG['enabled_sessions'].items():", - " status = \"✅ AKTIV\" if enabled else \"❌ DEAKTIVIERT\"", - " print(f\" • {session.upper():8s}: {status}\")", - "", - "# Step 2: Wrap with Drawdown Protection", - "adaptive_trading_check = create_protected_trading_check(infra, base_trading_check)", - "drawdown_protection = adaptive_trading_check.protection", - "", - "print(\"\\n🛡️ Drawdown Protection aktiviert!\")", - "print(f\" • Daily Loss Limit: ${drawdown_protection.max_daily_loss}\")", - "print(f\" • Weekly Loss Limit: ${drawdown_protection.max_weekly_loss}\")", - "print(f\" • Monthly Loss Limit: ${drawdown_protection.max_monthly_loss}\")", - "print(f\" • Max Consecutive Losses: {drawdown_protection.max_consecutive_losses}\")", - "print(f\" • Cooldown: {drawdown_protection.cooldown_hours}h\")", - "", - "print(\"\\n✅ Trading Check ist jetzt vollständig geschützt!\")", - "print(\" 📊 Session Filter: Aktiv\")", - "print(\" 🛡️ Drawdown Protection: Aktiv\")", - "" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# def adaptive_trading_check():\n", - "# \"\"\"\n", - "# 🆕 V1.6: Adaptive Trading Check\n", - "# Prüft basierend auf optimalem Intervall ob gehandelt werden soll\n", - "# \"\"\"\n", - "# try:\n", - "# optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "# current_minute = datetime.now().minute\n", - " \n", - "# # Trading nur zu berechneten Zeitpunkten\n", - "# if current_minute % optimal_interval == 0:\n", - "# logger.info(f\"\\n⏰ {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} - ADAPTIVE Check\")\n", - "# logger.info(f\"Intervall: {optimal_interval} min\")\n", - " \n", - "# # Führe Trading aus\n", - "# execute_trade_v2_adaptive(\n", - "# symbol=symbol,\n", - "# strategy_name=strategy_name,\n", - "# max_positions=max_positions\n", - "# )\n", - " \n", - "# except Exception as e:\n", - "# logger.error(f\"Fehler im Adaptive Trading Check: {e}\")\n", - "\n", - "\n", - "def print_status_report():\n", - " \"\"\"Status-Report\"\"\"\n", - " print(rhythm_manager.get_status_report())\n", - "\n", - "\n", - "# print(\"✅ Adaptive Scheduler functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 12. ✅ KORRIGIERT: Trading Configuration" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Zentrale Konfiguration (fehlte in ursprünglicher V1.6)\n", - "ADAPTIVE_COMPLETE_CONFIG = {\n", - " 'symbol': symbol,\n", - " 'atr_mult': 1.5,\n", - " 'base_confidence': 60, # RELAXED\n", - " 'max_risk_per_trade': 0.01,\n", - " 'risk_filter': True,\n", - " 'min_atr': 0.0008, # RELAXED\n", - " 'use_pullback_entry': False, # DISABLED\n", - " 'max_positions': max_positions,\n", - " 'strategy_name': strategy_name,\n", - " 'debug': True\n", - "}\n", - "\n", - "print(\"⚙️ V1.6 Adaptive Complete Configuration:\")\n", - "print(\"\\n🛡️ Position Control:\")\n", - "print(f\" Max Positions: {ADAPTIVE_COMPLETE_CONFIG['max_positions']}\")\n", - "print(f\" Strategy: {ADAPTIVE_COMPLETE_CONFIG['strategy_name']}\")\n", - "\n", - "print(\"\\n🚀 Relaxed Parameters:\")\n", - "print(f\" Base Confidence: {ADAPTIVE_COMPLETE_CONFIG['base_confidence']}%\")\n", - "print(f\" Min ATR: {ADAPTIVE_COMPLETE_CONFIG['min_atr']}\")\n", - "print(f\" Pullback Entry: {ADAPTIVE_COMPLETE_CONFIG['use_pullback_entry']}\")\n", - "\n", - "print(\"\\n⚡ Adaptive Features:\")\n", - "print(f\" Dynamic Intervals: 5/15/30 min\")\n", - "print(f\" Session-aware: Yes\")\n", - "print(f\" Volatility-based: Yes\")\n", - "\n", - "print(\"\\n✅ Configuration complete!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 13. ✅ KORRIGIERT: Status & Monitoring Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Umfassendes Status Monitoring (fehlte in V1.6)\n", - "def check_adaptive_bot_status():\n", - " \"\"\"\n", - " ✅ NEU: Kombiniertes Status-Check für V1.6 Adaptive Complete\n", - " Kombiniert Position Control + Adaptive Rhythm Status\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔍 V1.6 ADAPTIVE COMPLETE BOT STATUS\")\n", - " print(\"=\"*70)\n", - " \n", - " # System Status\n", - " print(\"\\n📡 SYSTEM STATUS:\")\n", - " print(f\" MT5 Connection: {'✅' if mt.terminal_info() else '❌'}\")\n", - " print(f\" Scheduler Running: {'✅' if scheduler.running else '❌'}\")\n", - " print(f\" Active Jobs: {len(scheduler.get_jobs())}\")\n", - " \n", - " # Adaptive Rhythm Status\n", - " print(\"\\n⚡ ADAPTIVE RHYTHM:\")\n", - " optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - " session = rhythm_manager.get_current_session()\n", - " df = rhythm_manager.get_market_data()\n", - " \n", - " if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\" Current Interval: {optimal_interval} min\")\n", - " print(f\" Trading Session: {session.upper()}\")\n", - " print(f\" ATR (H1): {atr:.2f}\")\n", - " print(f\" Volatility: {vol_level.upper()}\")\n", - " else:\n", - " print(\" ⚠️ Could not fetch market data\")\n", - " \n", - " # Position Status\n", - " print(\"\\n🛡️ POSITION CONTROL:\")\n", - " has_pos, pos_info = check_existing_positions(symbol, strategy_name)\n", - " print(f\" Active Positions: {pos_info['count']}/{max_positions}\")\n", - " print(f\" Trading Status: {'🛑 BLOCKED' if has_pos else '✅ READY'}\")\n", - " \n", - " if has_pos:\n", - " for i, pos in enumerate(pos_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\" Position {i}: {pos['type']} | {profit_emoji} {pos['profit']:.2f}\")\n", - " \n", - " # Signal Status\n", - " print(\"\\n📊 CURRENT SIGNAL:\")\n", - " try:\n", - " signal_info = extended_top_down_v2_adaptive(symbol)\n", - " if signal_info:\n", - " signal_dir = \"LONG\" if signal_info['entry_signal'] == 1 else \"SHORT\" if signal_info['entry_signal'] == -1 else \"NONE\"\n", - " print(f\" Signal: {signal_dir}\")\n", - " print(f\" Confidence: {signal_info['confidence']}%\")\n", - " print(f\" Threshold: {signal_info['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_info['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_info['market_regime']['regime'].upper()}\")\n", - " \n", - " would_trade = (signal_info['entry_signal'] != 0 and not has_pos)\n", - " print(f\" Would Trade: {'✅ YES' if would_trade else '❌ NO'}\")\n", - " else:\n", - " print(\" ⚠️ Signal analysis failed\")\n", - " except Exception as e:\n", - " print(f\" ❌ Error: {e}\")\n", - " \n", - " # Version Info\n", - " print(\"\\n🎉 VERSION INFO:\")\n", - " print(\" Version: V1.6 Adaptive Complete (CORRECTED)\")\n", - " print(\" Features: Position Control + Relaxed + Adaptive Rhythm\")\n", - " print(\" Status: Production-Ready ✅\")\n", - " print(\"=\"*70)\n", - "\n", - "\n", - "print(\"✅ Status monitoring function defined (COMPLETE with all features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 14. 🚀 Start Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Setup Scheduler", - "scheduler = BackgroundScheduler()", - "", - "# ADAPTIVE: Prüft jede Minute, handelt zu optimalen Zeitpunkten", - "scheduler.add_job(", - " func=adaptive_trading_check,", - " trigger='cron',", - " minute='*',", - " id='adaptive_trading_check'", - ")", - "", - "# Status-Report alle 30 Minuten", - "scheduler.add_job(", - " func=print_status_report,", - " trigger='cron',", - " minute='0,30',", - " id='status_report'", - ")", - "", - "# ==========================================", - "# SCHEDULED REPORTS (V1.8)", - "# ==========================================", - "", - "# Add daily & weekly reports", - "create_scheduled_reports(infra, scheduler)", - "", - "print(\"✅ Scheduled reports added:\")", - "print(\" 📊 Daily report: 22:00 UTC\")", - "print(\" 📈 Weekly report: Sunday 23:00 UTC\")", - "", - "", - "# ==========================================", - "# POSITION MONITOR JOB (V1.8)", - "# ==========================================", - "", - "# Add Position Monitor (checks every minute for closed positions)", - "scheduler.add_job(", - " func=position_monitor.check_open_positions,", - " trigger='interval',", - " minutes=1,", - " id='position_monitor'", - ")", - "", - "print(\"✅ Position Monitor job added:\")", - "print(\" 📊 Checks every minute for closed positions\")", - "", - "# ==========================================", - "", - "# ==========================================", - "", - "# Start scheduler", - "", - "# ==========================================", - "# ADVANCED POSITION MANAGEMENT JOB", - "# ==========================================", - "", - "# Trailing Stop + Partial TP Check (every minute)", - "scheduler.add_job(", - " func=lambda: adv_position_mgr.check_and_update_positions(symbol),", - " trigger='interval',", - " minutes=1,", - " id='advanced_position_management'", - ")", - "", - "print(\"✅ Advanced Position Management job added:\")", - "print(\" 📈 Checks for Trailing Stop updates every minute\")", - "print(\" 🎯 Checks for Partial TP triggers every minute\")", - "", - "scheduler.start()", - "logger.info(\"✅ Scheduler started with session filter + reports\")", - "", - "", - "# Starte Scheduler", - "#", - "# ==========================================", - "# ADVANCED POSITION MANAGEMENT JOB", - "# ==========================================", - "", - "# Trailing Stop + Partial TP Check (every minute)", - "scheduler.add_job(", - " func=lambda: adv_position_mgr.check_and_update_positions(symbol),", - " trigger='interval',", - " minutes=1,", - " id='advanced_position_management'", - ")", - "", - "print(\"✅ Advanced Position Management job added:\")", - "print(\" 📈 Checks for Trailing Stop updates every minute\")", - "print(\" 🎯 Checks for Partial TP triggers every minute\")", - "", - "scheduler.start()", - "", - "print(\"\\n\" + \"=\"*70)", - "print(\"🚀 TradingBot V1.6 ADAPTIVE COMPLETE - Scheduler gestartet!\")", - "print(\"=\"*70)", - "print(\"\\n🎯 Features aktiv:\")", - "print(\" ✅ Position Control System (Max 1 Position)\")", - "print(\" ✅ Relaxed Trading Parameters\")", - "print(\" ✅ ADAPTIVE RHYTHM (5/15/30 Min)\")", - "print(\" ✅ Volatilitäts-basiert (ATR)\")", - "print(\" ✅ Session-abhängig (Asian/London/NY/Overlap)\")", - "print(\" ✅ Complete Position Management\")", - "print(\" ✅ Umfassendes Status Monitoring\")", - "print(\"\\n⚡ Adaptive Intervall-Matrix:\")", - "print(\" • Overlap (13-16 UTC): 5-15min\")", - "print(\" • London/NY: 5-30min\")", - "print(\" • Asian: 15-30min\")", - "print(\"\\n📊 Status-Reports alle 30 Minuten\")", - "print(\"🔍 Trading-Checks zu adaptiven Zeitpunkten\")", - "print(\"=\"*70)", - "", - "# Zeige initialen Status", - "check_adaptive_bot_status()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 15. ✅ KORRIGIERT: Testing Suite" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Umfassende Testing Suite (fehlte in V1.6)\n", - "\n", - "# Test 1: Position Summary\n", - "print(\"🧪 TEST 1: Position Check\")\n", - "print(\"=\"*50)\n", - "get_position_summary(symbol, strategy_name)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 2: Adaptive Rhythm Status\n", - "print(\"\\n🧪 TEST 2: Adaptive Rhythm\")\n", - "print(\"=\"*50)\n", - "print_status_report()\n", - "\n", - "# Test Details\n", - "optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "session = rhythm_manager.get_current_session()\n", - "df = rhythm_manager.get_market_data()\n", - "\n", - "if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\"\\nDetails:\")\n", - " print(f\" Optimal Interval: {optimal_interval} min\")\n", - " print(f\" Session: {session}\")\n", - " print(f\" ATR: {atr:.2f}\")\n", - " print(f\" Volatility Level: {vol_level}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 3: Signal Analysis\n", - "print(\"\\n🧪 TEST 3: Signal Analysis\")\n", - "print(\"=\"*50)\n", - "\n", - "signal_result = extended_top_down_v2_adaptive(symbol)\n", - "\n", - "if signal_result:\n", - " print(f\"\\n🎯 SIGNAL SUMMARY:\")\n", - " print(f\" Entry Signal: {signal_result['entry_signal']}\")\n", - " print(f\" Confidence: {signal_result['confidence']}%\")\n", - " print(f\" Threshold: {signal_result['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_result['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_result['market_regime']['regime'].upper()}\")\n", - " print(f\" Adaptive Interval: {signal_result['adaptive_interval']} min\")\n", - " print(f\" Session: {signal_result['session'].upper()}\")\n", - " \n", - " if signal_result['entry_signal'] != 0:\n", - " direction = \"LONG\" if signal_result['entry_signal'] == 1 else \"SHORT\"\n", - " print(f\"\\n✅ TRADING SIGNAL: {direction}\")\n", - " else:\n", - " print(f\"\\n⏸️ NO TRADING SIGNAL\")\n", - "else:\n", - " print(\"❌ Signal analysis failed\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 4: Complete Bot Status\n", - "print(\"\\n🧪 TEST 4: Complete Bot Status\")\n", - "print(\"=\"*50)\n", - "check_adaptive_bot_status()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 5: Trade Execution Test (DRY RUN)\n", - "print(\"\\n🧪 TEST 5: Trade Execution (DRY RUN)\")\n", - "print(\"=\"*50)\n", - "print(\"\\nTesting trading logic without actual order...\")\n", - "\n", - "# Dies führt die komplette Trading-Logik aus,\n", - "# führt aber nur dann wirklich einen Trade aus,\n", - "# wenn alle Bedingungen erfüllt sind\n", - "\n", - "test_result = execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)\n", - "\n", - "if test_result:\n", - " print(\"\\n✅ Trade würde ausgeführt!\")\n", - "else:\n", - " print(\"\\n⏸️ Kein Trade - Bedingungen nicht erfüllt\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 16. ✅ KORRIGIERT: Management Control Panel" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "scheduler.get_jobs()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Management Control Panel (fehlte in V1.6)\n", - "def show_adaptive_management_options():\n", - " \"\"\"\n", - " ✅ NEU: Management UI für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔧 V1.6 ADAPTIVE COMPLETE - MANAGEMENT CONTROL PANEL\")\n", - " print(\"=\"*70)\n", - " \n", - " print(\"\\n📊 MONITORING:\")\n", - " print(\" 1. check_adaptive_bot_status() - Complete Status\")\n", - " print(\" 2. get_position_summary() - Position Overview\")\n", - " print(\" 3. print_status_report() - Adaptive Rhythm Status\")\n", - " print(\" 4. analyze_performance_adaptive() - Performance Analysis\")\n", - " \n", - " print(\"\\n🎯 ANALYSIS:\")\n", - " print(\" 5. extended_top_down_v2_adaptive() - Signal Analysis\")\n", - " print(\" 6. rhythm_manager.calculate_optimal_interval() - Current Interval\")\n", - " \n", - " print(\"\\n💼 POSITION MANAGEMENT:\")\n", - " print(\" 7. close_existing_positions(force_close=True) - Close All Positions\")\n", - " \n", - " print(\"\\n🚀 TRADING:\")\n", - " print(\" 8. execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG) - Manual Trade\")\n", - " \n", - " print(\"\\n⚙️ SCHEDULER CONTROL:\")\n", - " print(\" 9. scheduler.get_jobs() - Show Active Jobs\")\n", - " print(\" 10. scheduler.pause() - Pause Scheduler\")\n", - " print(\" 11. scheduler.resume() - Resume Scheduler\")\n", - " print(\" 12. scheduler.shutdown() - Stop Scheduler\")\n", - " \n", - " print(\"\\n🔧 CONFIGURATION:\")\n", - " print(\" 13. ADAPTIVE_COMPLETE_CONFIG - View Config\")\n", - " print(\" 14. rhythm_manager.atr_thresholds - ATR Settings\")\n", - " \n", - " print(\"\\n📝 QUICK COMMANDS:\")\n", - " print(\" • Status: check_adaptive_bot_status()\")\n", - " print(\" • Close: close_existing_positions(symbol, strategy_name, force_close=True)\")\n", - " print(\" • Stop: scheduler.shutdown()\")\n", - " \n", - " print(\"=\"*70)\n", - "\n", - "\n", - "show_adaptive_management_options()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Optional: Close positions manually\n", - "# UNCOMMENT to use:\n", - "# close_existing_positions(symbol, strategy_name, force_close=True)\n", - "\n", - "print(\"💡 To close positions manually, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Optional: ATR-Schwellenwerte anpassen\n", - "# UNCOMMENT to use:\n", - "# rhythm_manager.atr_thresholds = {\n", - "# 'high': 18.0,\n", - "# 'medium': 10.0,\n", - "# 'low': 5.0\n", - "# }\n", - "# print(\"✅ ATR thresholds updated\")\n", - "\n", - "print(\"💡 To adjust ATR thresholds, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Scheduler Control\n", - "print(\"🎛️ SCHEDULER CONTROL\")\n", - "print(\"\\n💡 To pause trading:\")\n", - "print(\"scheduler.pause()\")\n", - "print(\"\\n💡 To resume trading:\")\n", - "print(\"scheduler.resume()\")\n", - "print(\"\\n💡 To stop completely:\")\n", - "print(\"scheduler.shutdown()\")\n", - "\n", - "# UNCOMMENT to stop:\n", - "# scheduler.shutdown()\n", - "# print(\"🔴 Trading Bot stopped\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 17. 📈 V1.6 ADAPTIVE COMPLETE - Summary" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "print(\"\\n\" + \"=\"*70)\n", - "print(\"📈 TRADINGBOT V1.6 ADAPTIVE COMPLETE - SUMMARY\")\n", - "print(\"=\"*70)\n", - "\n", - "print(\"\\n🎉 VERSION: V1.6 ADAPTIVE COMPLETE (CORRECTED & READY!)\")\n", - "\n", - "print(\"\\n✅ ALLE FEATURES INTEGRIERT:\")\n", - "\n", - "print(\"\\n🛡️ Position Control (aus V1.5):\")\n", - "print(\" • Maximal 1 Trade gleichzeitig\")\n", - "print(\" • check_existing_positions()\")\n", - "print(\" • get_position_summary()\")\n", - "print(\" • close_existing_positions() ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🚀 Relaxed Trading Parameters (aus V1.5):\")\n", - "print(\" • 10-20% niedrigere Confidence-Schwellen\")\n", - "print(\" • Disabled Pullback Entry\")\n", - "print(\" • Relaxed Signal-Quality-Filter\")\n", - "print(\" • Niedrigere Min Risk-Adjusted Strength (80)\")\n", - "print(\" • Fixed 2/4 Timeframe Alignment\")\n", - "\n", - "print(\"\\n⚡ Adaptive Rhythm (NEU in V1.6):\")\n", - "print(\" • Adaptive Intervalle: 5/15/30 Minuten\")\n", - "print(\" • Volatilitäts-basiert (ATR)\")\n", - "print(\" • Session-abhängig (Asian/London/NY/Overlap)\")\n", - "print(\" • Intelligente Entscheidungs-Matrix\")\n", - "\n", - "print(\"\\n📊 Monitoring & Management (aus V1.5, angepasst):\")\n", - "print(\" • Performance Logging\")\n", - "print(\" • Performance Analysis\")\n", - "print(\" • Complete Status Monitoring ✅ KORRIGIERT!\")\n", - "print(\" • Management Control Panel ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🤖 Automation:\")\n", - "print(\" • APScheduler Integration\")\n", - "print(\" • Adaptive Trading Checks (jede Minute)\")\n", - "print(\" • Status Reports (alle 30 Min)\")\n", - "\n", - "print(\"\\n🧪 Testing Suite (aus V1.5):\")\n", - "print(\" • Position Tests ✅ KORRIGIERT!\")\n", - "print(\" • Signal Analysis Tests ✅ KORRIGIERT!\")\n", - "print(\" • Adaptive Rhythm Tests\")\n", - "print(\" • Complete Status Tests ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n⚙️ Configuration:\")\n", - "print(\" • ADAPTIVE_COMPLETE_CONFIG ✅ KORRIGIERT!\")\n", - "print(\" • Zentrale Parameter-Verwaltung\")\n", - "\n", - "print(\"\\n🎯 VORTEILE VON V1.6 ADAPTIVE COMPLETE:\")\n", - "print(\" ✅ Maximale Sicherheit (Position Control)\")\n", - "print(\" ✅ Maximale Gelegenheiten (Relaxed Parameters)\")\n", - "print(\" ✅ Maximale Effizienz (Adaptive Rhythm)\")\n", - "print(\" ✅ Vollständige Kontrolle (Complete Management)\")\n", - "print(\" ✅ Production-Ready!\")\n", - "\n", - "print(\"\\n📊 TYPISCHER 24H-ZYKLUS:\")\n", - "print(\" 00:00-08:00 (Asian) → 15-30 min\")\n", - "print(\" 08:00-13:00 (London) → 5-30 min\")\n", - "print(\" 13:00-16:00 (Overlap) → 5-15 min 🔥\")\n", - "print(\" 16:00-21:00 (NY) → 5-30 min\")\n", - "print(\" 21:00-00:00 (After) → 15-30 min\")\n", - "\n", - "print(\"\\n💡 HAUPTFUNKTIONEN:\")\n", - "print(\" • Status: check_adaptive_bot_status()\")\n", - "print(\" • Analyze: extended_top_down_v2_adaptive()\")\n", - "print(\" • Trade: execute_trade_v2_adaptive()\")\n", - "print(\" • Manage: show_adaptive_management_options()\")\n", - "\n", - "print(\"\\n🏆 V1.6 ADAPTIVE COMPLETE - ALLE FUNKTIONEN INTEGRIERT!\")\n", - "print(\" 🛡️ Sicherheit + 🚀 Aggressivität + ⚡ Intelligenz\")\n", - "print(\" Production-Ready & Fully Tested! ✅\")\n", - "\n", - "print(\"\\n\" + \"=\"*70)\n", - "print(\"🎊 Ready for intelligent, safe, and adaptive trading!\")\n", - "print(\"=\"*70)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2025-11-26 11:37:00,014 - INFO - Running job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" (scheduled at 2025-11-26 11:37:00+01:00)\n", - "2025-11-26 11:37:00,014 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-11-26 11:37:00,014 - INFO - Job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" executed successfully\n", - "2025-11-26 11:37:00,102 - INFO - Running job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" (scheduled at 2025-11-26 11:37:00+01:00)\n", - "2025-11-26 11:37:00,103 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-11-26 11:37:00,103 - INFO - Job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" executed successfully\n" - ] - } - ], - "source": [ - "# Prüfe ob Filter aktiv ist\n", - "print(SESSION_WHITELIST_CONFIG)\n", - "\n", - "# Teste manuell verschiedene Sessions\n", - "for session in ['asian', 'london', 'overlap', 'ny']:\n", - " allowed, reason = is_session_allowed(session)\n", - " emoji = \"✅\" if allowed else \"❌\"\n", - " print(f\"{emoji} {session}: {reason}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} \ No newline at end of file diff --git a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_drawdown_v2.ipynb b/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_drawdown_v2.ipynb deleted file mode 100644 index 40eb415..0000000 --- a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_drawdown_v2.ipynb +++ /dev/null @@ -1,2001 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# TradingBot V1.6 - Adaptive Complete Version 🚀🛡️⚡\n", - "\n", - "## 🆕 **NEU in V1.6: Adaptive Trading Rhythm**\n", - "- ⚡ **Adaptive Intervalle** - Automatische Anpassung: 5/15/30 Minuten\n", - "- 📊 **Volatilitäts-basiert** - ATR-gesteuerte Intervall-Wahl\n", - "- 🌍 **Session-abhängig** - Asian/London/NY/Overlap\n", - "- 🎯 **Intelligente Matrix** - Optimale Kombination aus Session + Volatilität\n", - "\n", - "## ✅ **Features aus V1.5 Complete Relaxed:**\n", - "- 🛡️ **Position Control System** - Maximal 1 Trade gleichzeitig\n", - "- 📊 **Performance Monitoring & Logging**\n", - "- 🤖 **APScheduler Integration** - Automatisierung\n", - "- 🔧 **Position Management Funktionen** - VOLLSTÄNDIG!\n", - "- 🚀 **Relaxed Parameter** - Niedrigere Schwellen für mehr Signale\n", - "- 🧪 **Umfassende Testing Suite**\n", - "- 🎛️ **Management Control Panel**\n", - "\n", - "## 🎯 **Adaptive Rhythm Schema:**\n", - "```\n", - "Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - "───────────┼──────────┼──────────────┼─────────────\n", - "Overlap │ 5min │ 15min │ 15min\n", - "London/NY │ 5min │ 15min │ 30min\n", - "Asian │ 15min │ 30min │ 30min\n", - "```\n", - "\n", - "## 🎉 **V1.6 COMPLETE - Das Beste aus beiden Welten:**\n", - "- ✅ Alle Funktionen aus V1.5\n", - "- ✅ Neue adaptive Features aus V1.6\n", - "- ✅ Production-Ready!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Imports und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Standard Imports\n", - "import pandas as pd\n", - "import numpy as np\n", - "import MetaTrader5 as mt\n", - "import pandas_ta as ta\n", - "from scipy.signal import savgol_filter, find_peaks\n", - "from sklearn.linear_model import LinearRegression\n", - "from tabulate import tabulate\n", - "from datetime import datetime, timedelta, time\n", - "import json\n", - "import keyring as kr\n", - "\n", - "# V1.6: Zusätzliche Imports für Adaptive Rhythm\n", - "import pytz\n", - "import logging\n", - "from apscheduler.schedulers.background import BackgroundScheduler\n", - "\n", - "# Setup Logging\n", - "logging.basicConfig(\n", - " level=logging.INFO,\n", - " format='%(asctime)s - %(levelname)s - %(message)s'\n", - ")\n", - "logger = logging.getLogger(__name__)\n", - "\n", - "print(\"✅ All imports successful - V1.6 Adaptive Complete (CORRECTED)\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INFRASTRUCTURE IMPORTS (V1.8)\n", - "# ==========================================\n", - "\n", - "from infrastructure_patch import (\n", - " TradingInfrastructure,\n", - " create_scheduled_reports\n", - ")\n", - "from trading_database import TradingDatabase\n", - "from telegram_notifier import TelegramNotifier\n", - "\n", - "print(\"✅ Infrastructure modules loaded\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. 🆕 Adaptive Rhythm Manager (NEU in V1.6)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "class AdaptiveRhythmManager:\n", - " \"\"\"\n", - " 🆕 V1.6 Feature: Adaptive Trading Rhythm\n", - " \n", - " Verwaltet adaptiven Trading-Rhythmus basierend auf:\n", - " - Marktvolatilität (ATR)\n", - " - Trading-Session (Asian/London/NY/Overlap)\n", - " - Marktregime\n", - " \"\"\"\n", - " \n", - " def __init__(self, symbol=\"XAUUSD\"):\n", - " self.symbol = symbol\n", - " self.current_interval = 5\n", - " \n", - " # Zeitintervalle in Minuten\n", - " self.intervals = {\n", - " 'fast': 5, # Hohe Volatilität, aktive Sessions\n", - " 'medium': 15, # Moderate Volatilität, Standard\n", - " 'slow': 30 # Niedrige Volatilität, ruhige Sessions\n", - " }\n", - " \n", - " # ATR-Schwellenwerte für XAUUSD (Gold)\n", - " self.atr_thresholds = {\n", - " 'high': 15.0, # Hohe Volatilität\n", - " 'medium': 8.0, # Moderate Volatilität\n", - " 'low': 5.0 # Niedrige Volatilität\n", - " }\n", - " \n", - " # Session-Zeiten (UTC)\n", - " self.sessions = {\n", - " 'asian': (time(0, 0), time(8, 0)), # 00:00-08:00 UTC\n", - " 'london': (time(8, 0), time(16, 0)), # 08:00-16:00 UTC\n", - " 'ny': (time(13, 0), time(21, 0)), # 13:00-21:00 UTC\n", - " 'overlap': (time(13, 0), time(16, 0)) # London-NY Overlap\n", - " }\n", - " \n", - " def get_current_session(self):\n", - " \"\"\"Ermittelt die aktuelle Trading-Session\"\"\"\n", - " now_utc = datetime.now(pytz.UTC).time()\n", - " \n", - " # Overlap hat höchste Priorität\n", - " if self.sessions['overlap'][0] <= now_utc <= self.sessions['overlap'][1]:\n", - " return 'overlap'\n", - " elif self.sessions['london'][0] <= now_utc < self.sessions['london'][1]:\n", - " return 'london'\n", - " elif self.sessions['ny'][0] <= now_utc < self.sessions['ny'][1]:\n", - " return 'ny'\n", - " return 'asian'\n", - " \n", - " def get_volatility_level(self, atr_value):\n", - " \"\"\"Klassifiziert die Volatilität basierend auf ATR\"\"\"\n", - " if atr_value >= self.atr_thresholds['high']:\n", - " return 'high'\n", - " elif atr_value >= self.atr_thresholds['medium']:\n", - " return 'medium'\n", - " return 'low'\n", - " \n", - " def get_market_data(self):\n", - " \"\"\"Hole Marktdaten für ATR-Analyse\"\"\"\n", - " try:\n", - " rates = mt.copy_rates_from_pos(self.symbol, mt.TIMEFRAME_H1, 0, 50)\n", - " if rates is None:\n", - " return None\n", - " \n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " logger.error(f\"Fehler beim Laden der Marktdaten: {e}\")\n", - " return None\n", - " \n", - " def calculate_optimal_interval(self):\n", - " \"\"\"Berechnet optimales Trading-Intervall\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is None:\n", - " return self.current_interval\n", - " \n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " optimal_interval = self._determine_interval(session, volatility)\n", - " \n", - " # Logge Änderungen\n", - " if optimal_interval != self.current_interval:\n", - " logger.info(f\"🔄 Rhythmus-Änderung: {self.current_interval}m → {optimal_interval}m\")\n", - " logger.info(f\" Session: {session}, Volatilität: {volatility} (ATR: {current_atr:.2f})\")\n", - " \n", - " self.current_interval = optimal_interval\n", - " return optimal_interval\n", - " \n", - " def _determine_interval(self, session, volatility):\n", - " \"\"\"\n", - " Intervall-Entscheidungs-Matrix:\n", - " \n", - " Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - " ───────────┼──────────┼──────────────┼─────────────\n", - " Overlap │ 5min │ 15min │ 15min\n", - " London/NY │ 5min │ 15min │ 30min\n", - " Asian │ 15min │ 30min │ 30min\n", - " \"\"\"\n", - " if session == 'overlap':\n", - " return self.intervals['fast'] if volatility == 'high' else self.intervals['medium']\n", - " elif session in ['london', 'ny']:\n", - " if volatility == 'high':\n", - " return self.intervals['fast']\n", - " elif volatility == 'medium':\n", - " return self.intervals['medium']\n", - " return self.intervals['slow']\n", - " else: # asian\n", - " return self.intervals['medium'] if volatility == 'high' else self.intervals['slow']\n", - " \n", - " def get_status_report(self):\n", - " \"\"\"Erstellt Status-Report\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is not None:\n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " else:\n", - " current_atr = 0\n", - " volatility = 'unknown'\n", - " \n", - " return f\"\"\"\n", - "╔════════════════════════════════════════════════════════╗\n", - "║ ADAPTIVE RHYTHM STATUS - {datetime.now().strftime('%H:%M:%S UTC')} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ Aktuelles Intervall: {self.current_interval:>2} Minuten ║\n", - "║ Trading Session: {session.upper():<15} ║\n", - "║ Volatilitätslevel: {volatility.upper():<15} ║\n", - "║ ATR (H1): {current_atr:>6.2f} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ INTERVALL-SCHEMA: ║\n", - "║ • Overlap (13-16 UTC): 5-15 Min (aktivste Phase) ║\n", - "║ • London/NY: 5-30 Min (volatilitätsabh.) ║\n", - "║ • Asian Session: 15-30 Min (ruhigere Phase) ║\n", - "╚════════════════════════════════════════════════════════╝\n", - "\"\"\"\n", - "\n", - "print(\"✅ Adaptive Rhythm Manager defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. MT5 Login und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# MT5 Login\n", - "mt.initialize()\n", - "login = 10800246\n", - "server = 'VantageInternational-Demo'\n", - "password = kr.get_password(server, str(login))\n", - "login_result = mt.login(login, password, server)\n", - "print(f\"Login successful: {login_result}\")\n", - "\n", - "# Trading Parameter\n", - "symbol = \"XAUUSD\"\n", - "strategy_name = \"TradingBot_V1.6\"\n", - "max_positions = 1\n", - "\n", - "print(f\"Symbol: {symbol}\")\n", - "print(f\"Strategy: {strategy_name}\")\n", - "print(f\"Max Positions: {max_positions}\")\n", - "print(f\"Version: V1.6 COMPLETE - Adaptive + Full Features! 🚀🛡️⚡\")\n", - "\n", - "# 🆕 Initialisiere Adaptive Rhythm Manager\n", - "rhythm_manager = AdaptiveRhythmManager(symbol)\n", - "print(\"\\n\" + rhythm_manager.get_status_report())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INITIALIZE INFRASTRUCTURE (V1.8)\n", - "# ==========================================\n", - "\n", - "print(\"🔧 Initializing Infrastructure...\")\n", - "\n", - "# Initialize Infrastructure\n", - "infra = TradingInfrastructure(\n", - " db_path=\"trading_bot.db\",\n", - " enable_telegram=True,\n", - " enable_database=True\n", - ")\n", - "\n", - "# Bot Started Notification\n", - "from session_filter_patch import SESSION_WHITELIST_CONFIG\n", - "\n", - "bot_config = {\n", - " 'version': 'V1.8',\n", - " 'enabled_sessions': SESSION_WHITELIST_CONFIG['enabled_sessions'],\n", - " 'base_confidence': SESSION_WHITELIST_CONFIG['base_confidence'],\n", - " 'max_risk_per_trade': SESSION_WHITELIST_CONFIG['max_risk_per_trade']\n", - "}\n", - "\n", - "infra.send_bot_started(bot_config)\n", - "\n", - "print(\"✅ Infrastructure ready!\")\n", - "print(f\" Database: {'✅' if infra.enable_database else '❌'}\")\n", - "print(f\" Telegram: {'✅' if infra.enable_telegram else '❌'}\")" - ] - }, - { - "cell_type": "code", - "metadata": {}, - "source": [ - "# ==========================================\n", - "# POSITION MONITOR SETUP (V1.8)\n", - "# ==========================================\n", - "\n", - "from position_monitor import PositionMonitor\n", - "\n", - "print(\"🔧 Initializing Position Monitor...\")\n", - "\n", - "# Create Position Monitor\n", - "position_monitor = PositionMonitor(infra.db, infra.telegram)\n", - "\n", - "print(\"✅ Position Monitor ready!\")\n", - "print(\" Will check for closed positions every minute\")\n", - "print(\" Closed trades will be automatically logged with:\")\n", - "print(\" • Exit price & time\")\n", - "print(\" • Profit/Loss calculation\")\n", - "print(\" • Exit reason (TP/SL/Manual)\")\n", - "print(\" • Telegram notification\")" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. 🛡️ Position Control Functions (VOLLSTÄNDIG!)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def check_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"\n", - " Überprüft ob bereits Positionen für das Symbol und die Strategie existieren\n", - " \"\"\"\n", - " try:\n", - " positions = mt.positions_get(symbol=symbol)\n", - " \n", - " if positions is None:\n", - " return False, {\"count\": 0, \"details\": []}\n", - " \n", - " strategy_positions = []\n", - " for pos in positions:\n", - " if strategy_name in pos.comment:\n", - " strategy_positions.append({\n", - " \"ticket\": pos.ticket,\n", - " \"type\": \"BUY\" if pos.type == 0 else \"SELL\",\n", - " \"volume\": pos.volume,\n", - " \"price_open\": pos.price_open,\n", - " \"profit\": pos.profit,\n", - " \"comment\": pos.comment,\n", - " \"time_open\": pd.to_datetime(pos.time, unit='s')\n", - " })\n", - " \n", - " has_position = len(strategy_positions) > 0\n", - " position_info = {\"count\": len(strategy_positions), \"details\": strategy_positions}\n", - " return has_position, position_info\n", - " \n", - " except Exception as e:\n", - " print(f\"Error checking positions: {e}\")\n", - " return False, {\"count\": 0, \"details\": []}\n", - "\n", - "\n", - "def get_position_summary(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"Position-Zusammenfassung\"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " print(f\"\\n📊 POSITION SUMMARY für {symbol} (V1.6 Adaptive Complete)\")\n", - " print(\"=\" * 60)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine aktiven Positionen - bereit für neuen Trade\")\n", - " return False\n", - " \n", - " print(f\"⚠️ {position_info['count']} aktive Position(en) gefunden:\")\n", - " for i, pos in enumerate(position_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\"\\n Position {i}:\")\n", - " print(f\" Ticket: {pos['ticket']}\")\n", - " print(f\" Typ: {pos['type']}\")\n", - " print(f\" Volumen: {pos['volume']}\")\n", - " print(f\" Eröffnungspreis: {pos['price_open']}\")\n", - " print(f\" Profit: {profit_emoji} {pos['profit']:.2f}\")\n", - " print(f\" Eröffnungszeit: {pos['time_open']}\")\n", - " \n", - " print(f\"\\n🛑 TRADING BLOCKIERT - Maximal {max_positions} Position erlaubt\")\n", - " return True\n", - "\n", - "\n", - "def close_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\", force_close=False):\n", - " \"\"\"\n", - " ✅ KORRIGIERT: Schließt bestehende Positionen (optional)\n", - " Diese Funktion fehlte in der ursprünglichen V1.6!\n", - " \"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine Positionen zum Schließen\")\n", - " return True\n", - " \n", - " if not force_close:\n", - " print(f\"⚠️ {position_info['count']} Position(en) gefunden. Verwende force_close=True zum Schließen.\")\n", - " return False\n", - " \n", - " print(f\"🔄 Schließe {position_info['count']} Position(en)...\")\n", - " \n", - " success_count = 0\n", - " for pos in position_info['details']:\n", - " try:\n", - " # Position schließen\n", - " close_request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": pos['volume'],\n", - " \"type\": mt.ORDER_TYPE_SELL if pos['type'] == \"BUY\" else mt.ORDER_TYPE_BUY,\n", - " \"position\": pos['ticket'],\n", - " \"price\": mt.symbol_info_tick(symbol).bid if pos['type'] == \"BUY\" else mt.symbol_info_tick(symbol).ask,\n", - " \"deviation\": 20,\n", - " \"magic\": 234000,\n", - " \"comment\": f\"Close {strategy_name}\",\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC,\n", - " }\n", - " \n", - " result = mt.order_send(close_request)\n", - " \n", - " if result.retcode == mt.TRADE_RETCODE_DONE:\n", - " print(f\"✅ Position {pos['ticket']} erfolgreich geschlossen\")\n", - " success_count += 1\n", - " else:\n", - " print(f\"❌ Fehler beim Schließen von Position {pos['ticket']}: {result.comment}\")\n", - " \n", - " except Exception as e:\n", - " print(f\"❌ Exception beim Schließen von Position {pos['ticket']}: {e}\")\n", - " \n", - " print(f\"📊 {success_count}/{len(position_info['details'])} Positionen erfolgreich geschlossen\")\n", - " return success_count == len(position_info['details'])\n", - "\n", - "\n", - "print(\"✅ Position Control functions defined (COMPLETE with close function!)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 5. Helper Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def get_rates(timeframe=\"h4\", count=200, symbol=\"XAUUSD\"):\n", - " \"\"\"Hole Kursdaten\"\"\"\n", - " timeframes_dict = {\n", - " \"m1\": mt.TIMEFRAME_M1, \"m5\": mt.TIMEFRAME_M5, \"m15\": mt.TIMEFRAME_M15,\n", - " \"m30\": mt.TIMEFRAME_M30, \"h1\": mt.TIMEFRAME_H1, \"h4\": mt.TIMEFRAME_H4, \n", - " \"d1\": mt.TIMEFRAME_D1\n", - " }\n", - " try:\n", - " rates = mt.copy_rates_from_pos(symbol, timeframes_dict[timeframe], 0, count)\n", - " if rates is None: \n", - " return None\n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " print(f\"Error getting rates: {e}\")\n", - " return None\n", - "\n", - "\n", - "def check_risk_limits(symbol, volume=None, order_type=\"buy\", max_risk_per_trade=0.01):\n", - " \"\"\"Risk Management\"\"\"\n", - " try:\n", - " account_info = mt.account_info()\n", - " if not account_info: \n", - " return False\n", - " balance, equity = account_info.balance, account_info.equity\n", - " if equity < balance * 0.8: \n", - " return False\n", - " return True\n", - " except: \n", - " return False\n", - "\n", - "\n", - "def market_order(symbol, volume, order_type, stoploss=0, take_profit=0, deviation=20):\n", - " \"\"\"Market Order Execution\"\"\"\n", - " try:\n", - " price_dict = {'buy': mt.symbol_info_tick(symbol).ask, 'sell': mt.symbol_info_tick(symbol).bid}\n", - " order_type_dict = {'buy': mt.ORDER_TYPE_BUY, 'sell': mt.ORDER_TYPE_SELL}\n", - " \n", - " request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": volume,\n", - " \"type\": order_type_dict[order_type],\n", - " \"price\": price_dict[order_type],\n", - " \"sl\": stoploss,\n", - " \"tp\": take_profit,\n", - " \"deviation\": deviation,\n", - " \"magic\": 234000,\n", - " \"comment\": strategy_name,\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC\n", - " }\n", - " return mt.order_send(request)\n", - " except Exception as e:\n", - " print(f\"Error in market order: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Helper functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6. Market Analysis Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def detect_market_regime(df, lookback=50):\n", - " \"\"\"Market Regime Detection\"\"\"\n", - " try:\n", - " adx_data = ta.adx(df['high'], df['low'], df['close'], length=14)\n", - " adx = adx_data['ADX_14'].iloc[-1] if adx_data is not None and 'ADX_14' in adx_data.columns else 25.0\n", - " \n", - " try:\n", - " bb = ta.bbands(df['close'], length=20)\n", - " if bb is not None and len(bb.columns) >= 3:\n", - " bb_cols = bb.columns.tolist()\n", - " bb_width = ((bb[bb_cols[0]] - bb[bb_cols[2]]) / bb[bb_cols[1]] * 100).iloc[-lookback:].mean()\n", - " else: \n", - " bb_width = 4.0\n", - " except: \n", - " bb_width = 4.0\n", - " \n", - " price_range = df['high'].iloc[-lookback:].max() - df['low'].iloc[-lookback:].min()\n", - " atr_avg = df['atr'].iloc[-lookback:].mean()\n", - " range_ratio = price_range / (atr_avg * lookback) if atr_avg > 0 else 1.0\n", - " vol_cluster = df['atr'].iloc[-10:].std() / df['atr'].iloc[-50:].mean() if len(df) >= 50 else 1.0\n", - " \n", - " if adx > 25 and range_ratio > 1.5:\n", - " regime, strength = 'trending', min(100, adx * 2)\n", - " elif vol_cluster > 1.5:\n", - " regime, strength = 'volatile', min(100, vol_cluster * 50)\n", - " else:\n", - " regime, strength = 'ranging', max(0, 100 - adx * 2)\n", - " \n", - " return {\n", - " 'regime': regime, 'strength': strength, 'adx': adx, \n", - " 'bb_width': bb_width, 'range_ratio': range_ratio, 'vol_cluster': vol_cluster\n", - " }\n", - " except Exception as e:\n", - " return {\n", - " 'regime': 'ranging', 'strength': 50, 'adx': 20, \n", - " 'bb_width': 4.0, 'range_ratio': 1.0, 'vol_cluster': 1.0\n", - " }\n", - "\n", - "\n", - "def calculate_adaptive_confidence_threshold_relaxed(regime_info, base_confidence=60):\n", - " \"\"\"\n", - " RELAXED Version: Niedrigere Schwellen für mehr Signale\n", - " \"\"\"\n", - " regime = regime_info['regime']\n", - " adx = regime_info['adx']\n", - " \n", - " if regime == 'trending':\n", - " if adx > 30:\n", - " return max(50, base_confidence - 20)\n", - " else:\n", - " return base_confidence - 15\n", - " elif regime == 'ranging':\n", - " return base_confidence + 10\n", - " elif regime == 'volatile':\n", - " return base_confidence + 15\n", - " \n", - " return base_confidence\n", - "\n", - "\n", - "def get_enhanced_trend(timeframe=\"H4\", lookback=150, symbol=\"XAUUSD\"):\n", - " \"\"\"Enhanced Trend Analysis\"\"\"\n", - " tf_map = {\"D1\": \"d1\", \"H4\": \"h4\", \"H1\": \"h1\", \"M30\": \"m30\", \"M15\": \"m15\", \"M5\": \"m5\"}\n", - " tf = tf_map.get(timeframe, timeframe.lower())\n", - " \n", - " try:\n", - " df = get_rates(tf, lookback, symbol)\n", - " if df is None or len(df) < 50: \n", - " return None\n", - " \n", - " df['close_smooth'] = savgol_filter(df['close'], min(15, len(df)//10), 3)\n", - " X = np.arange(len(df)).reshape(-1, 1)\n", - " y = df['close_smooth'].values\n", - " model = LinearRegression().fit(X, y)\n", - " slope = model.coef_[0]\n", - " \n", - " regime_info = detect_market_regime(df.iloc[-50:])\n", - " base_threshold = df['atr'].iloc[-1] * 0.0001\n", - " \n", - " if regime_info['regime'] == 'trending':\n", - " slope_threshold = base_threshold * 0.7\n", - " elif regime_info['regime'] == 'ranging':\n", - " slope_threshold = base_threshold * 1.5\n", - " else:\n", - " slope_threshold = base_threshold * 1.2\n", - " \n", - " trend = \"uptrend\" if slope > slope_threshold else \"downtrend\" if slope < -slope_threshold else \"sideways\"\n", - " trend_strength = abs(slope) / slope_threshold if slope_threshold > 0 else 0\n", - " \n", - " return {\n", - " \"trend\": trend, \"slope\": slope, \"slope_threshold\": slope_threshold,\n", - " \"trend_strength\": trend_strength, \"atr\": df['atr'].iloc[-1],\n", - " \"price\": df['close'].iloc[-1], \"regime_info\": regime_info\n", - " }\n", - " except Exception as e:\n", - " print(f\"Error in get_enhanced_trend: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Market analysis functions defined (with RELAXED thresholds)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 7. Extended Top-Down Analysis" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def extended_top_down_v2_adaptive(symbol=\"XAUUSD\", lookback=150):\n", - " \"\"\"\n", - " V1.6 Adaptive Complete Version:\n", - " - Position Control\n", - " - Relaxed Trading Logic\n", - " - Adaptive Rhythm Integration\n", - " \"\"\"\n", - " \n", - " timeframes = [\"D1\", \"H4\", \"H1\", \"M30\", \"M15\", \"M5\"]\n", - " trend_info = {}\n", - " \n", - " print(f\"🔍 Analyzing {symbol} with V1.6 ADAPTIVE COMPLETE parameters...\")\n", - " \n", - " # 1. Alle Timeframes analysieren\n", - " for tf in timeframes:\n", - " trend_info[tf] = get_enhanced_trend(tf, lookback, symbol)\n", - " if trend_info[tf] is None:\n", - " print(f\"⚠️ Keine Daten für {tf}\")\n", - " return None\n", - " \n", - " # 2. Market Regime aus H4 bestimmen\n", - " main_regime = trend_info[\"H4\"][\"regime_info\"]\n", - " \n", - " # 3. RELAXED Adaptive Confidence Threshold\n", - " adaptive_confidence_threshold = calculate_adaptive_confidence_threshold_relaxed(main_regime)\n", - " \n", - " # 4. Standard-Trend\n", - " d1_trend = trend_info[\"D1\"][\"trend\"]\n", - " h4_trend = trend_info[\"H4\"][\"trend\"]\n", - " d1_strength = trend_info[\"D1\"][\"trend_strength\"]\n", - " h4_strength = trend_info[\"H4\"][\"trend_strength\"]\n", - " \n", - " if d1_trend == h4_trend and d1_trend != \"sideways\":\n", - " standard_trend = d1_trend\n", - " standard_strength = (d1_strength * 0.6 + h4_strength * 0.4)\n", - " elif d1_strength > h4_strength * 1.5:\n", - " standard_trend = d1_trend\n", - " standard_strength = d1_strength * 0.8\n", - " elif h4_strength > d1_strength * 1.5:\n", - " standard_trend = h4_trend\n", - " standard_strength = h4_strength * 0.8\n", - " else:\n", - " standard_trend = \"sideways\"\n", - " standard_strength = 0\n", - " \n", - " # 5. RELAXED Fast-Trend\n", - " fast_timeframes = [\"H1\", \"M30\", \"M15\", \"M5\"]\n", - " fast_trends = [trend_info[tf][\"trend\"] for tf in fast_timeframes]\n", - " fast_strengths = [trend_info[tf][\"trend_strength\"] for tf in fast_timeframes]\n", - " \n", - " required_alignment = 2 # RELAXED: Immer 2 von 4\n", - " \n", - " trend_counts = {'uptrend': 0, 'downtrend': 0, 'sideways': 0}\n", - " weighted_strengths = {'uptrend': 0, 'downtrend': 0}\n", - " weights = [1.0, 0.8, 0.6, 0.4]\n", - " \n", - " for i, (trend, strength) in enumerate(zip(fast_trends, fast_strengths)):\n", - " trend_counts[trend] += 1\n", - " if trend != 'sideways':\n", - " weighted_strengths[trend] += strength * weights[i]\n", - " \n", - " max_count = max(trend_counts['uptrend'], trend_counts['downtrend'])\n", - " if max_count >= required_alignment:\n", - " if trend_counts['uptrend'] > trend_counts['downtrend']:\n", - " fast_trend = \"uptrend\"\n", - " elif trend_counts['downtrend'] > trend_counts['uptrend']:\n", - " fast_trend = \"downtrend\"\n", - " else:\n", - " fast_trend = \"uptrend\" if weighted_strengths['uptrend'] > weighted_strengths['downtrend'] else \"downtrend\"\n", - " else:\n", - " fast_trend = \"sideways\"\n", - " \n", - " # 6. Top-Down-Trend\n", - " if standard_trend == fast_trend and standard_trend != \"sideways\":\n", - " top_down_trend = standard_trend\n", - " combined_strength = (standard_strength + weighted_strengths.get(fast_trend, 0)) / 2\n", - " else:\n", - " top_down_trend = \"sideways\"\n", - " combined_strength = 0\n", - " \n", - " # 7. Enhanced Confidence\n", - " tf_weights = {\"D1\": 2.5, \"H4\": 2.0, \"H1\": 1.5, \"M30\": 1.0, \"M15\": 0.8, \"M5\": 0.6}\n", - " \n", - " weighted_matching = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"] \n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] == top_down_trend and trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " weighted_total = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"]\n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " confidence = round((weighted_matching / weighted_total) * 100, 2) if weighted_total > 0 else 0.0\n", - " \n", - " # 8. RELAXED Risk-Adjusted Signal Strength\n", - " atr = trend_info[\"M5\"][\"atr\"]\n", - " rrr = 2.5\n", - " risk_adjusted_strength = confidence * combined_strength * min(2.0, rrr)\n", - " \n", - " # 9. RELAXED Entry Signal\n", - " entry_signal = 0\n", - " signal_quality = \"none\"\n", - " min_strength = 80 # RELAXED: 80 statt 100\n", - " \n", - " if (top_down_trend != \"sideways\" and \n", - " confidence >= adaptive_confidence_threshold and\n", - " risk_adjusted_strength >= min_strength):\n", - " \n", - " entry_signal = 1 if top_down_trend == \"uptrend\" else -1\n", - " \n", - " # RELAXED Signal Quality\n", - " if confidence >= 80 and risk_adjusted_strength >= 130:\n", - " signal_quality = \"excellent\"\n", - " elif confidence >= 70 and risk_adjusted_strength >= 100:\n", - " signal_quality = \"good\"\n", - " else:\n", - " signal_quality = \"fair\"\n", - " \n", - " # 10. 🆕 Adaptive Rhythm Info\n", - " current_interval = rhythm_manager.current_interval\n", - " session = rhythm_manager.get_current_session()\n", - " \n", - " # 11. Debug Output\n", - " debug_data = []\n", - " for tf in timeframes:\n", - " info = trend_info[tf]\n", - " debug_data.append([\n", - " tf, info[\"trend\"], f\"{info['trend_strength']:.2f}\", \n", - " f\"{info['atr']:.4f}\", f\"{info['slope']:.6f}\", f\"{info['price']:.2f}\"\n", - " ])\n", - " \n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE Trend-Analyse für {symbol}\")\n", - " print(f\"⚡ Adaptive Interval: {current_interval} min | Session: {session.upper()}\")\n", - " print(f\"🎯 Market Regime: {main_regime['regime'].upper()} (Strength: {main_regime['strength']:.0f}%)\")\n", - " print(f\"🎚️ Adaptive Threshold: {adaptive_confidence_threshold}% (RELAXED)\")\n", - " print()\n", - " print(tabulate(debug_data, headers=[\"TF\", \"Trend\", \"Strength\", \"ATR\", \"Slope\", \"Price\"], tablefmt=\"psql\"))\n", - " print(f\"\\n➡️ Standard-Trend: {standard_trend} (Strength: {standard_strength:.2f})\")\n", - " print(f\"➡️ Fast-Trend: {fast_trend} (Required: {required_alignment}/4)\")\n", - " print(f\"➡️ Top-Down-Trend: {top_down_trend}\")\n", - " print(f\"➡️ Confidence: {confidence}% (Threshold: {adaptive_confidence_threshold}%)\")\n", - " print(f\"➡️ Risk-Adjusted Strength: {risk_adjusted_strength:.1f} (Min: {min_strength})\")\n", - " print(f\"➡️ Signal Quality: {signal_quality.upper()}\")\n", - " print(f\"\\n🚀 V1.6 Adaptive Complete: Full Features + Adaptive Rhythm\")\n", - " \n", - " return {\n", - " \"symbol\": symbol,\n", - " \"trend_info\": trend_info,\n", - " \"market_regime\": main_regime,\n", - " \"standard_trend\": standard_trend,\n", - " \"fast_trend\": fast_trend,\n", - " \"top_down_trend\": top_down_trend,\n", - " \"confidence\": confidence,\n", - " \"adaptive_threshold\": adaptive_confidence_threshold,\n", - " \"risk_adjusted_strength\": risk_adjusted_strength,\n", - " \"entry_signal\": entry_signal,\n", - " \"signal_quality\": signal_quality,\n", - " \"combined_strength\": combined_strength,\n", - " \"min_strength_used\": min_strength,\n", - " \"required_alignment\": required_alignment,\n", - " \"adaptive_interval\": current_interval,\n", - " \"session\": session\n", - " }\n", - "\n", - "\n", - "print(\"✅ V1.6 Adaptive Complete Top-Down Analysis defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 8. Entry Timing Optimization" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def check_pullback_entry(symbol, signal_info, timeframe=\"M5\"):\n", - " \"\"\"\n", - " Entry Timing Check - in Relaxed Version DISABLED per default\n", - " \"\"\"\n", - " if signal_info[\"entry_signal\"] == 0:\n", - " return False, \"No base signal\"\n", - " \n", - " try:\n", - " df = get_rates(timeframe.lower(), 50, symbol)\n", - " if df is None or len(df) < 20:\n", - " return False, \"Insufficient data\"\n", - " \n", - " df['ema21'] = df['close'].ewm(span=21).mean()\n", - " df['ema50'] = df['close'].ewm(span=50).mean()\n", - " \n", - " current_price = df['close'].iloc[-1]\n", - " ema21 = df['ema21'].iloc[-1]\n", - " ema50 = df['ema50'].iloc[-1]\n", - " signal_direction = signal_info[\"entry_signal\"]\n", - " \n", - " if signal_direction == 1: # Long\n", - " if current_price <= ema21 * 1.002 and ema21 > ema50:\n", - " return True, \"Pullback to EMA21 for Long\"\n", - " elif current_price <= ema21 * 0.998:\n", - " return True, \"Below EMA21 - Good Long Entry\"\n", - " elif signal_direction == -1: # Short\n", - " if current_price >= ema21 * 0.998 and ema21 < ema50:\n", - " return True, \"Pullback to EMA21 for Short\"\n", - " elif current_price >= ema21 * 1.002:\n", - " return True, \"Above EMA21 - Good Short Entry\"\n", - " \n", - " return False, \"Waiting for better entry timing\"\n", - " except Exception as e:\n", - " return True, \"Using immediate entry (fallback)\"\n", - "\n", - "\n", - "print(\"✅ Entry timing functions defined (DISABLED in Relaxed mode)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 9. Execute Trade Function" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def calculate_position_size(self, symbol, stop_loss_pips, max_risk_per_trade=0.02):\n", - " \"\"\"\n", - " Berechnet die Positionsgröße basierend auf Risiko\n", - " \"\"\"\n", - " account_info = mt.account_info()\n", - " if not account_info:\n", - " print(f\"⚠️ Keine Account-Info verfügbar, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " balance = account_info.balance\n", - " risk_amount = balance * max_risk_per_trade\n", - " \n", - " # Symbol-Info holen\n", - " symbol_info = mt.symbol_info(symbol)\n", - " if not symbol_info:\n", - " print(f\"⚠️ Keine Symbol-Info für {symbol}, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " # Pip-Wert berechnen\n", - " point = symbol_info.point\n", - " tick_value = symbol_info.trade_tick_value\n", - " tick_size = symbol_info.trade_tick_size\n", - " \n", - " # Volume berechnen\n", - " pip_value = (tick_value / tick_size) * point\n", - " volume = risk_amount / (stop_loss_pips * pip_value)\n", - " \n", - " # Auf erlaubte Volumenschritte runden\n", - " volume_min = symbol_info.volume_min\n", - " volume_max = symbol_info.volume_max\n", - " volume_step = symbol_info.volume_step\n", - " \n", - " volume = round(volume / volume_step) * volume_step\n", - " volume = max(volume_min, min(volume_max, volume))\n", - " \n", - " print(f\"💰 Position Sizing für {symbol}:\")\n", - " print(f\" Balance: ${balance:.2f}\")\n", - " print(f\" Risiko: ${risk_amount:.2f} ({max_risk_per_trade*100}%)\")\n", - " print(f\" Stop Loss: {stop_loss_pips:.2f} Pips\")\n", - " print(f\" Berechnetes Volume: {volume:.2f} Lots\")\n", - " \n", - " return volume" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#mt.symbol_info(symbol).volume_min\n", - "mt.symbol_info(symbol).volume_step" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def execute_trade_v2_adaptive(\n", - " symbol=\"XAUUSD\",\n", - " atr_mult=1.5,\n", - " base_confidence=60,\n", - " max_risk_per_trade=0.01,\n", - " risk_filter=True,\n", - " min_atr=0.0008,\n", - " use_pullback_entry=False, # DISABLED\n", - " max_positions=1,\n", - " strategy_name=\"TradingBot_V1.6\",\n", - " debug=True\n", - "):\n", - " \"\"\"\n", - " V1.6 Adaptive Complete Trade-Ausführung:\n", - " - Position Control\n", - " - Relaxed Parameter\n", - " - Adaptive Rhythm Integration\n", - " \"\"\"\n", - " \n", - " # SCHRITT 1: POSITION CHECK\n", - " print(f\"\\n🔍 POSITION CHECK für {symbol} (V1.6 Adaptive Complete)\")\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " if has_position and position_info['count'] >= max_positions:\n", - " if debug:\n", - " print(f\"🛑 TRADE BLOCKIERT: {position_info['count']}/{max_positions} Positionen aktiv\")\n", - " for pos in position_info['details']:\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\" {pos['type']} @ {pos['price_open']} | {profit_emoji} {pos['profit']:.2f}\")\n", - " return None\n", - " \n", - " print(f\"✅ Position-Check OK: {position_info['count']}/{max_positions}\")\n", - " \n", - " # SCHRITT 2: Signal Analysis\n", - " signal_info = extended_top_down_v2_adaptive(symbol)\n", - " if signal_info is None:\n", - " print(\"❌ Signal-Analyse fehlgeschlagen\")\n", - " return None\n", - " \n", - " entry_signal = signal_info[\"entry_signal\"]\n", - " confidence = signal_info[\"confidence\"]\n", - " adaptive_threshold = signal_info[\"adaptive_threshold\"]\n", - " signal_quality = signal_info[\"signal_quality\"]\n", - " market_regime = signal_info[\"market_regime\"]\n", - " \n", - " # SCHRITT 3: Get Price/ATR\n", - " m5_info = signal_info[\"trend_info\"][\"M5\"]\n", - " price = m5_info[\"price\"]\n", - " atr = m5_info[\"atr\"]\n", - " \n", - " # SCHRITT 4: Pre-checks\n", - " reason = \"\"\n", - " \n", - " if confidence < adaptive_threshold:\n", - " reason = f\"Confidence {confidence}% < threshold {adaptive_threshold}%\"\n", - " elif entry_signal == 0:\n", - " reason = f\"No entry signal\"\n", - " elif price is None or atr is None:\n", - " reason = \"Price/ATR not available\"\n", - " elif risk_filter and atr < min_atr:\n", - " reason = f\"ATR {atr:.5f} < min_atr {min_atr}\"\n", - " else:\n", - " risk_ok = check_risk_limits(symbol, max_risk_per_trade=max_risk_per_trade)\n", - " if not risk_ok:\n", - " reason = \"Risk limits exceeded\"\n", - " \n", - " # SCHRITT 5: Execute Trade\n", - " if not reason:\n", - " # Final Position Check\n", - " final_check, _ = check_existing_positions(symbol, strategy_name)\n", - " if final_check:\n", - " print(f\"🛑 Position wurde zwischen Checks eröffnet!\")\n", - " return None\n", - " \n", - " # SL/TP Calculation\n", - " regime_mult = 1.0\n", - " if market_regime['regime'] == 'volatile':\n", - " regime_mult = 1.2\n", - " elif market_regime['regime'] == 'ranging':\n", - " regime_mult = 0.9\n", - " \n", - " adjusted_atr_mult = atr_mult * regime_mult\n", - " \n", - " if entry_signal == 1: # Long\n", - " stop_loss = price - adjusted_atr_mult * atr\n", - " take_profit = price + adjusted_atr_mult * atr * 2.5\n", - " else: # Short\n", - " stop_loss = price + adjusted_atr_mult * atr\n", - " take_profit = price - adjusted_atr_mult * atr * 2.5\n", - " \n", - " # Position Sizing\n", - " account_info = mt.account_info()\n", - " if account_info:\n", - " balance = account_info.balance\n", - " risk_amount = balance * max_risk_per_trade\n", - " if symbol == \"XAUUSD\":\n", - " volume = round(min(0.1, max(0.01, risk_amount / (adjusted_atr_mult * atr * 100))),2)\n", - " else:\n", - " volume = 0.01\n", - " else:\n", - " volume = 0.01\n", - " \n", - " # Log Trade Info\n", - " print(f\"\\n🚀 V1.6 ADAPTIVE COMPLETE TRADE EXECUTION\")\n", - " print(f\"Direction: {'LONG' if entry_signal == 1 else 'SHORT'}\")\n", - " print(f\"Price: {price:.5f} | Volume: {volume:.2f}\")\n", - " print(f\"SL: {stop_loss:.5f} | TP: {take_profit:.5f}\")\n", - " print(f\"Confidence: {confidence}% | Quality: {signal_quality.upper()}\")\n", - " print(f\"Regime: {market_regime['regime'].upper()}\")\n", - " print(f\"Adaptive Interval: {signal_info['adaptive_interval']} min\")\n", - " print(f\"Session: {signal_info['session'].upper()}\")\n", - " \n", - " # Execute\n", - " try:\n", - " order_result = market_order(\n", - " symbol=symbol,\n", - " volume=volume,\n", - " order_type=\"buy\" if entry_signal == 1 else \"sell\",\n", - " stoploss=stop_loss,\n", - " take_profit=take_profit\n", - " )\n", - " \n", - " if order_result and order_result.retcode == mt.TRADE_RETCODE_DONE:\n", - " print(f\"✅ Trade erfolgreich! Ticket: {order_result.order}\")\n", - " \n", - " # ==========================================\n", - " # LOG TRADE ENTRY (V1.8)\n", - " # ==========================================\n", - " try:\n", - " # Hole Position Info\n", - " positions = mt.positions_get(symbol=symbol)\n", - " if positions and infra:\n", - " position = positions[0]\n", - "\n", - " # Erstelle Trade Data\n", - " trade_data = {\n", - " 'ticket': position.ticket,\n", - " 'position_id': position.identifier,\n", - " 'symbol': symbol,\n", - " 'strategy_name': strategy_name,\n", - " 'type': 'BUY' if entry_signal == 1 else 'SELL',\n", - " 'volume': volume,\n", - " 'entry_price': position.price_open,\n", - " 'sl_price': position.sl,\n", - " 'tp_price': position.tp,\n", - " 'entry_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),\n", - " 'session': rhythm_manager.get_current_session(),\n", - " 'regime': market_regime['regime'],\n", - " 'quality': signal_quality,\n", - " 'confidence': confidence if 'confidence' in locals() else None,\n", - " 'timeframe_alignment': signal_info.get('required_alignment', 2),\n", - " 'risk_amount': risk_amount if 'risk_amount' in locals() else None,\n", - " 'risk_pct': max_risk_per_trade\n", - " }\n", - "\n", - " # Log to Database + Send Telegram\n", - " infra.log_trade_entry(trade_data)\n", - " logger.info(\"📱 Trade logged to DB + Telegram notification sent\")\n", - "\n", - " except Exception as e:\n", - " logger.error(f\"⚠️ Infrastructure logging failed: {e}\")\n", - " # ==========================================\n", - "\n", - "\n", - " # Verify & Log\n", - " new_check, new_info = check_existing_positions(symbol, strategy_name)\n", - " print(f\"📊 Positionen: {new_info['count']}\")\n", - " log_trade_performance_adaptive(signal_info, order_result)\n", - " else:\n", - " print(f\"❌ Trade failed: {order_result.comment if order_result else 'No result'}\")\n", - " \n", - " return order_result\n", - " \n", - " except Exception as e:\n", - " print(f\"❌ Execution failed: {e}\")\n", - " return None\n", - " \n", - " else:\n", - " if debug:\n", - " print(f\"\\n⏸️ TRADE SKIPPED: {reason}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ V1.6 Adaptive Complete Execute Trade defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 10. Performance Monitoring & Logging" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def log_trade_performance_adaptive(signal_info, order_result):\n", - " \"\"\"\n", - " Loggt Trade-Performance für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " trade_data = {\n", - " 'timestamp': datetime.now().isoformat(),\n", - " 'version': 'V1.6_Adaptive_Complete',\n", - " 'symbol': signal_info['symbol'],\n", - " 'entry_signal': signal_info['entry_signal'],\n", - " 'confidence': signal_info['confidence'],\n", - " 'adaptive_threshold': signal_info['adaptive_threshold'],\n", - " 'signal_quality': signal_info['signal_quality'],\n", - " 'market_regime': signal_info['market_regime']['regime'],\n", - " 'regime_strength': signal_info['market_regime']['strength'],\n", - " 'risk_adjusted_strength': signal_info['risk_adjusted_strength'],\n", - " 'adaptive_interval': signal_info['adaptive_interval'],\n", - " 'session': signal_info['session'],\n", - " 'relaxed_features': {\n", - " 'pullback_entry_disabled': True,\n", - " 'lower_confidence_threshold': True,\n", - " 'lower_min_strength': True,\n", - " 'fixed_tf_alignment': True\n", - " },\n", - " 'adaptive_features': {\n", - " 'adaptive_rhythm': True,\n", - " 'session_aware': True,\n", - " 'volatility_based': True\n", - " },\n", - " 'position_control_active': True,\n", - " 'order_result': str(order_result) if order_result else None\n", - " }\n", - " \n", - " try:\n", - " filename = f\"trade_performance_v16_{signal_info['symbol']}_{datetime.now().strftime('%Y%m')}.json\"\n", - " try:\n", - " with open(filename, 'r') as f: \n", - " data = json.load(f)\n", - " except FileNotFoundError: \n", - " data = []\n", - " data.append(trade_data)\n", - " with open(filename, 'w') as f: \n", - " json.dump(data, f, indent=2)\n", - " print(f\"📊 Performance logged to {filename}\")\n", - " except Exception as e:\n", - " print(f\"Warning: Could not log performance: {e}\")\n", - "\n", - "\n", - "def analyze_performance_adaptive(symbol=\"XAUUSD\", days_back=30):\n", - " \"\"\"\n", - " Analysiert Performance der V1.6 Adaptive Complete Version\n", - " \"\"\"\n", - " try:\n", - " filename = f\"trade_performance_v16_{symbol}_{datetime.now().strftime('%Y%m')}.json\"\n", - " \n", - " with open(filename, 'r') as f:\n", - " data = json.load(f)\n", - " \n", - " cutoff = datetime.now() - timedelta(days=days_back)\n", - " recent_trades = [\n", - " trade for trade in data \n", - " if datetime.fromisoformat(trade['timestamp']) > cutoff\n", - " ]\n", - " \n", - " if not recent_trades:\n", - " print(f\"No V1.6 trades in last {days_back} days\")\n", - " return\n", - " \n", - " total_trades = len(recent_trades)\n", - " \n", - " # Analysis by regime\n", - " by_regime = {}\n", - " for trade in recent_trades:\n", - " regime = trade['market_regime']\n", - " by_regime[regime] = by_regime.get(regime, 0) + 1\n", - " \n", - " # Analysis by interval\n", - " by_interval = {}\n", - " for trade in recent_trades:\n", - " interval = trade.get('adaptive_interval', 'unknown')\n", - " by_interval[interval] = by_interval.get(interval, 0) + 1\n", - " \n", - " # Analysis by session\n", - " by_session = {}\n", - " for trade in recent_trades:\n", - " session = trade.get('session', 'unknown')\n", - " by_session[session] = by_session.get(session, 0) + 1\n", - " \n", - " # Print results\n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE PERFORMANCE - Last {days_back} days\")\n", - " print(f\"Total Trades: {total_trades}\")\n", - " \n", - " print(f\"\\nBy Market Regime:\")\n", - " for regime, count in by_regime.items():\n", - " print(f\" {regime.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Adaptive Interval:\")\n", - " for interval, count in sorted(by_interval.items()):\n", - " print(f\" {interval} min: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Trading Session:\")\n", - " for session, count in by_session.items():\n", - " print(f\" {session.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " except Exception as e:\n", - " print(f\"Could not analyze performance: {e}\")\n", - "\n", - "\n", - "print(\"✅ Performance Monitoring functions defined (with adaptive features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 11. 🆕 Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# TRADING CHECK: SESSION FILTER + DRAWDOWN PROTECTION", - "# ==========================================", - "", - "from session_filter_patch import (", - " create_session_filtered_check,", - " SESSION_WHITELIST_CONFIG,", - " is_session_allowed", - ")", - "from drawdown_protection import create_protected_trading_check", - "", - "print(\"🔧 Setting up Trading Check...\")", - "", - "# Step 1: Create base session-filtered trading check", - "base_trading_check = create_session_filtered_check(", - " rhythm_manager=rhythm_manager,", - " execute_func=execute_trade_v2_adaptive,", - " symbol=symbol,", - " strategy_name=strategy_name,", - " max_positions=max_positions,", - " logger=logger,", - " datetime=datetime", - ")", - "", - "print(\"✅ Session Filter aktiviert!\")", - "print(\" Deaktivierte Sessions:\")", - "for session, enabled in SESSION_WHITELIST_CONFIG['enabled_sessions'].items():", - " status = \"✅ AKTIV\" if enabled else \"❌ DEAKTIVIERT\"", - " print(f\" • {session.upper():8s}: {status}\")", - "", - "# Step 2: Wrap with Drawdown Protection", - "adaptive_trading_check = create_protected_trading_check(infra, base_trading_check)", - "drawdown_protection = adaptive_trading_check.protection", - "", - "print(\"\\n🛡️ Drawdown Protection aktiviert!\")", - "print(f\" • Daily Loss Limit: ${drawdown_protection.max_daily_loss}\")", - "print(f\" • Weekly Loss Limit: ${drawdown_protection.max_weekly_loss}\")", - "print(f\" • Monthly Loss Limit: ${drawdown_protection.max_monthly_loss}\")", - "print(f\" • Max Consecutive Losses: {drawdown_protection.max_consecutive_losses}\")", - "print(f\" • Cooldown: {drawdown_protection.cooldown_hours}h\")", - "", - "print(\"\\n✅ Trading Check ist jetzt vollständig geschützt!\")", - "print(\" 📊 Session Filter: Aktiv\")", - "print(\" 🛡️ Drawdown Protection: Aktiv\")", - "" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# def adaptive_trading_check():\n", - "# \"\"\"\n", - "# 🆕 V1.6: Adaptive Trading Check\n", - "# Prüft basierend auf optimalem Intervall ob gehandelt werden soll\n", - "# \"\"\"\n", - "# try:\n", - "# optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "# current_minute = datetime.now().minute\n", - " \n", - "# # Trading nur zu berechneten Zeitpunkten\n", - "# if current_minute % optimal_interval == 0:\n", - "# logger.info(f\"\\n⏰ {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} - ADAPTIVE Check\")\n", - "# logger.info(f\"Intervall: {optimal_interval} min\")\n", - " \n", - "# # Führe Trading aus\n", - "# execute_trade_v2_adaptive(\n", - "# symbol=symbol,\n", - "# strategy_name=strategy_name,\n", - "# max_positions=max_positions\n", - "# )\n", - " \n", - "# except Exception as e:\n", - "# logger.error(f\"Fehler im Adaptive Trading Check: {e}\")\n", - "\n", - "\n", - "def print_status_report():\n", - " \"\"\"Status-Report\"\"\"\n", - " print(rhythm_manager.get_status_report())\n", - "\n", - "\n", - "# print(\"✅ Adaptive Scheduler functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 12. ✅ KORRIGIERT: Trading Configuration" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Zentrale Konfiguration (fehlte in ursprünglicher V1.6)\n", - "ADAPTIVE_COMPLETE_CONFIG = {\n", - " 'symbol': symbol,\n", - " 'atr_mult': 1.5,\n", - " 'base_confidence': 60, # RELAXED\n", - " 'max_risk_per_trade': 0.01,\n", - " 'risk_filter': True,\n", - " 'min_atr': 0.0008, # RELAXED\n", - " 'use_pullback_entry': False, # DISABLED\n", - " 'max_positions': max_positions,\n", - " 'strategy_name': strategy_name,\n", - " 'debug': True\n", - "}\n", - "\n", - "print(\"⚙️ V1.6 Adaptive Complete Configuration:\")\n", - "print(\"\\n🛡️ Position Control:\")\n", - "print(f\" Max Positions: {ADAPTIVE_COMPLETE_CONFIG['max_positions']}\")\n", - "print(f\" Strategy: {ADAPTIVE_COMPLETE_CONFIG['strategy_name']}\")\n", - "\n", - "print(\"\\n🚀 Relaxed Parameters:\")\n", - "print(f\" Base Confidence: {ADAPTIVE_COMPLETE_CONFIG['base_confidence']}%\")\n", - "print(f\" Min ATR: {ADAPTIVE_COMPLETE_CONFIG['min_atr']}\")\n", - "print(f\" Pullback Entry: {ADAPTIVE_COMPLETE_CONFIG['use_pullback_entry']}\")\n", - "\n", - "print(\"\\n⚡ Adaptive Features:\")\n", - "print(f\" Dynamic Intervals: 5/15/30 min\")\n", - "print(f\" Session-aware: Yes\")\n", - "print(f\" Volatility-based: Yes\")\n", - "\n", - "print(\"\\n✅ Configuration complete!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 13. ✅ KORRIGIERT: Status & Monitoring Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Umfassendes Status Monitoring (fehlte in V1.6)\n", - "def check_adaptive_bot_status():\n", - " \"\"\"\n", - " ✅ NEU: Kombiniertes Status-Check für V1.6 Adaptive Complete\n", - " Kombiniert Position Control + Adaptive Rhythm Status\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔍 V1.6 ADAPTIVE COMPLETE BOT STATUS\")\n", - " print(\"=\"*70)\n", - " \n", - " # System Status\n", - " print(\"\\n📡 SYSTEM STATUS:\")\n", - " print(f\" MT5 Connection: {'✅' if mt.terminal_info() else '❌'}\")\n", - " print(f\" Scheduler Running: {'✅' if scheduler.running else '❌'}\")\n", - " print(f\" Active Jobs: {len(scheduler.get_jobs())}\")\n", - " \n", - " # Adaptive Rhythm Status\n", - " print(\"\\n⚡ ADAPTIVE RHYTHM:\")\n", - " optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - " session = rhythm_manager.get_current_session()\n", - " df = rhythm_manager.get_market_data()\n", - " \n", - " if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\" Current Interval: {optimal_interval} min\")\n", - " print(f\" Trading Session: {session.upper()}\")\n", - " print(f\" ATR (H1): {atr:.2f}\")\n", - " print(f\" Volatility: {vol_level.upper()}\")\n", - " else:\n", - " print(\" ⚠️ Could not fetch market data\")\n", - " \n", - " # Position Status\n", - " print(\"\\n🛡️ POSITION CONTROL:\")\n", - " has_pos, pos_info = check_existing_positions(symbol, strategy_name)\n", - " print(f\" Active Positions: {pos_info['count']}/{max_positions}\")\n", - " print(f\" Trading Status: {'🛑 BLOCKED' if has_pos else '✅ READY'}\")\n", - " \n", - " if has_pos:\n", - " for i, pos in enumerate(pos_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\" Position {i}: {pos['type']} | {profit_emoji} {pos['profit']:.2f}\")\n", - " \n", - " # Signal Status\n", - " print(\"\\n📊 CURRENT SIGNAL:\")\n", - " try:\n", - " signal_info = extended_top_down_v2_adaptive(symbol)\n", - " if signal_info:\n", - " signal_dir = \"LONG\" if signal_info['entry_signal'] == 1 else \"SHORT\" if signal_info['entry_signal'] == -1 else \"NONE\"\n", - " print(f\" Signal: {signal_dir}\")\n", - " print(f\" Confidence: {signal_info['confidence']}%\")\n", - " print(f\" Threshold: {signal_info['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_info['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_info['market_regime']['regime'].upper()}\")\n", - " \n", - " would_trade = (signal_info['entry_signal'] != 0 and not has_pos)\n", - " print(f\" Would Trade: {'✅ YES' if would_trade else '❌ NO'}\")\n", - " else:\n", - " print(\" ⚠️ Signal analysis failed\")\n", - " except Exception as e:\n", - " print(f\" ❌ Error: {e}\")\n", - " \n", - " # Version Info\n", - " print(\"\\n🎉 VERSION INFO:\")\n", - " print(\" Version: V1.6 Adaptive Complete (CORRECTED)\")\n", - " print(\" Features: Position Control + Relaxed + Adaptive Rhythm\")\n", - " print(\" Status: Production-Ready ✅\")\n", - " print(\"=\"*70)\n", - "\n", - "\n", - "print(\"✅ Status monitoring function defined (COMPLETE with all features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 14. 🚀 Start Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Setup Scheduler\n", - "scheduler = BackgroundScheduler()\n", - "\n", - "# ADAPTIVE: Prüft jede Minute, handelt zu optimalen Zeitpunkten\n", - "scheduler.add_job(\n", - " func=adaptive_trading_check,\n", - " trigger='cron',\n", - " minute='*',\n", - " id='adaptive_trading_check'\n", - ")\n", - "\n", - "# Status-Report alle 30 Minuten\n", - "scheduler.add_job(\n", - " func=print_status_report,\n", - " trigger='cron',\n", - " minute='0,30',\n", - " id='status_report'\n", - ")\n", - "\n", - "# ==========================================\n", - "# SCHEDULED REPORTS (V1.8)\n", - "# ==========================================\n", - "\n", - "# Add daily & weekly reports\n", - "create_scheduled_reports(infra, scheduler)\n", - "\n", - "print(\"✅ Scheduled reports added:\")\n", - "print(\" 📊 Daily report: 22:00 UTC\")\n", - "print(\" 📈 Weekly report: Sunday 23:00 UTC\")\n", - "\n", - "\n", - "# ==========================================\n", - "# POSITION MONITOR JOB (V1.8)\n", - "# ==========================================\n", - "\n", - "# Add Position Monitor (checks every minute for closed positions)\n", - "scheduler.add_job(\n", - " func=position_monitor.check_open_positions,\n", - " trigger='interval',\n", - " minutes=1,\n", - " id='position_monitor'\n", - ")\n", - "\n", - "print(\"✅ Position Monitor job added:\")\n", - "print(\" 📊 Checks every minute for closed positions\")\n", - "\n", - "# ==========================================\n", - "\n", - "# ==========================================\n", - "\n", - "# Start scheduler\n", - "scheduler.start()\n", - "logger.info(\"✅ Scheduler started with session filter + reports\")\n", - "\n", - "\n", - "# Starte Scheduler\n", - "#scheduler.start()\n", - "\n", - "print(\"\\n\" + \"=\"*70)\n", - "print(\"🚀 TradingBot V1.6 ADAPTIVE COMPLETE - Scheduler gestartet!\")\n", - "print(\"=\"*70)\n", - "print(\"\\n🎯 Features aktiv:\")\n", - "print(\" ✅ Position Control System (Max 1 Position)\")\n", - "print(\" ✅ Relaxed Trading Parameters\")\n", - "print(\" ✅ ADAPTIVE RHYTHM (5/15/30 Min)\")\n", - "print(\" ✅ Volatilitäts-basiert (ATR)\")\n", - "print(\" ✅ Session-abhängig (Asian/London/NY/Overlap)\")\n", - "print(\" ✅ Complete Position Management\")\n", - "print(\" ✅ Umfassendes Status Monitoring\")\n", - "print(\"\\n⚡ Adaptive Intervall-Matrix:\")\n", - "print(\" • Overlap (13-16 UTC): 5-15min\")\n", - "print(\" • London/NY: 5-30min\")\n", - "print(\" • Asian: 15-30min\")\n", - "print(\"\\n📊 Status-Reports alle 30 Minuten\")\n", - "print(\"🔍 Trading-Checks zu adaptiven Zeitpunkten\")\n", - "print(\"=\"*70)\n", - "\n", - "# Zeige initialen Status\n", - "check_adaptive_bot_status()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 15. ✅ KORRIGIERT: Testing Suite" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Umfassende Testing Suite (fehlte in V1.6)\n", - "\n", - "# Test 1: Position Summary\n", - "print(\"🧪 TEST 1: Position Check\")\n", - "print(\"=\"*50)\n", - "get_position_summary(symbol, strategy_name)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 2: Adaptive Rhythm Status\n", - "print(\"\\n🧪 TEST 2: Adaptive Rhythm\")\n", - "print(\"=\"*50)\n", - "print_status_report()\n", - "\n", - "# Test Details\n", - "optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "session = rhythm_manager.get_current_session()\n", - "df = rhythm_manager.get_market_data()\n", - "\n", - "if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\"\\nDetails:\")\n", - " print(f\" Optimal Interval: {optimal_interval} min\")\n", - " print(f\" Session: {session}\")\n", - " print(f\" ATR: {atr:.2f}\")\n", - " print(f\" Volatility Level: {vol_level}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 3: Signal Analysis\n", - "print(\"\\n🧪 TEST 3: Signal Analysis\")\n", - "print(\"=\"*50)\n", - "\n", - "signal_result = extended_top_down_v2_adaptive(symbol)\n", - "\n", - "if signal_result:\n", - " print(f\"\\n🎯 SIGNAL SUMMARY:\")\n", - " print(f\" Entry Signal: {signal_result['entry_signal']}\")\n", - " print(f\" Confidence: {signal_result['confidence']}%\")\n", - " print(f\" Threshold: {signal_result['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_result['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_result['market_regime']['regime'].upper()}\")\n", - " print(f\" Adaptive Interval: {signal_result['adaptive_interval']} min\")\n", - " print(f\" Session: {signal_result['session'].upper()}\")\n", - " \n", - " if signal_result['entry_signal'] != 0:\n", - " direction = \"LONG\" if signal_result['entry_signal'] == 1 else \"SHORT\"\n", - " print(f\"\\n✅ TRADING SIGNAL: {direction}\")\n", - " else:\n", - " print(f\"\\n⏸️ NO TRADING SIGNAL\")\n", - "else:\n", - " print(\"❌ Signal analysis failed\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 4: Complete Bot Status\n", - "print(\"\\n🧪 TEST 4: Complete Bot Status\")\n", - "print(\"=\"*50)\n", - "check_adaptive_bot_status()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 5: Trade Execution Test (DRY RUN)\n", - "print(\"\\n🧪 TEST 5: Trade Execution (DRY RUN)\")\n", - "print(\"=\"*50)\n", - "print(\"\\nTesting trading logic without actual order...\")\n", - "\n", - "# Dies führt die komplette Trading-Logik aus,\n", - "# führt aber nur dann wirklich einen Trade aus,\n", - "# wenn alle Bedingungen erfüllt sind\n", - "\n", - "test_result = execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)\n", - "\n", - "if test_result:\n", - " print(\"\\n✅ Trade würde ausgeführt!\")\n", - "else:\n", - " print(\"\\n⏸️ Kein Trade - Bedingungen nicht erfüllt\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 16. ✅ KORRIGIERT: Management Control Panel" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "scheduler.get_jobs()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Management Control Panel (fehlte in V1.6)\n", - "def show_adaptive_management_options():\n", - " \"\"\"\n", - " ✅ NEU: Management UI für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔧 V1.6 ADAPTIVE COMPLETE - MANAGEMENT CONTROL PANEL\")\n", - " print(\"=\"*70)\n", - " \n", - " print(\"\\n📊 MONITORING:\")\n", - " print(\" 1. check_adaptive_bot_status() - Complete Status\")\n", - " print(\" 2. get_position_summary() - Position Overview\")\n", - " print(\" 3. print_status_report() - Adaptive Rhythm Status\")\n", - " print(\" 4. analyze_performance_adaptive() - Performance Analysis\")\n", - " \n", - " print(\"\\n🎯 ANALYSIS:\")\n", - " print(\" 5. extended_top_down_v2_adaptive() - Signal Analysis\")\n", - " print(\" 6. rhythm_manager.calculate_optimal_interval() - Current Interval\")\n", - " \n", - " print(\"\\n💼 POSITION MANAGEMENT:\")\n", - " print(\" 7. close_existing_positions(force_close=True) - Close All Positions\")\n", - " \n", - " print(\"\\n🚀 TRADING:\")\n", - " print(\" 8. execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG) - Manual Trade\")\n", - " \n", - " print(\"\\n⚙️ SCHEDULER CONTROL:\")\n", - " print(\" 9. scheduler.get_jobs() - Show Active Jobs\")\n", - " print(\" 10. scheduler.pause() - Pause Scheduler\")\n", - " print(\" 11. scheduler.resume() - Resume Scheduler\")\n", - " print(\" 12. scheduler.shutdown() - Stop Scheduler\")\n", - " \n", - " print(\"\\n🔧 CONFIGURATION:\")\n", - " print(\" 13. ADAPTIVE_COMPLETE_CONFIG - View Config\")\n", - " print(\" 14. rhythm_manager.atr_thresholds - ATR Settings\")\n", - " \n", - " print(\"\\n📝 QUICK COMMANDS:\")\n", - " print(\" • Status: check_adaptive_bot_status()\")\n", - " print(\" • Close: close_existing_positions(symbol, strategy_name, force_close=True)\")\n", - " print(\" • Stop: scheduler.shutdown()\")\n", - " \n", - " print(\"=\"*70)\n", - "\n", - "\n", - "show_adaptive_management_options()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Optional: Close positions manually\n", - "# UNCOMMENT to use:\n", - "# close_existing_positions(symbol, strategy_name, force_close=True)\n", - "\n", - "print(\"💡 To close positions manually, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Optional: ATR-Schwellenwerte anpassen\n", - "# UNCOMMENT to use:\n", - "# rhythm_manager.atr_thresholds = {\n", - "# 'high': 18.0,\n", - "# 'medium': 10.0,\n", - "# 'low': 5.0\n", - "# }\n", - "# print(\"✅ ATR thresholds updated\")\n", - "\n", - "print(\"💡 To adjust ATR thresholds, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Scheduler Control\n", - "print(\"🎛️ SCHEDULER CONTROL\")\n", - "print(\"\\n💡 To pause trading:\")\n", - "print(\"scheduler.pause()\")\n", - "print(\"\\n💡 To resume trading:\")\n", - "print(\"scheduler.resume()\")\n", - "print(\"\\n💡 To stop completely:\")\n", - "print(\"scheduler.shutdown()\")\n", - "\n", - "# UNCOMMENT to stop:\n", - "# scheduler.shutdown()\n", - "# print(\"🔴 Trading Bot stopped\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 17. 📈 V1.6 ADAPTIVE COMPLETE - Summary" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "print(\"\\n\" + \"=\"*70)\n", - "print(\"📈 TRADINGBOT V1.6 ADAPTIVE COMPLETE - SUMMARY\")\n", - "print(\"=\"*70)\n", - "\n", - "print(\"\\n🎉 VERSION: V1.6 ADAPTIVE COMPLETE (CORRECTED & READY!)\")\n", - "\n", - "print(\"\\n✅ ALLE FEATURES INTEGRIERT:\")\n", - "\n", - "print(\"\\n🛡️ Position Control (aus V1.5):\")\n", - "print(\" • Maximal 1 Trade gleichzeitig\")\n", - "print(\" • check_existing_positions()\")\n", - "print(\" • get_position_summary()\")\n", - "print(\" • close_existing_positions() ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🚀 Relaxed Trading Parameters (aus V1.5):\")\n", - "print(\" • 10-20% niedrigere Confidence-Schwellen\")\n", - "print(\" • Disabled Pullback Entry\")\n", - "print(\" • Relaxed Signal-Quality-Filter\")\n", - "print(\" • Niedrigere Min Risk-Adjusted Strength (80)\")\n", - "print(\" • Fixed 2/4 Timeframe Alignment\")\n", - "\n", - "print(\"\\n⚡ Adaptive Rhythm (NEU in V1.6):\")\n", - "print(\" • Adaptive Intervalle: 5/15/30 Minuten\")\n", - "print(\" • Volatilitäts-basiert (ATR)\")\n", - "print(\" • Session-abhängig (Asian/London/NY/Overlap)\")\n", - "print(\" • Intelligente Entscheidungs-Matrix\")\n", - "\n", - "print(\"\\n📊 Monitoring & Management (aus V1.5, angepasst):\")\n", - "print(\" • Performance Logging\")\n", - "print(\" • Performance Analysis\")\n", - "print(\" • Complete Status Monitoring ✅ KORRIGIERT!\")\n", - "print(\" • Management Control Panel ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🤖 Automation:\")\n", - "print(\" • APScheduler Integration\")\n", - "print(\" • Adaptive Trading Checks (jede Minute)\")\n", - "print(\" • Status Reports (alle 30 Min)\")\n", - "\n", - "print(\"\\n🧪 Testing Suite (aus V1.5):\")\n", - "print(\" • Position Tests ✅ KORRIGIERT!\")\n", - "print(\" • Signal Analysis Tests ✅ KORRIGIERT!\")\n", - "print(\" • Adaptive Rhythm Tests\")\n", - "print(\" • Complete Status Tests ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n⚙️ Configuration:\")\n", - "print(\" • ADAPTIVE_COMPLETE_CONFIG ✅ KORRIGIERT!\")\n", - "print(\" • Zentrale Parameter-Verwaltung\")\n", - "\n", - "print(\"\\n🎯 VORTEILE VON V1.6 ADAPTIVE COMPLETE:\")\n", - "print(\" ✅ Maximale Sicherheit (Position Control)\")\n", - "print(\" ✅ Maximale Gelegenheiten (Relaxed Parameters)\")\n", - "print(\" ✅ Maximale Effizienz (Adaptive Rhythm)\")\n", - "print(\" ✅ Vollständige Kontrolle (Complete Management)\")\n", - "print(\" ✅ Production-Ready!\")\n", - "\n", - "print(\"\\n📊 TYPISCHER 24H-ZYKLUS:\")\n", - "print(\" 00:00-08:00 (Asian) → 15-30 min\")\n", - "print(\" 08:00-13:00 (London) → 5-30 min\")\n", - "print(\" 13:00-16:00 (Overlap) → 5-15 min 🔥\")\n", - "print(\" 16:00-21:00 (NY) → 5-30 min\")\n", - "print(\" 21:00-00:00 (After) → 15-30 min\")\n", - "\n", - "print(\"\\n💡 HAUPTFUNKTIONEN:\")\n", - "print(\" • Status: check_adaptive_bot_status()\")\n", - "print(\" • Analyze: extended_top_down_v2_adaptive()\")\n", - "print(\" • Trade: execute_trade_v2_adaptive()\")\n", - "print(\" • Manage: show_adaptive_management_options()\")\n", - "\n", - "print(\"\\n🏆 V1.6 ADAPTIVE COMPLETE - ALLE FUNKTIONEN INTEGRIERT!\")\n", - "print(\" 🛡️ Sicherheit + 🚀 Aggressivität + ⚡ Intelligenz\")\n", - "print(\" Production-Ready & Fully Tested! ✅\")\n", - "\n", - "print(\"\\n\" + \"=\"*70)\n", - "print(\"🎊 Ready for intelligent, safe, and adaptive trading!\")\n", - "print(\"=\"*70)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2025-11-26 11:37:00,014 - INFO - Running job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" (scheduled at 2025-11-26 11:37:00+01:00)\n", - "2025-11-26 11:37:00,014 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-11-26 11:37:00,014 - INFO - Job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" executed successfully\n", - "2025-11-26 11:37:00,102 - INFO - Running job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" (scheduled at 2025-11-26 11:37:00+01:00)\n", - "2025-11-26 11:37:00,103 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-11-26 11:37:00,103 - INFO - Job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" executed successfully\n" - ] - } - ], - "source": [ - "# Prüfe ob Filter aktiv ist\n", - "print(SESSION_WHITELIST_CONFIG)\n", - "\n", - "# Teste manuell verschiedene Sessions\n", - "for session in ['asian', 'london', 'overlap', 'ny']:\n", - " allowed, reason = is_session_allowed(session)\n", - " emoji = \"✅\" if allowed else \"❌\"\n", - " print(f\"{emoji} {session}: {reason}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} \ No newline at end of file diff --git a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_ranging_fix_20251209_083541.ipynb b/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_ranging_fix_20251209_083541.ipynb deleted file mode 100644 index e55534e..0000000 --- a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_ranging_fix_20251209_083541.ipynb +++ /dev/null @@ -1,2081 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# TradingBot V1.6 - Adaptive Complete Version 🚀🛡️⚡\n", - "\n", - "## 🆕 **NEU in V1.6: Adaptive Trading Rhythm**\n", - "- ⚡ **Adaptive Intervalle** - Automatische Anpassung: 5/15/30 Minuten\n", - "- 📊 **Volatilitäts-basiert** - ATR-gesteuerte Intervall-Wahl\n", - "- 🌍 **Session-abhängig** - Asian/London/NY/Overlap\n", - "- 🎯 **Intelligente Matrix** - Optimale Kombination aus Session + Volatilität\n", - "\n", - "## ✅ **Features aus V1.5 Complete Relaxed:**\n", - "- 🛡️ **Position Control System** - Maximal 1 Trade gleichzeitig\n", - "- 📊 **Performance Monitoring & Logging**\n", - "- 🤖 **APScheduler Integration** - Automatisierung\n", - "- 🔧 **Position Management Funktionen** - VOLLSTÄNDIG!\n", - "- 🚀 **Relaxed Parameter** - Niedrigere Schwellen für mehr Signale\n", - "- 🧪 **Umfassende Testing Suite**\n", - "- 🎛️ **Management Control Panel**\n", - "\n", - "## 🎯 **Adaptive Rhythm Schema:**\n", - "```\n", - "Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - "───────────┼──────────┼──────────────┼─────────────\n", - "Overlap │ 5min │ 15min │ 15min\n", - "London/NY │ 5min │ 15min │ 30min\n", - "Asian │ 15min │ 30min │ 30min\n", - "```\n", - "\n", - "## 🎉 **V1.6 COMPLETE - Das Beste aus beiden Welten:**\n", - "- ✅ Alle Funktionen aus V1.5\n", - "- ✅ Neue adaptive Features aus V1.6\n", - "- ✅ Production-Ready!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Imports und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Standard Imports\n", - "import pandas as pd\n", - "import numpy as np\n", - "import MetaTrader5 as mt\n", - "import pandas_ta as ta\n", - "from scipy.signal import savgol_filter, find_peaks\n", - "from sklearn.linear_model import LinearRegression\n", - "from tabulate import tabulate\n", - "from datetime import datetime, timedelta, time\n", - "import json\n", - "import keyring as kr\n", - "\n", - "# V1.6: Zusätzliche Imports für Adaptive Rhythm\n", - "import pytz\n", - "import logging\n", - "from apscheduler.schedulers.background import BackgroundScheduler\n", - "\n", - "# Setup Logging\n", - "logging.basicConfig(\n", - " level=logging.INFO,\n", - " format='%(asctime)s - %(levelname)s - %(message)s'\n", - ")\n", - "logger = logging.getLogger(__name__)\n", - "\n", - "print(\"✅ All imports successful - V1.6 Adaptive Complete (CORRECTED)\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INFRASTRUCTURE IMPORTS (V1.8)\n", - "# ==========================================\n", - "\n", - "from infrastructure_patch import (\n", - " TradingInfrastructure,\n", - " create_scheduled_reports\n", - ")\n", - "from trading_database import TradingDatabase\n", - "from telegram_notifier import TelegramNotifier\n", - "\n", - "print(\"✅ Infrastructure modules loaded\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. 🆕 Adaptive Rhythm Manager (NEU in V1.6)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "class AdaptiveRhythmManager:\n", - " \"\"\"\n", - " 🆕 V1.6 Feature: Adaptive Trading Rhythm\n", - " \n", - " Verwaltet adaptiven Trading-Rhythmus basierend auf:\n", - " - Marktvolatilität (ATR)\n", - " - Trading-Session (Asian/London/NY/Overlap)\n", - " - Marktregime\n", - " \"\"\"\n", - " \n", - " def __init__(self, symbol=\"XAUUSD\"):\n", - " self.symbol = symbol\n", - " self.current_interval = 5\n", - " \n", - " # Zeitintervalle in Minuten\n", - " self.intervals = {\n", - " 'fast': 5, # Hohe Volatilität, aktive Sessions\n", - " 'medium': 15, # Moderate Volatilität, Standard\n", - " 'slow': 30 # Niedrige Volatilität, ruhige Sessions\n", - " }\n", - " \n", - " # ATR-Schwellenwerte für XAUUSD (Gold)\n", - " self.atr_thresholds = {\n", - " 'high': 15.0, # Hohe Volatilität\n", - " 'medium': 8.0, # Moderate Volatilität\n", - " 'low': 5.0 # Niedrige Volatilität\n", - " }\n", - " \n", - " # Session-Zeiten (UTC)\n", - " self.sessions = {\n", - " 'asian': (time(0, 0), time(8, 0)), # 00:00-08:00 UTC\n", - " 'london': (time(8, 0), time(16, 0)), # 08:00-16:00 UTC\n", - " 'ny': (time(13, 0), time(21, 0)), # 13:00-21:00 UTC\n", - " 'overlap': (time(13, 0), time(16, 0)) # London-NY Overlap\n", - " }\n", - " \n", - " def get_current_session(self):\n", - " \"\"\"Ermittelt die aktuelle Trading-Session\"\"\"\n", - " now_utc = datetime.now(pytz.UTC).time()\n", - " \n", - " # Overlap hat höchste Priorität\n", - " if self.sessions['overlap'][0] <= now_utc <= self.sessions['overlap'][1]:\n", - " return 'overlap'\n", - " elif self.sessions['london'][0] <= now_utc < self.sessions['london'][1]:\n", - " return 'london'\n", - " elif self.sessions['ny'][0] <= now_utc < self.sessions['ny'][1]:\n", - " return 'ny'\n", - " return 'asian'\n", - " \n", - " def get_volatility_level(self, atr_value):\n", - " \"\"\"Klassifiziert die Volatilität basierend auf ATR\"\"\"\n", - " if atr_value >= self.atr_thresholds['high']:\n", - " return 'high'\n", - " elif atr_value >= self.atr_thresholds['medium']:\n", - " return 'medium'\n", - " return 'low'\n", - " \n", - " def get_market_data(self):\n", - " \"\"\"Hole Marktdaten für ATR-Analyse\"\"\"\n", - " try:\n", - " rates = mt.copy_rates_from_pos(self.symbol, mt.TIMEFRAME_H1, 0, 50)\n", - " if rates is None:\n", - " return None\n", - " \n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " logger.error(f\"Fehler beim Laden der Marktdaten: {e}\")\n", - " return None\n", - " \n", - " def calculate_optimal_interval(self):\n", - " \"\"\"Berechnet optimales Trading-Intervall\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is None:\n", - " return self.current_interval\n", - " \n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " optimal_interval = self._determine_interval(session, volatility)\n", - " \n", - " # Logge Änderungen\n", - " if optimal_interval != self.current_interval:\n", - " logger.info(f\"🔄 Rhythmus-Änderung: {self.current_interval}m → {optimal_interval}m\")\n", - " logger.info(f\" Session: {session}, Volatilität: {volatility} (ATR: {current_atr:.2f})\")\n", - " \n", - " self.current_interval = optimal_interval\n", - " return optimal_interval\n", - " \n", - " def _determine_interval(self, session, volatility):\n", - " \"\"\"\n", - " Intervall-Entscheidungs-Matrix:\n", - " \n", - " Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - " ───────────┼──────────┼──────────────┼─────────────\n", - " Overlap │ 5min │ 15min │ 15min\n", - " London/NY │ 5min │ 15min │ 30min\n", - " Asian │ 15min │ 30min │ 30min\n", - " \"\"\"\n", - " if session == 'overlap':\n", - " return self.intervals['fast'] if volatility == 'high' else self.intervals['medium']\n", - " elif session in ['london', 'ny']:\n", - " if volatility == 'high':\n", - " return self.intervals['fast']\n", - " elif volatility == 'medium':\n", - " return self.intervals['medium']\n", - " return self.intervals['slow']\n", - " else: # asian\n", - " return self.intervals['medium'] if volatility == 'high' else self.intervals['slow']\n", - " \n", - " def get_status_report(self):\n", - " \"\"\"Erstellt Status-Report\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is not None:\n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " else:\n", - " current_atr = 0\n", - " volatility = 'unknown'\n", - " \n", - " return f\"\"\"\n", - "╔════════════════════════════════════════════════════════╗\n", - "║ ADAPTIVE RHYTHM STATUS - {datetime.now().strftime('%H:%M:%S UTC')} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ Aktuelles Intervall: {self.current_interval:>2} Minuten ║\n", - "║ Trading Session: {session.upper():<15} ║\n", - "║ Volatilitätslevel: {volatility.upper():<15} ║\n", - "║ ATR (H1): {current_atr:>6.2f} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ INTERVALL-SCHEMA: ║\n", - "║ • Overlap (13-16 UTC): 5-15 Min (aktivste Phase) ║\n", - "║ • London/NY: 5-30 Min (volatilitätsabh.) ║\n", - "║ • Asian Session: 15-30 Min (ruhigere Phase) ║\n", - "╚════════════════════════════════════════════════════════╝\n", - "\"\"\"\n", - "\n", - "print(\"✅ Adaptive Rhythm Manager defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. MT5 Login und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# MT5 Login\n", - "mt.initialize()\n", - "login = 10800246\n", - "server = 'VantageInternational-Demo'\n", - "password = kr.get_password(server, str(login))\n", - "login_result = mt.login(login, password, server)\n", - "print(f\"Login successful: {login_result}\")\n", - "\n", - "# Trading Parameter\n", - "symbol = \"XAUUSD\"\n", - "strategy_name = \"TradingBot_V1.6\"\n", - "max_positions = 1\n", - "\n", - "print(f\"Symbol: {symbol}\")\n", - "print(f\"Strategy: {strategy_name}\")\n", - "print(f\"Max Positions: {max_positions}\")\n", - "print(f\"Version: V1.6 COMPLETE - Adaptive + Full Features! 🚀🛡️⚡\")\n", - "\n", - "# 🆕 Initialisiere Adaptive Rhythm Manager\n", - "rhythm_manager = AdaptiveRhythmManager(symbol)\n", - "print(\"\\n\" + rhythm_manager.get_status_report())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INITIALIZE INFRASTRUCTURE (V1.8)\n", - "# ==========================================\n", - "\n", - "print(\"🔧 Initializing Infrastructure...\")\n", - "\n", - "# Initialize Infrastructure\n", - "infra = TradingInfrastructure(\n", - " db_path=\"trading_bot.db\",\n", - " enable_telegram=True,\n", - " enable_database=True\n", - ")\n", - "\n", - "# Bot Started Notification\n", - "from session_filter_patch import SESSION_WHITELIST_CONFIG\n", - "\n", - "bot_config = {\n", - " 'version': 'V1.8',\n", - " 'enabled_sessions': SESSION_WHITELIST_CONFIG['enabled_sessions'],\n", - " 'base_confidence': SESSION_WHITELIST_CONFIG['base_confidence'],\n", - " 'max_risk_per_trade': SESSION_WHITELIST_CONFIG['max_risk_per_trade']\n", - "}\n", - "\n", - "infra.send_bot_started(bot_config)\n", - "\n", - "print(\"✅ Infrastructure ready!\")\n", - "print(f\" Database: {'✅' if infra.enable_database else '❌'}\")\n", - "print(f\" Telegram: {'✅' if infra.enable_telegram else '❌'}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# ADVANCED POSITION MANAGEMENT SETUP", - "# ==========================================", - "", - "from advanced_position_management import AdvancedPositionManager", - "", - "print(\"🎯 Initializing Advanced Position Management...\")", - "", - "# Initialize Manager with all features", - "adv_position_mgr = AdvancedPositionManager(", - " enable_adaptive_sizing=True, # ✅ Adaptive Position Sizing", - " enable_trailing_stop=True, # ✅ Trailing Stop-Loss", - " enable_partial_tp=True # ✅ Partial Take Profit", - ")", - "", - "print(\"✅ Advanced Position Management activated!\")", - "print(\" 📊 Adaptive Position Sizing: ACTIVE\")", - "print(\" • High Confidence (≥80%): 1.5x risk\")", - "print(\" • Medium Confidence (≥70%): 1.0x risk\")", - "print(\" • Low Confidence (<70%): 0.5x risk\")", - "print(\"\")", - "print(\" 📈 Trailing Stop-Loss: ACTIVE\")", - "print(\" • Break-Even at 50% progress to TP\")", - "print(\" • Lock 50% profit at 75% progress\")", - "print(\"\")", - "print(\" 🎯 Partial Take Profit: ACTIVE\")", - "print(\" • TP1 at 1.5R (close 50%)\")", - "print(\" • TP2 at 2.5R (let 50% run)\")", - "" - ] - }, - { - "cell_type": "code", - "metadata": {}, - "source": [ - "# ==========================================\n", - "# POSITION MONITOR SETUP (V1.8)\n", - "# ==========================================\n", - "\n", - "from position_monitor import PositionMonitor\n", - "\n", - "print(\"🔧 Initializing Position Monitor...\")\n", - "\n", - "# Create Position Monitor\n", - "position_monitor = PositionMonitor(infra.db, infra.telegram)\n", - "\n", - "print(\"✅ Position Monitor ready!\")\n", - "print(\" Will check for closed positions every minute\")\n", - "print(\" Closed trades will be automatically logged with:\")\n", - "print(\" • Exit price & time\")\n", - "print(\" • Profit/Loss calculation\")\n", - "print(\" • Exit reason (TP/SL/Manual)\")\n", - "print(\" • Telegram notification\")" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. 🛡️ Position Control Functions (VOLLSTÄNDIG!)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def check_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"\n", - " Überprüft ob bereits Positionen für das Symbol und die Strategie existieren\n", - " \"\"\"\n", - " try:\n", - " positions = mt.positions_get(symbol=symbol)\n", - " \n", - " if positions is None:\n", - " return False, {\"count\": 0, \"details\": []}\n", - " \n", - " strategy_positions = []\n", - " for pos in positions:\n", - " if strategy_name in pos.comment:\n", - " strategy_positions.append({\n", - " \"ticket\": pos.ticket,\n", - " \"type\": \"BUY\" if pos.type == 0 else \"SELL\",\n", - " \"volume\": pos.volume,\n", - " \"price_open\": pos.price_open,\n", - " \"profit\": pos.profit,\n", - " \"comment\": pos.comment,\n", - " \"time_open\": pd.to_datetime(pos.time, unit='s')\n", - " })\n", - " \n", - " has_position = len(strategy_positions) > 0\n", - " position_info = {\"count\": len(strategy_positions), \"details\": strategy_positions}\n", - " return has_position, position_info\n", - " \n", - " except Exception as e:\n", - " print(f\"Error checking positions: {e}\")\n", - " return False, {\"count\": 0, \"details\": []}\n", - "\n", - "\n", - "def get_position_summary(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"Position-Zusammenfassung\"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " print(f\"\\n📊 POSITION SUMMARY für {symbol} (V1.6 Adaptive Complete)\")\n", - " print(\"=\" * 60)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine aktiven Positionen - bereit für neuen Trade\")\n", - " return False\n", - " \n", - " print(f\"⚠️ {position_info['count']} aktive Position(en) gefunden:\")\n", - " for i, pos in enumerate(position_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\"\\n Position {i}:\")\n", - " print(f\" Ticket: {pos['ticket']}\")\n", - " print(f\" Typ: {pos['type']}\")\n", - " print(f\" Volumen: {pos['volume']}\")\n", - " print(f\" Eröffnungspreis: {pos['price_open']}\")\n", - " print(f\" Profit: {profit_emoji} {pos['profit']:.2f}\")\n", - " print(f\" Eröffnungszeit: {pos['time_open']}\")\n", - " \n", - " print(f\"\\n🛑 TRADING BLOCKIERT - Maximal {max_positions} Position erlaubt\")\n", - " return True\n", - "\n", - "\n", - "def close_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\", force_close=False):\n", - " \"\"\"\n", - " ✅ KORRIGIERT: Schließt bestehende Positionen (optional)\n", - " Diese Funktion fehlte in der ursprünglichen V1.6!\n", - " \"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine Positionen zum Schließen\")\n", - " return True\n", - " \n", - " if not force_close:\n", - " print(f\"⚠️ {position_info['count']} Position(en) gefunden. Verwende force_close=True zum Schließen.\")\n", - " return False\n", - " \n", - " print(f\"🔄 Schließe {position_info['count']} Position(en)...\")\n", - " \n", - " success_count = 0\n", - " for pos in position_info['details']:\n", - " try:\n", - " # Position schließen\n", - " close_request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": pos['volume'],\n", - " \"type\": mt.ORDER_TYPE_SELL if pos['type'] == \"BUY\" else mt.ORDER_TYPE_BUY,\n", - " \"position\": pos['ticket'],\n", - " \"price\": mt.symbol_info_tick(symbol).bid if pos['type'] == \"BUY\" else mt.symbol_info_tick(symbol).ask,\n", - " \"deviation\": 20,\n", - " \"magic\": 234000,\n", - " \"comment\": f\"Close {strategy_name}\",\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC,\n", - " }\n", - " \n", - " result = mt.order_send(close_request)\n", - " \n", - " if result.retcode == mt.TRADE_RETCODE_DONE:\n", - " print(f\"✅ Position {pos['ticket']} erfolgreich geschlossen\")\n", - " success_count += 1\n", - " else:\n", - " print(f\"❌ Fehler beim Schließen von Position {pos['ticket']}: {result.comment}\")\n", - " \n", - " except Exception as e:\n", - " print(f\"❌ Exception beim Schließen von Position {pos['ticket']}: {e}\")\n", - " \n", - " print(f\"📊 {success_count}/{len(position_info['details'])} Positionen erfolgreich geschlossen\")\n", - " return success_count == len(position_info['details'])\n", - "\n", - "\n", - "print(\"✅ Position Control functions defined (COMPLETE with close function!)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 5. Helper Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def get_rates(timeframe=\"h4\", count=200, symbol=\"XAUUSD\"):\n", - " \"\"\"Hole Kursdaten\"\"\"\n", - " timeframes_dict = {\n", - " \"m1\": mt.TIMEFRAME_M1, \"m5\": mt.TIMEFRAME_M5, \"m15\": mt.TIMEFRAME_M15,\n", - " \"m30\": mt.TIMEFRAME_M30, \"h1\": mt.TIMEFRAME_H1, \"h4\": mt.TIMEFRAME_H4, \n", - " \"d1\": mt.TIMEFRAME_D1\n", - " }\n", - " try:\n", - " rates = mt.copy_rates_from_pos(symbol, timeframes_dict[timeframe], 0, count)\n", - " if rates is None: \n", - " return None\n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " print(f\"Error getting rates: {e}\")\n", - " return None\n", - "\n", - "\n", - "def check_risk_limits(symbol, volume=None, order_type=\"buy\", max_risk_per_trade=0.01):\n", - " \"\"\"Risk Management\"\"\"\n", - " try:\n", - " account_info = mt.account_info()\n", - " if not account_info: \n", - " return False\n", - " balance, equity = account_info.balance, account_info.equity\n", - " if equity < balance * 0.8: \n", - " return False\n", - " return True\n", - " except: \n", - " return False\n", - "\n", - "\n", - "def market_order(symbol, volume, order_type, stoploss=0, take_profit=0, deviation=20):\n", - " \"\"\"Market Order Execution\"\"\"\n", - " try:\n", - " price_dict = {'buy': mt.symbol_info_tick(symbol).ask, 'sell': mt.symbol_info_tick(symbol).bid}\n", - " order_type_dict = {'buy': mt.ORDER_TYPE_BUY, 'sell': mt.ORDER_TYPE_SELL}\n", - " \n", - " request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": volume,\n", - " \"type\": order_type_dict[order_type],\n", - " \"price\": price_dict[order_type],\n", - " \"sl\": stoploss,\n", - " \"tp\": take_profit,\n", - " \"deviation\": deviation,\n", - " \"magic\": 234000,\n", - " \"comment\": strategy_name,\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC\n", - " }\n", - " return mt.order_send(request)\n", - " except Exception as e:\n", - " print(f\"Error in market order: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Helper functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6. Market Analysis Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def detect_market_regime(df, lookback=50):\n", - " \"\"\"Market Regime Detection\"\"\"\n", - " try:\n", - " adx_data = ta.adx(df['high'], df['low'], df['close'], length=14)\n", - " adx = adx_data['ADX_14'].iloc[-1] if adx_data is not None and 'ADX_14' in adx_data.columns else 25.0\n", - " \n", - " try:\n", - " bb = ta.bbands(df['close'], length=20)\n", - " if bb is not None and len(bb.columns) >= 3:\n", - " bb_cols = bb.columns.tolist()\n", - " bb_width = ((bb[bb_cols[0]] - bb[bb_cols[2]]) / bb[bb_cols[1]] * 100).iloc[-lookback:].mean()\n", - " else: \n", - " bb_width = 4.0\n", - " except: \n", - " bb_width = 4.0\n", - " \n", - " price_range = df['high'].iloc[-lookback:].max() - df['low'].iloc[-lookback:].min()\n", - " atr_avg = df['atr'].iloc[-lookback:].mean()\n", - " range_ratio = price_range / (atr_avg * lookback) if atr_avg > 0 else 1.0\n", - " vol_cluster = df['atr'].iloc[-10:].std() / df['atr'].iloc[-50:].mean() if len(df) >= 50 else 1.0\n", - " \n", - " if adx > 25 and range_ratio > 1.5:\n", - " regime, strength = 'trending', min(100, adx * 2)\n", - " elif vol_cluster > 1.5:\n", - " regime, strength = 'volatile', min(100, vol_cluster * 50)\n", - " else:\n", - " regime, strength = 'ranging', max(0, 100 - adx * 2)\n", - " \n", - " return {\n", - " 'regime': regime, 'strength': strength, 'adx': adx, \n", - " 'bb_width': bb_width, 'range_ratio': range_ratio, 'vol_cluster': vol_cluster\n", - " }\n", - " except Exception as e:\n", - " return {\n", - " 'regime': 'ranging', 'strength': 50, 'adx': 20, \n", - " 'bb_width': 4.0, 'range_ratio': 1.0, 'vol_cluster': 1.0\n", - " }\n", - "\n", - "\n", - "def calculate_adaptive_confidence_threshold_relaxed(regime_info, base_confidence=60):\n", - " \"\"\"\n", - " RELAXED Version: Niedrigere Schwellen für mehr Signale\n", - " \"\"\"\n", - " regime = regime_info['regime']\n", - " adx = regime_info['adx']\n", - " \n", - " if regime == 'trending':\n", - " if adx > 30:\n", - " return max(50, base_confidence - 20)\n", - " else:\n", - " return base_confidence - 15\n", - " elif regime == 'ranging':\n", - " return base_confidence + 10\n", - " elif regime == 'volatile':\n", - " return base_confidence + 15\n", - " \n", - " return base_confidence\n", - "\n", - "\n", - "def get_enhanced_trend(timeframe=\"H4\", lookback=150, symbol=\"XAUUSD\"):\n", - " \"\"\"Enhanced Trend Analysis\"\"\"\n", - " tf_map = {\"D1\": \"d1\", \"H4\": \"h4\", \"H1\": \"h1\", \"M30\": \"m30\", \"M15\": \"m15\", \"M5\": \"m5\"}\n", - " tf = tf_map.get(timeframe, timeframe.lower())\n", - " \n", - " try:\n", - " df = get_rates(tf, lookback, symbol)\n", - " if df is None or len(df) < 50: \n", - " return None\n", - " \n", - " df['close_smooth'] = savgol_filter(df['close'], min(15, len(df)//10), 3)\n", - " X = np.arange(len(df)).reshape(-1, 1)\n", - " y = df['close_smooth'].values\n", - " model = LinearRegression().fit(X, y)\n", - " slope = model.coef_[0]\n", - " \n", - " regime_info = detect_market_regime(df.iloc[-50:])\n", - " base_threshold = df['atr'].iloc[-1] * 0.0001\n", - " \n", - " if regime_info['regime'] == 'trending':\n", - " slope_threshold = base_threshold * 0.7\n", - " elif regime_info['regime'] == 'ranging':\n", - " slope_threshold = base_threshold * 1.5\n", - " else:\n", - " slope_threshold = base_threshold * 1.2\n", - " \n", - " trend = \"uptrend\" if slope > slope_threshold else \"downtrend\" if slope < -slope_threshold else \"sideways\"\n", - " trend_strength = abs(slope) / slope_threshold if slope_threshold > 0 else 0\n", - " \n", - " return {\n", - " \"trend\": trend, \"slope\": slope, \"slope_threshold\": slope_threshold,\n", - " \"trend_strength\": trend_strength, \"atr\": df['atr'].iloc[-1],\n", - " \"price\": df['close'].iloc[-1], \"regime_info\": regime_info\n", - " }\n", - " except Exception as e:\n", - " print(f\"Error in get_enhanced_trend: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Market analysis functions defined (with RELAXED thresholds)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 7. Extended Top-Down Analysis" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def extended_top_down_v2_adaptive(symbol=\"XAUUSD\", lookback=150):\n", - " \"\"\"\n", - " V1.6 Adaptive Complete Version:\n", - " - Position Control\n", - " - Relaxed Trading Logic\n", - " - Adaptive Rhythm Integration\n", - " \"\"\"\n", - " \n", - " timeframes = [\"D1\", \"H4\", \"H1\", \"M30\", \"M15\", \"M5\"]\n", - " trend_info = {}\n", - " \n", - " print(f\"🔍 Analyzing {symbol} with V1.6 ADAPTIVE COMPLETE parameters...\")\n", - " \n", - " # 1. Alle Timeframes analysieren\n", - " for tf in timeframes:\n", - " trend_info[tf] = get_enhanced_trend(tf, lookback, symbol)\n", - " if trend_info[tf] is None:\n", - " print(f\"⚠️ Keine Daten für {tf}\")\n", - " return None\n", - " \n", - " # 2. Market Regime aus H4 bestimmen\n", - " main_regime = trend_info[\"H4\"][\"regime_info\"]\n", - " \n", - " # 3. RELAXED Adaptive Confidence Threshold\n", - " adaptive_confidence_threshold = calculate_adaptive_confidence_threshold_relaxed(main_regime)\n", - " \n", - " # 4. Standard-Trend\n", - " d1_trend = trend_info[\"D1\"][\"trend\"]\n", - " h4_trend = trend_info[\"H4\"][\"trend\"]\n", - " d1_strength = trend_info[\"D1\"][\"trend_strength\"]\n", - " h4_strength = trend_info[\"H4\"][\"trend_strength\"]\n", - " \n", - " if d1_trend == h4_trend and d1_trend != \"sideways\":\n", - " standard_trend = d1_trend\n", - " standard_strength = (d1_strength * 0.6 + h4_strength * 0.4)\n", - " elif d1_strength > h4_strength * 1.5:\n", - " standard_trend = d1_trend\n", - " standard_strength = d1_strength * 0.8\n", - " elif h4_strength > d1_strength * 1.5:\n", - " standard_trend = h4_trend\n", - " standard_strength = h4_strength * 0.8\n", - " else:\n", - " standard_trend = \"sideways\"\n", - " standard_strength = 0\n", - " \n", - " # 5. RELAXED Fast-Trend\n", - " fast_timeframes = [\"H1\", \"M30\", \"M15\", \"M5\"]\n", - " fast_trends = [trend_info[tf][\"trend\"] for tf in fast_timeframes]\n", - " fast_strengths = [trend_info[tf][\"trend_strength\"] for tf in fast_timeframes]\n", - " \n", - " required_alignment = 2 # RELAXED: Immer 2 von 4\n", - " \n", - " trend_counts = {'uptrend': 0, 'downtrend': 0, 'sideways': 0}\n", - " weighted_strengths = {'uptrend': 0, 'downtrend': 0}\n", - " weights = [1.0, 0.8, 0.6, 0.4]\n", - " \n", - " for i, (trend, strength) in enumerate(zip(fast_trends, fast_strengths)):\n", - " trend_counts[trend] += 1\n", - " if trend != 'sideways':\n", - " weighted_strengths[trend] += strength * weights[i]\n", - " \n", - " max_count = max(trend_counts['uptrend'], trend_counts['downtrend'])\n", - " if max_count >= required_alignment:\n", - " if trend_counts['uptrend'] > trend_counts['downtrend']:\n", - " fast_trend = \"uptrend\"\n", - " elif trend_counts['downtrend'] > trend_counts['uptrend']:\n", - " fast_trend = \"downtrend\"\n", - " else:\n", - " fast_trend = \"uptrend\" if weighted_strengths['uptrend'] > weighted_strengths['downtrend'] else \"downtrend\"\n", - " else:\n", - " fast_trend = \"sideways\"\n", - " \n", - " # 6. Top-Down-Trend\n", - " if standard_trend == fast_trend and standard_trend != \"sideways\":\n", - " top_down_trend = standard_trend\n", - " combined_strength = (standard_strength + weighted_strengths.get(fast_trend, 0)) / 2\n", - " else:\n", - " top_down_trend = \"sideways\"\n", - " combined_strength = 0\n", - " \n", - " # 7. Enhanced Confidence\n", - " tf_weights = {\"D1\": 2.5, \"H4\": 2.0, \"H1\": 1.5, \"M30\": 1.0, \"M15\": 0.8, \"M5\": 0.6}\n", - " \n", - " weighted_matching = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"] \n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] == top_down_trend and trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " weighted_total = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"]\n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " confidence = round((weighted_matching / weighted_total) * 100, 2) if weighted_total > 0 else 0.0\n", - " \n", - " # 8. RELAXED Risk-Adjusted Signal Strength\n", - " atr = trend_info[\"M5\"][\"atr\"]\n", - " rrr = 2.5\n", - " risk_adjusted_strength = confidence * combined_strength * min(2.0, rrr)\n", - " \n", - " # 9. RELAXED Entry Signal\n", - " entry_signal = 0\n", - " signal_quality = \"none\"\n", - " min_strength = 80 # RELAXED: 80 statt 100\n", - " \n", - " if (top_down_trend != \"sideways\" and \n", - " confidence >= adaptive_confidence_threshold and\n", - " risk_adjusted_strength >= min_strength):\n", - " \n", - " entry_signal = 1 if top_down_trend == \"uptrend\" else -1\n", - " \n", - " # RELAXED Signal Quality\n", - " if confidence >= 80 and risk_adjusted_strength >= 130:\n", - " signal_quality = \"excellent\"\n", - " elif confidence >= 70 and risk_adjusted_strength >= 100:\n", - " signal_quality = \"good\"\n", - " else:\n", - " signal_quality = \"fair\"\n", - " \n", - " # 10. 🆕 Adaptive Rhythm Info\n", - " current_interval = rhythm_manager.current_interval\n", - " session = rhythm_manager.get_current_session()\n", - " \n", - " # 11. Debug Output\n", - " debug_data = []\n", - " for tf in timeframes:\n", - " info = trend_info[tf]\n", - " debug_data.append([\n", - " tf, info[\"trend\"], f\"{info['trend_strength']:.2f}\", \n", - " f\"{info['atr']:.4f}\", f\"{info['slope']:.6f}\", f\"{info['price']:.2f}\"\n", - " ])\n", - " \n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE Trend-Analyse für {symbol}\")\n", - " print(f\"⚡ Adaptive Interval: {current_interval} min | Session: {session.upper()}\")\n", - " print(f\"🎯 Market Regime: {main_regime['regime'].upper()} (Strength: {main_regime['strength']:.0f}%)\")\n", - " print(f\"🎚️ Adaptive Threshold: {adaptive_confidence_threshold}% (RELAXED)\")\n", - " print()\n", - " print(tabulate(debug_data, headers=[\"TF\", \"Trend\", \"Strength\", \"ATR\", \"Slope\", \"Price\"], tablefmt=\"psql\"))\n", - " print(f\"\\n➡️ Standard-Trend: {standard_trend} (Strength: {standard_strength:.2f})\")\n", - " print(f\"➡️ Fast-Trend: {fast_trend} (Required: {required_alignment}/4)\")\n", - " print(f\"➡️ Top-Down-Trend: {top_down_trend}\")\n", - " print(f\"➡️ Confidence: {confidence}% (Threshold: {adaptive_confidence_threshold}%)\")\n", - " print(f\"➡️ Risk-Adjusted Strength: {risk_adjusted_strength:.1f} (Min: {min_strength})\")\n", - " print(f\"➡️ Signal Quality: {signal_quality.upper()}\")\n", - " print(f\"\\n🚀 V1.6 Adaptive Complete: Full Features + Adaptive Rhythm\")\n", - " \n", - " return {\n", - " \"symbol\": symbol,\n", - " \"trend_info\": trend_info,\n", - " \"market_regime\": main_regime,\n", - " \"standard_trend\": standard_trend,\n", - " \"fast_trend\": fast_trend,\n", - " \"top_down_trend\": top_down_trend,\n", - " \"confidence\": confidence,\n", - " \"adaptive_threshold\": adaptive_confidence_threshold,\n", - " \"risk_adjusted_strength\": risk_adjusted_strength,\n", - " \"entry_signal\": entry_signal,\n", - " \"signal_quality\": signal_quality,\n", - " \"combined_strength\": combined_strength,\n", - " \"min_strength_used\": min_strength,\n", - " \"required_alignment\": required_alignment,\n", - " \"adaptive_interval\": current_interval,\n", - " \"session\": session\n", - " }\n", - "\n", - "\n", - "print(\"✅ V1.6 Adaptive Complete Top-Down Analysis defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 8. Entry Timing Optimization" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def check_pullback_entry(symbol, signal_info, timeframe=\"M5\"):\n", - " \"\"\"\n", - " Entry Timing Check - in Relaxed Version DISABLED per default\n", - " \"\"\"\n", - " if signal_info[\"entry_signal\"] == 0:\n", - " return False, \"No base signal\"\n", - " \n", - " try:\n", - " df = get_rates(timeframe.lower(), 50, symbol)\n", - " if df is None or len(df) < 20:\n", - " return False, \"Insufficient data\"\n", - " \n", - " df['ema21'] = df['close'].ewm(span=21).mean()\n", - " df['ema50'] = df['close'].ewm(span=50).mean()\n", - " \n", - " current_price = df['close'].iloc[-1]\n", - " ema21 = df['ema21'].iloc[-1]\n", - " ema50 = df['ema50'].iloc[-1]\n", - " signal_direction = signal_info[\"entry_signal\"]\n", - " \n", - " if signal_direction == 1: # Long\n", - " if current_price <= ema21 * 1.002 and ema21 > ema50:\n", - " return True, \"Pullback to EMA21 for Long\"\n", - " elif current_price <= ema21 * 0.998:\n", - " return True, \"Below EMA21 - Good Long Entry\"\n", - " elif signal_direction == -1: # Short\n", - " if current_price >= ema21 * 0.998 and ema21 < ema50:\n", - " return True, \"Pullback to EMA21 for Short\"\n", - " elif current_price >= ema21 * 1.002:\n", - " return True, \"Above EMA21 - Good Short Entry\"\n", - " \n", - " return False, \"Waiting for better entry timing\"\n", - " except Exception as e:\n", - " return True, \"Using immediate entry (fallback)\"\n", - "\n", - "\n", - "print(\"✅ Entry timing functions defined (DISABLED in Relaxed mode)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 9. Execute Trade Function" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def calculate_position_size(self, symbol, stop_loss_pips, max_risk_per_trade=0.02):\n", - " \"\"\"\n", - " Berechnet die Positionsgröße basierend auf Risiko\n", - " \"\"\"\n", - " account_info = mt.account_info()\n", - " if not account_info:\n", - " print(f\"⚠️ Keine Account-Info verfügbar, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " balance = account_info.balance\n", - " risk_amount = balance * max_risk_per_trade\n", - " \n", - " # Symbol-Info holen\n", - " symbol_info = mt.symbol_info(symbol)\n", - " if not symbol_info:\n", - " print(f\"⚠️ Keine Symbol-Info für {symbol}, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " # Pip-Wert berechnen\n", - " point = symbol_info.point\n", - " tick_value = symbol_info.trade_tick_value\n", - " tick_size = symbol_info.trade_tick_size\n", - " \n", - " # Volume berechnen\n", - " pip_value = (tick_value / tick_size) * point\n", - " volume = risk_amount / (stop_loss_pips * pip_value)\n", - " \n", - " # Auf erlaubte Volumenschritte runden\n", - " volume_min = symbol_info.volume_min\n", - " volume_max = symbol_info.volume_max\n", - " volume_step = symbol_info.volume_step\n", - " \n", - " volume = round(volume / volume_step) * volume_step\n", - " volume = max(volume_min, min(volume_max, volume))\n", - " \n", - " print(f\"💰 Position Sizing für {symbol}:\")\n", - " print(f\" Balance: ${balance:.2f}\")\n", - " print(f\" Risiko: ${risk_amount:.2f} ({max_risk_per_trade*100}%)\")\n", - " print(f\" Stop Loss: {stop_loss_pips:.2f} Pips\")\n", - " print(f\" Berechnetes Volume: {volume:.2f} Lots\")\n", - " \n", - " return volume" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#mt.symbol_info(symbol).volume_min\n", - "mt.symbol_info(symbol).volume_step" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def execute_trade_v2_adaptive(", - " symbol=\"XAUUSD\",", - " atr_mult=1.5,", - " base_confidence=60,", - " max_risk_per_trade=0.01,", - " risk_filter=True,", - " min_atr=0.0008,", - " use_pullback_entry=False, # DISABLED", - " max_positions=1,", - " strategy_name=\"TradingBot_V1.6\",", - " debug=True", - "):", - " \"\"\"", - " V1.6 Adaptive Complete Trade-Ausführung:", - " - Position Control", - " - Relaxed Parameter", - " - Adaptive Rhythm Integration", - " \"\"\"", - " ", - " # SCHRITT 1: POSITION CHECK", - " print(f\"\\n🔍 POSITION CHECK für {symbol} (V1.6 Adaptive Complete)\")", - " has_position, position_info = check_existing_positions(symbol, strategy_name)", - " ", - " if has_position and position_info['count'] >= max_positions:", - " if debug:", - " print(f\"🛑 TRADE BLOCKIERT: {position_info['count']}/{max_positions} Positionen aktiv\")", - " for pos in position_info['details']:", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"", - " print(f\" {pos['type']} @ {pos['price_open']} | {profit_emoji} {pos['profit']:.2f}\")", - " return None", - " ", - " print(f\"✅ Position-Check OK: {position_info['count']}/{max_positions}\")", - " ", - " # SCHRITT 2: Signal Analysis", - " signal_info = extended_top_down_v2_adaptive(symbol)", - " if signal_info is None:", - " print(\"❌ Signal-Analyse fehlgeschlagen\")", - " return None", - " ", - " entry_signal = signal_info[\"entry_signal\"]", - " confidence = signal_info[\"confidence\"]", - " adaptive_threshold = signal_info[\"adaptive_threshold\"]", - " signal_quality = signal_info[\"signal_quality\"]", - " market_regime = signal_info[\"market_regime\"]", - " ", - " # SCHRITT 3: Get Price/ATR", - " m5_info = signal_info[\"trend_info\"][\"M5\"]", - " price = m5_info[\"price\"]", - " atr = m5_info[\"atr\"]", - " ", - " # SCHRITT 4: Pre-checks", - " reason = \"\"", - " ", - " if confidence < adaptive_threshold:", - " reason = f\"Confidence {confidence}% < threshold {adaptive_threshold}%\"", - " elif entry_signal == 0:", - " reason = f\"No entry signal\"", - " elif price is None or atr is None:", - " reason = \"Price/ATR not available\"", - " elif risk_filter and atr < min_atr:", - " reason = f\"ATR {atr:.5f} < min_atr {min_atr}\"", - " else:", - " risk_ok = check_risk_limits(symbol, max_risk_per_trade=max_risk_per_trade)", - " if not risk_ok:", - " reason = \"Risk limits exceeded\"", - " ", - " # SCHRITT 5: Execute Trade", - " if not reason:", - " # Final Position Check", - " final_check, _ = check_existing_positions(symbol, strategy_name)", - " if final_check:", - " print(f\"🛑 Position wurde zwischen Checks eröffnet!\")", - " return None", - " ", - " # SL/TP Calculation", - " regime_mult = 1.0", - " if market_regime['regime'] == 'volatile':", - " regime_mult = 1.2", - " elif market_regime['regime'] == 'ranging':", - " regime_mult = 0.9", - " ", - " adjusted_atr_mult = atr_mult * regime_mult", - " ", - " if entry_signal == 1: # Long", - " stop_loss = price - adjusted_atr_mult * atr", - " take_profit = price + adjusted_atr_mult * atr * 2.5", - " else: # Short", - " stop_loss = price + adjusted_atr_mult * atr", - " take_profit = price - adjusted_atr_mult * atr * 2.5", - " ", - " # Position Sizing", - " account_info = mt.account_info()", - " if account_info:", - " balance = account_info.balance", - " risk_amount = balance * max_risk_per_trade", - " if symbol == \"XAUUSD\":", - " # 🎯 ADAPTIVE POSITION SIZING", - " if 'adv_position_mgr' in globals() and adv_position_mgr.adaptive_sizing:", - " volume = adv_position_mgr.adaptive_sizing.calculate_position_size(", - " confidence=confidence,", - " balance=balance,", - " stop_loss_distance=adjusted_atr_mult * atr * 10000, # Convert to pips", - " symbol=symbol", - " )", - " else:", - " volume = round(min(0.1, max(0.01, risk_amount / (adjusted_atr_mult * atr * 100))),2)", - " else:", - " volume = 0.01", - " else:", - " volume = 0.01", - " ", - " # Log Trade Info", - " print(f\"\\n🚀 V1.6 ADAPTIVE COMPLETE TRADE EXECUTION\")", - " print(f\"Direction: {'LONG' if entry_signal == 1 else 'SHORT'}\")", - " print(f\"Price: {price:.5f} | Volume: {volume:.2f}\")", - " print(f\"SL: {stop_loss:.5f} | TP: {take_profit:.5f}\")", - " print(f\"Confidence: {confidence}% | Quality: {signal_quality.upper()}\")", - " print(f\"Regime: {market_regime['regime'].upper()}\")", - " print(f\"Adaptive Interval: {signal_info['adaptive_interval']} min\")", - " print(f\"Session: {signal_info['session'].upper()}\")", - " ", - " # Execute", - " try:", - " order_result = market_order(", - " symbol=symbol,", - " volume=volume,", - " order_type=\"buy\" if entry_signal == 1 else \"sell\",", - " stoploss=stop_loss,", - " take_profit=take_profit", - " )", - " ", - " if order_result and order_result.retcode == mt.TRADE_RETCODE_DONE:", - " print(f\"✅ Trade erfolgreich! Ticket: {order_result.order}\")", - " ", - " # ==========================================", - " # LOG TRADE ENTRY (V1.8)", - " # ==========================================", - " try:", - " # Hole Position Info", - " positions = mt.positions_get(symbol=symbol)", - " if positions and infra:", - " position = positions[0]", - "", - " # Erstelle Trade Data", - " trade_data = {", - " 'ticket': position.ticket,", - " 'position_id': position.identifier,", - " 'symbol': symbol,", - " 'strategy_name': strategy_name,", - " 'type': 'BUY' if entry_signal == 1 else 'SELL',", - " 'volume': volume,", - " 'entry_price': position.price_open,", - " 'sl_price': position.sl,", - " 'tp_price': position.tp,", - " 'entry_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),", - " 'session': rhythm_manager.get_current_session(),", - " 'regime': market_regime['regime'],", - " 'quality': signal_quality,", - " 'confidence': confidence if 'confidence' in locals() else None,", - " 'timeframe_alignment': signal_info.get('required_alignment', 2),", - " 'risk_amount': risk_amount if 'risk_amount' in locals() else None,", - " 'risk_pct': max_risk_per_trade", - " }", - "", - " # Log to Database + Send Telegram", - " infra.log_trade_entry(trade_data)", - " logger.info(\"📱 Trade logged to DB + Telegram notification sent\")", - "", - " except Exception as e:", - " logger.error(f\"⚠️ Infrastructure logging failed: {e}\")", - " # ==========================================", - "", - "", - " # Verify & Log", - " new_check, new_info = check_existing_positions(symbol, strategy_name)", - " print(f\"📊 Positionen: {new_info['count']}\")", - " log_trade_performance_adaptive(signal_info, order_result)", - " else:", - " print(f\"❌ Trade failed: {order_result.comment if order_result else 'No result'}\")", - " ", - " return order_result", - " ", - " except Exception as e:", - " print(f\"❌ Execution failed: {e}\")", - " return None", - " ", - " else:", - " if debug:", - " print(f\"\\n⏸️ TRADE SKIPPED: {reason}\")", - " return None", - "", - "", - "print(\"✅ V1.6 Adaptive Complete Execute Trade defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 10. Performance Monitoring & Logging" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def log_trade_performance_adaptive(signal_info, order_result):\n", - " \"\"\"\n", - " Loggt Trade-Performance für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " trade_data = {\n", - " 'timestamp': datetime.now().isoformat(),\n", - " 'version': 'V1.6_Adaptive_Complete',\n", - " 'symbol': signal_info['symbol'],\n", - " 'entry_signal': signal_info['entry_signal'],\n", - " 'confidence': signal_info['confidence'],\n", - " 'adaptive_threshold': signal_info['adaptive_threshold'],\n", - " 'signal_quality': signal_info['signal_quality'],\n", - " 'market_regime': signal_info['market_regime']['regime'],\n", - " 'regime_strength': signal_info['market_regime']['strength'],\n", - " 'risk_adjusted_strength': signal_info['risk_adjusted_strength'],\n", - " 'adaptive_interval': signal_info['adaptive_interval'],\n", - " 'session': signal_info['session'],\n", - " 'relaxed_features': {\n", - " 'pullback_entry_disabled': True,\n", - " 'lower_confidence_threshold': True,\n", - " 'lower_min_strength': True,\n", - " 'fixed_tf_alignment': True\n", - " },\n", - " 'adaptive_features': {\n", - " 'adaptive_rhythm': True,\n", - " 'session_aware': True,\n", - " 'volatility_based': True\n", - " },\n", - " 'position_control_active': True,\n", - " 'order_result': str(order_result) if order_result else None\n", - " }\n", - " \n", - " try:\n", - " filename = f\"trade_performance_v16_{signal_info['symbol']}_{datetime.now().strftime('%Y%m')}.json\"\n", - " try:\n", - " with open(filename, 'r') as f: \n", - " data = json.load(f)\n", - " except FileNotFoundError: \n", - " data = []\n", - " data.append(trade_data)\n", - " with open(filename, 'w') as f: \n", - " json.dump(data, f, indent=2)\n", - " print(f\"📊 Performance logged to {filename}\")\n", - " except Exception as e:\n", - " print(f\"Warning: Could not log performance: {e}\")\n", - "\n", - "\n", - "def analyze_performance_adaptive(symbol=\"XAUUSD\", days_back=30):\n", - " \"\"\"\n", - " Analysiert Performance der V1.6 Adaptive Complete Version\n", - " \"\"\"\n", - " try:\n", - " filename = f\"trade_performance_v16_{symbol}_{datetime.now().strftime('%Y%m')}.json\"\n", - " \n", - " with open(filename, 'r') as f:\n", - " data = json.load(f)\n", - " \n", - " cutoff = datetime.now() - timedelta(days=days_back)\n", - " recent_trades = [\n", - " trade for trade in data \n", - " if datetime.fromisoformat(trade['timestamp']) > cutoff\n", - " ]\n", - " \n", - " if not recent_trades:\n", - " print(f\"No V1.6 trades in last {days_back} days\")\n", - " return\n", - " \n", - " total_trades = len(recent_trades)\n", - " \n", - " # Analysis by regime\n", - " by_regime = {}\n", - " for trade in recent_trades:\n", - " regime = trade['market_regime']\n", - " by_regime[regime] = by_regime.get(regime, 0) + 1\n", - " \n", - " # Analysis by interval\n", - " by_interval = {}\n", - " for trade in recent_trades:\n", - " interval = trade.get('adaptive_interval', 'unknown')\n", - " by_interval[interval] = by_interval.get(interval, 0) + 1\n", - " \n", - " # Analysis by session\n", - " by_session = {}\n", - " for trade in recent_trades:\n", - " session = trade.get('session', 'unknown')\n", - " by_session[session] = by_session.get(session, 0) + 1\n", - " \n", - " # Print results\n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE PERFORMANCE - Last {days_back} days\")\n", - " print(f\"Total Trades: {total_trades}\")\n", - " \n", - " print(f\"\\nBy Market Regime:\")\n", - " for regime, count in by_regime.items():\n", - " print(f\" {regime.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Adaptive Interval:\")\n", - " for interval, count in sorted(by_interval.items()):\n", - " print(f\" {interval} min: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Trading Session:\")\n", - " for session, count in by_session.items():\n", - " print(f\" {session.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " except Exception as e:\n", - " print(f\"Could not analyze performance: {e}\")\n", - "\n", - "\n", - "print(\"✅ Performance Monitoring functions defined (with adaptive features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 11. 🆕 Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# TRADING CHECK: SESSION FILTER + DRAWDOWN PROTECTION", - "# ==========================================", - "", - "from session_filter_patch import (", - " create_session_filtered_check,", - " SESSION_WHITELIST_CONFIG,", - " is_session_allowed", - ")", - "from drawdown_protection import create_protected_trading_check", - "", - "print(\"🔧 Setting up Trading Check...\")", - "", - "# Step 1: Create base session-filtered trading check", - "base_trading_check = create_session_filtered_check(", - " rhythm_manager=rhythm_manager,", - " execute_func=execute_trade_v2_adaptive,", - " symbol=symbol,", - " strategy_name=strategy_name,", - " max_positions=max_positions,", - " logger=logger,", - " datetime=datetime", - ")", - "", - "print(\"✅ Session Filter aktiviert!\")", - "print(\" Deaktivierte Sessions:\")", - "for session, enabled in SESSION_WHITELIST_CONFIG['enabled_sessions'].items():", - " status = \"✅ AKTIV\" if enabled else \"❌ DEAKTIVIERT\"", - " print(f\" • {session.upper():8s}: {status}\")", - "", - "# Step 2: Wrap with Drawdown Protection", - "adaptive_trading_check = create_protected_trading_check(infra, base_trading_check)", - "drawdown_protection = adaptive_trading_check.protection", - "", - "print(\"\\n🛡️ Drawdown Protection aktiviert!\")", - "print(f\" • Daily Loss Limit: ${drawdown_protection.max_daily_loss}\")", - "print(f\" • Weekly Loss Limit: ${drawdown_protection.max_weekly_loss}\")", - "print(f\" • Monthly Loss Limit: ${drawdown_protection.max_monthly_loss}\")", - "print(f\" • Max Consecutive Losses: {drawdown_protection.max_consecutive_losses}\")", - "print(f\" • Cooldown: {drawdown_protection.cooldown_hours}h\")", - "", - "print(\"\\n✅ Trading Check ist jetzt vollständig geschützt!\")", - "print(\" 📊 Session Filter: Aktiv\")", - "print(\" 🛡️ Drawdown Protection: Aktiv\")", - "" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# def adaptive_trading_check():\n", - "# \"\"\"\n", - "# 🆕 V1.6: Adaptive Trading Check\n", - "# Prüft basierend auf optimalem Intervall ob gehandelt werden soll\n", - "# \"\"\"\n", - "# try:\n", - "# optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "# current_minute = datetime.now().minute\n", - " \n", - "# # Trading nur zu berechneten Zeitpunkten\n", - "# if current_minute % optimal_interval == 0:\n", - "# logger.info(f\"\\n⏰ {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} - ADAPTIVE Check\")\n", - "# logger.info(f\"Intervall: {optimal_interval} min\")\n", - " \n", - "# # Führe Trading aus\n", - "# execute_trade_v2_adaptive(\n", - "# symbol=symbol,\n", - "# strategy_name=strategy_name,\n", - "# max_positions=max_positions\n", - "# )\n", - " \n", - "# except Exception as e:\n", - "# logger.error(f\"Fehler im Adaptive Trading Check: {e}\")\n", - "\n", - "\n", - "def print_status_report():\n", - " \"\"\"Status-Report\"\"\"\n", - " print(rhythm_manager.get_status_report())\n", - "\n", - "\n", - "# print(\"✅ Adaptive Scheduler functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 12. ✅ KORRIGIERT: Trading Configuration" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Zentrale Konfiguration (fehlte in ursprünglicher V1.6)\n", - "ADAPTIVE_COMPLETE_CONFIG = {\n", - " 'symbol': symbol,\n", - " 'atr_mult': 1.5,\n", - " 'base_confidence': 60, # RELAXED\n", - " 'max_risk_per_trade': 0.01,\n", - " 'risk_filter': True,\n", - " 'min_atr': 0.0008, # RELAXED\n", - " 'use_pullback_entry': False, # DISABLED\n", - " 'max_positions': max_positions,\n", - " 'strategy_name': strategy_name,\n", - " 'debug': True\n", - "}\n", - "\n", - "print(\"⚙️ V1.6 Adaptive Complete Configuration:\")\n", - "print(\"\\n🛡️ Position Control:\")\n", - "print(f\" Max Positions: {ADAPTIVE_COMPLETE_CONFIG['max_positions']}\")\n", - "print(f\" Strategy: {ADAPTIVE_COMPLETE_CONFIG['strategy_name']}\")\n", - "\n", - "print(\"\\n🚀 Relaxed Parameters:\")\n", - "print(f\" Base Confidence: {ADAPTIVE_COMPLETE_CONFIG['base_confidence']}%\")\n", - "print(f\" Min ATR: {ADAPTIVE_COMPLETE_CONFIG['min_atr']}\")\n", - "print(f\" Pullback Entry: {ADAPTIVE_COMPLETE_CONFIG['use_pullback_entry']}\")\n", - "\n", - "print(\"\\n⚡ Adaptive Features:\")\n", - "print(f\" Dynamic Intervals: 5/15/30 min\")\n", - "print(f\" Session-aware: Yes\")\n", - "print(f\" Volatility-based: Yes\")\n", - "\n", - "print(\"\\n✅ Configuration complete!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 13. ✅ KORRIGIERT: Status & Monitoring Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Umfassendes Status Monitoring (fehlte in V1.6)\n", - "def check_adaptive_bot_status():\n", - " \"\"\"\n", - " ✅ NEU: Kombiniertes Status-Check für V1.6 Adaptive Complete\n", - " Kombiniert Position Control + Adaptive Rhythm Status\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔍 V1.6 ADAPTIVE COMPLETE BOT STATUS\")\n", - " print(\"=\"*70)\n", - " \n", - " # System Status\n", - " print(\"\\n📡 SYSTEM STATUS:\")\n", - " print(f\" MT5 Connection: {'✅' if mt.terminal_info() else '❌'}\")\n", - " print(f\" Scheduler Running: {'✅' if scheduler.running else '❌'}\")\n", - " print(f\" Active Jobs: {len(scheduler.get_jobs())}\")\n", - " \n", - " # Adaptive Rhythm Status\n", - " print(\"\\n⚡ ADAPTIVE RHYTHM:\")\n", - " optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - " session = rhythm_manager.get_current_session()\n", - " df = rhythm_manager.get_market_data()\n", - " \n", - " if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\" Current Interval: {optimal_interval} min\")\n", - " print(f\" Trading Session: {session.upper()}\")\n", - " print(f\" ATR (H1): {atr:.2f}\")\n", - " print(f\" Volatility: {vol_level.upper()}\")\n", - " else:\n", - " print(\" ⚠️ Could not fetch market data\")\n", - " \n", - " # Position Status\n", - " print(\"\\n🛡️ POSITION CONTROL:\")\n", - " has_pos, pos_info = check_existing_positions(symbol, strategy_name)\n", - " print(f\" Active Positions: {pos_info['count']}/{max_positions}\")\n", - " print(f\" Trading Status: {'🛑 BLOCKED' if has_pos else '✅ READY'}\")\n", - " \n", - " if has_pos:\n", - " for i, pos in enumerate(pos_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\" Position {i}: {pos['type']} | {profit_emoji} {pos['profit']:.2f}\")\n", - " \n", - " # Signal Status\n", - " print(\"\\n📊 CURRENT SIGNAL:\")\n", - " try:\n", - " signal_info = extended_top_down_v2_adaptive(symbol)\n", - " if signal_info:\n", - " signal_dir = \"LONG\" if signal_info['entry_signal'] == 1 else \"SHORT\" if signal_info['entry_signal'] == -1 else \"NONE\"\n", - " print(f\" Signal: {signal_dir}\")\n", - " print(f\" Confidence: {signal_info['confidence']}%\")\n", - " print(f\" Threshold: {signal_info['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_info['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_info['market_regime']['regime'].upper()}\")\n", - " \n", - " would_trade = (signal_info['entry_signal'] != 0 and not has_pos)\n", - " print(f\" Would Trade: {'✅ YES' if would_trade else '❌ NO'}\")\n", - " else:\n", - " print(\" ⚠️ Signal analysis failed\")\n", - " except Exception as e:\n", - " print(f\" ❌ Error: {e}\")\n", - " \n", - " # Version Info\n", - " print(\"\\n🎉 VERSION INFO:\")\n", - " print(\" Version: V1.6 Adaptive Complete (CORRECTED)\")\n", - " print(\" Features: Position Control + Relaxed + Adaptive Rhythm\")\n", - " print(\" Status: Production-Ready ✅\")\n", - " print(\"=\"*70)\n", - "\n", - "\n", - "print(\"✅ Status monitoring function defined (COMPLETE with all features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 14. 🚀 Start Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Setup Scheduler", - "scheduler = BackgroundScheduler()", - "", - "# ADAPTIVE: Prüft jede Minute, handelt zu optimalen Zeitpunkten", - "scheduler.add_job(", - " func=adaptive_trading_check,", - " trigger='cron',", - " minute='*',", - " id='adaptive_trading_check'", - ")", - "", - "# Status-Report alle 30 Minuten", - "scheduler.add_job(", - " func=print_status_report,", - " trigger='cron',", - " minute='0,30',", - " id='status_report'", - ")", - "", - "# ==========================================", - "# SCHEDULED REPORTS (V1.8)", - "# ==========================================", - "", - "# Add daily & weekly reports", - "create_scheduled_reports(infra, scheduler)", - "", - "print(\"✅ Scheduled reports added:\")", - "print(\" 📊 Daily report: 22:00 UTC\")", - "print(\" 📈 Weekly report: Sunday 23:00 UTC\")", - "", - "", - "# ==========================================", - "# POSITION MONITOR JOB (V1.8)", - "# ==========================================", - "", - "# Add Position Monitor (checks every minute for closed positions)", - "scheduler.add_job(", - " func=position_monitor.check_open_positions,", - " trigger='interval',", - " minutes=1,", - " id='position_monitor'", - ")", - "", - "print(\"✅ Position Monitor job added:\")", - "print(\" 📊 Checks every minute for closed positions\")", - "", - "# ==========================================", - "", - "# ==========================================", - "", - "# Start scheduler", - "", - "# ==========================================", - "# ADVANCED POSITION MANAGEMENT JOB", - "# ==========================================", - "", - "# Trailing Stop + Partial TP Check (every minute)", - "scheduler.add_job(", - " func=lambda: adv_position_mgr.check_and_update_positions(symbol),", - " trigger='interval',", - " minutes=1,", - " id='advanced_position_management'", - ")", - "", - "print(\"✅ Advanced Position Management job added:\")", - "print(\" 📈 Checks for Trailing Stop updates every minute\")", - "print(\" 🎯 Checks for Partial TP triggers every minute\")", - "", - "scheduler.start()", - "logger.info(\"✅ Scheduler started with session filter + reports\")", - "", - "", - "# Starte Scheduler", - "#", - "# ==========================================", - "# ADVANCED POSITION MANAGEMENT JOB", - "# ==========================================", - "", - "# Trailing Stop + Partial TP Check (every minute)", - "scheduler.add_job(", - " func=lambda: adv_position_mgr.check_and_update_positions(symbol),", - " trigger='interval',", - " minutes=1,", - " id='advanced_position_management'", - ")", - "", - "print(\"✅ Advanced Position Management job added:\")", - "print(\" 📈 Checks for Trailing Stop updates every minute\")", - "print(\" 🎯 Checks for Partial TP triggers every minute\")", - "", - "scheduler.start()", - "", - "print(\"\\n\" + \"=\"*70)", - "print(\"🚀 TradingBot V1.6 ADAPTIVE COMPLETE - Scheduler gestartet!\")", - "print(\"=\"*70)", - "print(\"\\n🎯 Features aktiv:\")", - "print(\" ✅ Position Control System (Max 1 Position)\")", - "print(\" ✅ Relaxed Trading Parameters\")", - "print(\" ✅ ADAPTIVE RHYTHM (5/15/30 Min)\")", - "print(\" ✅ Volatilitäts-basiert (ATR)\")", - "print(\" ✅ Session-abhängig (Asian/London/NY/Overlap)\")", - "print(\" ✅ Complete Position Management\")", - "print(\" ✅ Umfassendes Status Monitoring\")", - "print(\"\\n⚡ Adaptive Intervall-Matrix:\")", - "print(\" • Overlap (13-16 UTC): 5-15min\")", - "print(\" • London/NY: 5-30min\")", - "print(\" • Asian: 15-30min\")", - "print(\"\\n📊 Status-Reports alle 30 Minuten\")", - "print(\"🔍 Trading-Checks zu adaptiven Zeitpunkten\")", - "print(\"=\"*70)", - "", - "# Zeige initialen Status", - "check_adaptive_bot_status()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 15. ✅ KORRIGIERT: Testing Suite" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Umfassende Testing Suite (fehlte in V1.6)\n", - "\n", - "# Test 1: Position Summary\n", - "print(\"🧪 TEST 1: Position Check\")\n", - "print(\"=\"*50)\n", - "get_position_summary(symbol, strategy_name)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 2: Adaptive Rhythm Status\n", - "print(\"\\n🧪 TEST 2: Adaptive Rhythm\")\n", - "print(\"=\"*50)\n", - "print_status_report()\n", - "\n", - "# Test Details\n", - "optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "session = rhythm_manager.get_current_session()\n", - "df = rhythm_manager.get_market_data()\n", - "\n", - "if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\"\\nDetails:\")\n", - " print(f\" Optimal Interval: {optimal_interval} min\")\n", - " print(f\" Session: {session}\")\n", - " print(f\" ATR: {atr:.2f}\")\n", - " print(f\" Volatility Level: {vol_level}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 3: Signal Analysis\n", - "print(\"\\n🧪 TEST 3: Signal Analysis\")\n", - "print(\"=\"*50)\n", - "\n", - "signal_result = extended_top_down_v2_adaptive(symbol)\n", - "\n", - "if signal_result:\n", - " print(f\"\\n🎯 SIGNAL SUMMARY:\")\n", - " print(f\" Entry Signal: {signal_result['entry_signal']}\")\n", - " print(f\" Confidence: {signal_result['confidence']}%\")\n", - " print(f\" Threshold: {signal_result['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_result['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_result['market_regime']['regime'].upper()}\")\n", - " print(f\" Adaptive Interval: {signal_result['adaptive_interval']} min\")\n", - " print(f\" Session: {signal_result['session'].upper()}\")\n", - " \n", - " if signal_result['entry_signal'] != 0:\n", - " direction = \"LONG\" if signal_result['entry_signal'] == 1 else \"SHORT\"\n", - " print(f\"\\n✅ TRADING SIGNAL: {direction}\")\n", - " else:\n", - " print(f\"\\n⏸️ NO TRADING SIGNAL\")\n", - "else:\n", - " print(\"❌ Signal analysis failed\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 4: Complete Bot Status\n", - "print(\"\\n🧪 TEST 4: Complete Bot Status\")\n", - "print(\"=\"*50)\n", - "check_adaptive_bot_status()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 5: Trade Execution Test (DRY RUN)\n", - "print(\"\\n🧪 TEST 5: Trade Execution (DRY RUN)\")\n", - "print(\"=\"*50)\n", - "print(\"\\nTesting trading logic without actual order...\")\n", - "\n", - "# Dies führt die komplette Trading-Logik aus,\n", - "# führt aber nur dann wirklich einen Trade aus,\n", - "# wenn alle Bedingungen erfüllt sind\n", - "\n", - "test_result = execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)\n", - "\n", - "if test_result:\n", - " print(\"\\n✅ Trade würde ausgeführt!\")\n", - "else:\n", - " print(\"\\n⏸️ Kein Trade - Bedingungen nicht erfüllt\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 16. ✅ KORRIGIERT: Management Control Panel" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "scheduler.get_jobs()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Management Control Panel (fehlte in V1.6)\n", - "def show_adaptive_management_options():\n", - " \"\"\"\n", - " ✅ NEU: Management UI für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔧 V1.6 ADAPTIVE COMPLETE - MANAGEMENT CONTROL PANEL\")\n", - " print(\"=\"*70)\n", - " \n", - " print(\"\\n📊 MONITORING:\")\n", - " print(\" 1. check_adaptive_bot_status() - Complete Status\")\n", - " print(\" 2. get_position_summary() - Position Overview\")\n", - " print(\" 3. print_status_report() - Adaptive Rhythm Status\")\n", - " print(\" 4. analyze_performance_adaptive() - Performance Analysis\")\n", - " \n", - " print(\"\\n🎯 ANALYSIS:\")\n", - " print(\" 5. extended_top_down_v2_adaptive() - Signal Analysis\")\n", - " print(\" 6. rhythm_manager.calculate_optimal_interval() - Current Interval\")\n", - " \n", - " print(\"\\n💼 POSITION MANAGEMENT:\")\n", - " print(\" 7. close_existing_positions(force_close=True) - Close All Positions\")\n", - " \n", - " print(\"\\n🚀 TRADING:\")\n", - " print(\" 8. execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG) - Manual Trade\")\n", - " \n", - " print(\"\\n⚙️ SCHEDULER CONTROL:\")\n", - " print(\" 9. scheduler.get_jobs() - Show Active Jobs\")\n", - " print(\" 10. scheduler.pause() - Pause Scheduler\")\n", - " print(\" 11. scheduler.resume() - Resume Scheduler\")\n", - " print(\" 12. scheduler.shutdown() - Stop Scheduler\")\n", - " \n", - " print(\"\\n🔧 CONFIGURATION:\")\n", - " print(\" 13. ADAPTIVE_COMPLETE_CONFIG - View Config\")\n", - " print(\" 14. rhythm_manager.atr_thresholds - ATR Settings\")\n", - " \n", - " print(\"\\n📝 QUICK COMMANDS:\")\n", - " print(\" • Status: check_adaptive_bot_status()\")\n", - " print(\" • Close: close_existing_positions(symbol, strategy_name, force_close=True)\")\n", - " print(\" • Stop: scheduler.shutdown()\")\n", - " \n", - " print(\"=\"*70)\n", - "\n", - "\n", - "show_adaptive_management_options()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Optional: Close positions manually\n", - "# UNCOMMENT to use:\n", - "# close_existing_positions(symbol, strategy_name, force_close=True)\n", - "\n", - "print(\"💡 To close positions manually, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Optional: ATR-Schwellenwerte anpassen\n", - "# UNCOMMENT to use:\n", - "# rhythm_manager.atr_thresholds = {\n", - "# 'high': 18.0,\n", - "# 'medium': 10.0,\n", - "# 'low': 5.0\n", - "# }\n", - "# print(\"✅ ATR thresholds updated\")\n", - "\n", - "print(\"💡 To adjust ATR thresholds, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Scheduler Control\n", - "print(\"🎛️ SCHEDULER CONTROL\")\n", - "print(\"\\n💡 To pause trading:\")\n", - "print(\"scheduler.pause()\")\n", - "print(\"\\n💡 To resume trading:\")\n", - "print(\"scheduler.resume()\")\n", - "print(\"\\n💡 To stop completely:\")\n", - "print(\"scheduler.shutdown()\")\n", - "\n", - "# UNCOMMENT to stop:\n", - "# scheduler.shutdown()\n", - "# print(\"🔴 Trading Bot stopped\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 17. 📈 V1.6 ADAPTIVE COMPLETE - Summary" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "print(\"\\n\" + \"=\"*70)\n", - "print(\"📈 TRADINGBOT V1.6 ADAPTIVE COMPLETE - SUMMARY\")\n", - "print(\"=\"*70)\n", - "\n", - "print(\"\\n🎉 VERSION: V1.6 ADAPTIVE COMPLETE (CORRECTED & READY!)\")\n", - "\n", - "print(\"\\n✅ ALLE FEATURES INTEGRIERT:\")\n", - "\n", - "print(\"\\n🛡️ Position Control (aus V1.5):\")\n", - "print(\" • Maximal 1 Trade gleichzeitig\")\n", - "print(\" • check_existing_positions()\")\n", - "print(\" • get_position_summary()\")\n", - "print(\" • close_existing_positions() ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🚀 Relaxed Trading Parameters (aus V1.5):\")\n", - "print(\" • 10-20% niedrigere Confidence-Schwellen\")\n", - "print(\" • Disabled Pullback Entry\")\n", - "print(\" • Relaxed Signal-Quality-Filter\")\n", - "print(\" • Niedrigere Min Risk-Adjusted Strength (80)\")\n", - "print(\" • Fixed 2/4 Timeframe Alignment\")\n", - "\n", - "print(\"\\n⚡ Adaptive Rhythm (NEU in V1.6):\")\n", - "print(\" • Adaptive Intervalle: 5/15/30 Minuten\")\n", - "print(\" • Volatilitäts-basiert (ATR)\")\n", - "print(\" • Session-abhängig (Asian/London/NY/Overlap)\")\n", - "print(\" • Intelligente Entscheidungs-Matrix\")\n", - "\n", - "print(\"\\n📊 Monitoring & Management (aus V1.5, angepasst):\")\n", - "print(\" • Performance Logging\")\n", - "print(\" • Performance Analysis\")\n", - "print(\" • Complete Status Monitoring ✅ KORRIGIERT!\")\n", - "print(\" • Management Control Panel ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🤖 Automation:\")\n", - "print(\" • APScheduler Integration\")\n", - "print(\" • Adaptive Trading Checks (jede Minute)\")\n", - "print(\" • Status Reports (alle 30 Min)\")\n", - "\n", - "print(\"\\n🧪 Testing Suite (aus V1.5):\")\n", - "print(\" • Position Tests ✅ KORRIGIERT!\")\n", - "print(\" • Signal Analysis Tests ✅ KORRIGIERT!\")\n", - "print(\" • Adaptive Rhythm Tests\")\n", - "print(\" • Complete Status Tests ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n⚙️ Configuration:\")\n", - "print(\" • ADAPTIVE_COMPLETE_CONFIG ✅ KORRIGIERT!\")\n", - "print(\" • Zentrale Parameter-Verwaltung\")\n", - "\n", - "print(\"\\n🎯 VORTEILE VON V1.6 ADAPTIVE COMPLETE:\")\n", - "print(\" ✅ Maximale Sicherheit (Position Control)\")\n", - "print(\" ✅ Maximale Gelegenheiten (Relaxed Parameters)\")\n", - "print(\" ✅ Maximale Effizienz (Adaptive Rhythm)\")\n", - "print(\" ✅ Vollständige Kontrolle (Complete Management)\")\n", - "print(\" ✅ Production-Ready!\")\n", - "\n", - "print(\"\\n📊 TYPISCHER 24H-ZYKLUS:\")\n", - "print(\" 00:00-08:00 (Asian) → 15-30 min\")\n", - "print(\" 08:00-13:00 (London) → 5-30 min\")\n", - "print(\" 13:00-16:00 (Overlap) → 5-15 min 🔥\")\n", - "print(\" 16:00-21:00 (NY) → 5-30 min\")\n", - "print(\" 21:00-00:00 (After) → 15-30 min\")\n", - "\n", - "print(\"\\n💡 HAUPTFUNKTIONEN:\")\n", - "print(\" • Status: check_adaptive_bot_status()\")\n", - "print(\" • Analyze: extended_top_down_v2_adaptive()\")\n", - "print(\" • Trade: execute_trade_v2_adaptive()\")\n", - "print(\" • Manage: show_adaptive_management_options()\")\n", - "\n", - "print(\"\\n🏆 V1.6 ADAPTIVE COMPLETE - ALLE FUNKTIONEN INTEGRIERT!\")\n", - "print(\" 🛡️ Sicherheit + 🚀 Aggressivität + ⚡ Intelligenz\")\n", - "print(\" Production-Ready & Fully Tested! ✅\")\n", - "\n", - "print(\"\\n\" + \"=\"*70)\n", - "print(\"🎊 Ready for intelligent, safe, and adaptive trading!\")\n", - "print(\"=\"*70)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2025-11-26 11:37:00,014 - INFO - Running job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" (scheduled at 2025-11-26 11:37:00+01:00)\n", - "2025-11-26 11:37:00,014 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-11-26 11:37:00,014 - INFO - Job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" executed successfully\n", - "2025-11-26 11:37:00,102 - INFO - Running job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" (scheduled at 2025-11-26 11:37:00+01:00)\n", - "2025-11-26 11:37:00,103 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-11-26 11:37:00,103 - INFO - Job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" executed successfully\n" - ] - } - ], - "source": [ - "# Prüfe ob Filter aktiv ist\n", - "print(SESSION_WHITELIST_CONFIG)\n", - "\n", - "# Teste manuell verschiedene Sessions\n", - "for session in ['asian', 'london', 'overlap', 'ny']:\n", - " allowed, reason = is_session_allowed(session)\n", - " emoji = \"✅\" if allowed else \"❌\"\n", - " print(f\"{emoji} {session}: {reason}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} \ No newline at end of file diff --git a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_scheduler_fix_20251209_160941.ipynb b/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_scheduler_fix_20251209_160941.ipynb deleted file mode 100644 index 9cbb6c8..0000000 --- a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_before_scheduler_fix_20251209_160941.ipynb +++ /dev/null @@ -1,2116 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# TradingBot V1.6 - Adaptive Complete Version 🚀🛡️⚡\n", - "\n", - "## 🆕 **NEU in V1.6: Adaptive Trading Rhythm**\n", - "- ⚡ **Adaptive Intervalle** - Automatische Anpassung: 5/15/30 Minuten\n", - "- 📊 **Volatilitäts-basiert** - ATR-gesteuerte Intervall-Wahl\n", - "- 🌍 **Session-abhängig** - Asian/London/NY/Overlap\n", - "- 🎯 **Intelligente Matrix** - Optimale Kombination aus Session + Volatilität\n", - "\n", - "## ✅ **Features aus V1.5 Complete Relaxed:**\n", - "- 🛡️ **Position Control System** - Maximal 1 Trade gleichzeitig\n", - "- 📊 **Performance Monitoring & Logging**\n", - "- 🤖 **APScheduler Integration** - Automatisierung\n", - "- 🔧 **Position Management Funktionen** - VOLLSTÄNDIG!\n", - "- 🚀 **Relaxed Parameter** - Niedrigere Schwellen für mehr Signale\n", - "- 🧪 **Umfassende Testing Suite**\n", - "- 🎛️ **Management Control Panel**\n", - "\n", - "## 🎯 **Adaptive Rhythm Schema:**\n", - "```\n", - "Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - "───────────┼──────────┼──────────────┼─────────────\n", - "Overlap │ 5min │ 15min │ 15min\n", - "London/NY │ 5min │ 15min │ 30min\n", - "Asian │ 15min │ 30min │ 30min\n", - "```\n", - "\n", - "## 🎉 **V1.6 COMPLETE - Das Beste aus beiden Welten:**\n", - "- ✅ Alle Funktionen aus V1.5\n", - "- ✅ Neue adaptive Features aus V1.6\n", - "- ✅ Production-Ready!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Imports und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Standard Imports\n", - "import pandas as pd\n", - "import numpy as np\n", - "import MetaTrader5 as mt\n", - "import pandas_ta as ta\n", - "from scipy.signal import savgol_filter, find_peaks\n", - "from sklearn.linear_model import LinearRegression\n", - "from tabulate import tabulate\n", - "from datetime import datetime, timedelta, time\n", - "import json\n", - "import keyring as kr\n", - "\n", - "# V1.6: Zusätzliche Imports für Adaptive Rhythm\n", - "import pytz\n", - "import logging\n", - "from apscheduler.schedulers.background import BackgroundScheduler\n", - "\n", - "# Setup Logging\n", - "logging.basicConfig(\n", - " level=logging.INFO,\n", - " format='%(asctime)s - %(levelname)s - %(message)s'\n", - ")\n", - "logger = logging.getLogger(__name__)\n", - "\n", - "print(\"✅ All imports successful - V1.6 Adaptive Complete (CORRECTED)\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INFRASTRUCTURE IMPORTS (V1.8)\n", - "# ==========================================\n", - "\n", - "from infrastructure_patch import (\n", - " TradingInfrastructure,\n", - " create_scheduled_reports\n", - ")\n", - "from trading_database import TradingDatabase\n", - "from telegram_notifier import TelegramNotifier\n", - "\n", - "print(\"✅ Infrastructure modules loaded\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. 🆕 Adaptive Rhythm Manager (NEU in V1.6)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "class AdaptiveRhythmManager:\n", - " \"\"\"\n", - " 🆕 V1.6 Feature: Adaptive Trading Rhythm\n", - " \n", - " Verwaltet adaptiven Trading-Rhythmus basierend auf:\n", - " - Marktvolatilität (ATR)\n", - " - Trading-Session (Asian/London/NY/Overlap)\n", - " - Marktregime\n", - " \"\"\"\n", - " \n", - " def __init__(self, symbol=\"XAUUSD\"):\n", - " self.symbol = symbol\n", - " self.current_interval = 5\n", - " \n", - " # Zeitintervalle in Minuten\n", - " self.intervals = {\n", - " 'fast': 5, # Hohe Volatilität, aktive Sessions\n", - " 'medium': 15, # Moderate Volatilität, Standard\n", - " 'slow': 30 # Niedrige Volatilität, ruhige Sessions\n", - " }\n", - " \n", - " # ATR-Schwellenwerte für XAUUSD (Gold)\n", - " self.atr_thresholds = {\n", - " 'high': 15.0, # Hohe Volatilität\n", - " 'medium': 8.0, # Moderate Volatilität\n", - " 'low': 5.0 # Niedrige Volatilität\n", - " }\n", - " \n", - " # Session-Zeiten (UTC)\n", - " self.sessions = {\n", - " 'asian': (time(0, 0), time(8, 0)), # 00:00-08:00 UTC\n", - " 'london': (time(8, 0), time(16, 0)), # 08:00-16:00 UTC\n", - " 'ny': (time(13, 0), time(21, 0)), # 13:00-21:00 UTC\n", - " 'overlap': (time(13, 0), time(16, 0)) # London-NY Overlap\n", - " }\n", - " \n", - " def get_current_session(self):\n", - " \"\"\"Ermittelt die aktuelle Trading-Session\"\"\"\n", - " now_utc = datetime.now(pytz.UTC).time()\n", - " \n", - " # Overlap hat höchste Priorität\n", - " if self.sessions['overlap'][0] <= now_utc <= self.sessions['overlap'][1]:\n", - " return 'overlap'\n", - " elif self.sessions['london'][0] <= now_utc < self.sessions['london'][1]:\n", - " return 'london'\n", - " elif self.sessions['ny'][0] <= now_utc < self.sessions['ny'][1]:\n", - " return 'ny'\n", - " return 'asian'\n", - " \n", - " def get_volatility_level(self, atr_value):\n", - " \"\"\"Klassifiziert die Volatilität basierend auf ATR\"\"\"\n", - " if atr_value >= self.atr_thresholds['high']:\n", - " return 'high'\n", - " elif atr_value >= self.atr_thresholds['medium']:\n", - " return 'medium'\n", - " return 'low'\n", - " \n", - " def get_market_data(self):\n", - " \"\"\"Hole Marktdaten für ATR-Analyse\"\"\"\n", - " try:\n", - " rates = mt.copy_rates_from_pos(self.symbol, mt.TIMEFRAME_H1, 0, 50)\n", - " if rates is None:\n", - " return None\n", - " \n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " logger.error(f\"Fehler beim Laden der Marktdaten: {e}\")\n", - " return None\n", - " \n", - " def calculate_optimal_interval(self):\n", - " \"\"\"Berechnet optimales Trading-Intervall\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is None:\n", - " return self.current_interval\n", - " \n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " optimal_interval = self._determine_interval(session, volatility)\n", - " \n", - " # Logge Änderungen\n", - " if optimal_interval != self.current_interval:\n", - " logger.info(f\"🔄 Rhythmus-Änderung: {self.current_interval}m → {optimal_interval}m\")\n", - " logger.info(f\" Session: {session}, Volatilität: {volatility} (ATR: {current_atr:.2f})\")\n", - " \n", - " self.current_interval = optimal_interval\n", - " return optimal_interval\n", - " \n", - " def _determine_interval(self, session, volatility):\n", - " \"\"\"\n", - " Intervall-Entscheidungs-Matrix:\n", - " \n", - " Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - " ───────────┼──────────┼──────────────┼─────────────\n", - " Overlap │ 5min │ 15min │ 15min\n", - " London/NY │ 5min │ 15min │ 30min\n", - " Asian │ 15min │ 30min │ 30min\n", - " \"\"\"\n", - " if session == 'overlap':\n", - " return self.intervals['fast'] if volatility == 'high' else self.intervals['medium']\n", - " elif session in ['london', 'ny']:\n", - " if volatility == 'high':\n", - " return self.intervals['fast']\n", - " elif volatility == 'medium':\n", - " return self.intervals['medium']\n", - " return self.intervals['slow']\n", - " else: # asian\n", - " return self.intervals['medium'] if volatility == 'high' else self.intervals['slow']\n", - " \n", - " def get_status_report(self):\n", - " \"\"\"Erstellt Status-Report\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is not None:\n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " else:\n", - " current_atr = 0\n", - " volatility = 'unknown'\n", - " \n", - " return f\"\"\"\n", - "╔════════════════════════════════════════════════════════╗\n", - "║ ADAPTIVE RHYTHM STATUS - {datetime.now().strftime('%H:%M:%S UTC')} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ Aktuelles Intervall: {self.current_interval:>2} Minuten ║\n", - "║ Trading Session: {session.upper():<15} ║\n", - "║ Volatilitätslevel: {volatility.upper():<15} ║\n", - "║ ATR (H1): {current_atr:>6.2f} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ INTERVALL-SCHEMA: ║\n", - "║ • Overlap (13-16 UTC): 5-15 Min (aktivste Phase) ║\n", - "║ • London/NY: 5-30 Min (volatilitätsabh.) ║\n", - "║ • Asian Session: 15-30 Min (ruhigere Phase) ║\n", - "╚════════════════════════════════════════════════════════╝\n", - "\"\"\"\n", - "\n", - "print(\"✅ Adaptive Rhythm Manager defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. MT5 Login und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# MT5 Login\n", - "mt.initialize()\n", - "login = 10800246\n", - "server = 'VantageInternational-Demo'\n", - "password = kr.get_password(server, str(login))\n", - "login_result = mt.login(login, password, server)\n", - "print(f\"Login successful: {login_result}\")\n", - "\n", - "# Trading Parameter\n", - "symbol = \"XAUUSD\"\n", - "strategy_name = \"TradingBot_V1.6\"\n", - "max_positions = 1\n", - "\n", - "print(f\"Symbol: {symbol}\")\n", - "print(f\"Strategy: {strategy_name}\")\n", - "print(f\"Max Positions: {max_positions}\")\n", - "print(f\"Version: V1.6 COMPLETE - Adaptive + Full Features! 🚀🛡️⚡\")\n", - "\n", - "# 🆕 Initialisiere Adaptive Rhythm Manager\n", - "rhythm_manager = AdaptiveRhythmManager(symbol)\n", - "print(\"\\n\" + rhythm_manager.get_status_report())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INITIALIZE INFRASTRUCTURE (V1.8)\n", - "# ==========================================\n", - "\n", - "print(\"🔧 Initializing Infrastructure...\")\n", - "\n", - "# Initialize Infrastructure\n", - "infra = TradingInfrastructure(\n", - " db_path=\"trading_bot.db\",\n", - " enable_telegram=True,\n", - " enable_database=True\n", - ")\n", - "\n", - "# Bot Started Notification\n", - "from session_filter_patch import SESSION_WHITELIST_CONFIG\n", - "\n", - "bot_config = {\n", - " 'version': 'V1.8',\n", - " 'enabled_sessions': SESSION_WHITELIST_CONFIG['enabled_sessions'],\n", - " 'base_confidence': SESSION_WHITELIST_CONFIG['base_confidence'],\n", - " 'max_risk_per_trade': SESSION_WHITELIST_CONFIG['max_risk_per_trade']\n", - "}\n", - "\n", - "infra.send_bot_started(bot_config)\n", - "\n", - "print(\"✅ Infrastructure ready!\")\n", - "print(f\" Database: {'✅' if infra.enable_database else '❌'}\")\n", - "print(f\" Telegram: {'✅' if infra.enable_telegram else '❌'}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# ADVANCED POSITION MANAGEMENT SETUP", - "# ==========================================", - "", - "from advanced_position_management import AdvancedPositionManager", - "", - "print(\"🎯 Initializing Advanced Position Management...\")", - "", - "# Initialize Manager with all features", - "adv_position_mgr = AdvancedPositionManager(", - " enable_adaptive_sizing=True, # ✅ Adaptive Position Sizing", - " enable_trailing_stop=True, # ✅ Trailing Stop-Loss", - " enable_partial_tp=True # ✅ Partial Take Profit", - ")", - "", - "print(\"✅ Advanced Position Management activated!\")", - "print(\" 📊 Adaptive Position Sizing: ACTIVE\")", - "print(\" • High Confidence (≥80%): 1.5x risk\")", - "print(\" • Medium Confidence (≥70%): 1.0x risk\")", - "print(\" • Low Confidence (<70%): 0.5x risk\")", - "print(\"\")", - "print(\" 📈 Trailing Stop-Loss: ACTIVE\")", - "print(\" • Break-Even at 50% progress to TP\")", - "print(\" • Lock 50% profit at 75% progress\")", - "print(\"\")", - "print(\" 🎯 Partial Take Profit: ACTIVE\")", - "print(\" • TP1 at 1.5R (close 50%)\")", - "print(\" • TP2 at 2.5R (let 50% run)\")", - "" - ] - }, - { - "cell_type": "code", - "metadata": {}, - "source": [ - "# ==========================================\n", - "# POSITION MONITOR SETUP (V1.8)\n", - "# ==========================================\n", - "\n", - "from position_monitor import PositionMonitor\n", - "\n", - "print(\"🔧 Initializing Position Monitor...\")\n", - "\n", - "# Create Position Monitor\n", - "position_monitor = PositionMonitor(infra.db, infra.telegram)\n", - "\n", - "print(\"✅ Position Monitor ready!\")\n", - "print(\" Will check for closed positions every minute\")\n", - "print(\" Closed trades will be automatically logged with:\")\n", - "print(\" • Exit price & time\")\n", - "print(\" • Profit/Loss calculation\")\n", - "print(\" • Exit reason (TP/SL/Manual)\")\n", - "print(\" • Telegram notification\")" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. 🛡️ Position Control Functions (VOLLSTÄNDIG!)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def check_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"\n", - " Überprüft ob bereits Positionen für das Symbol und die Strategie existieren\n", - " \"\"\"\n", - " try:\n", - " positions = mt.positions_get(symbol=symbol)\n", - " \n", - " if positions is None:\n", - " return False, {\"count\": 0, \"details\": []}\n", - " \n", - " strategy_positions = []\n", - " for pos in positions:\n", - " if strategy_name in pos.comment:\n", - " strategy_positions.append({\n", - " \"ticket\": pos.ticket,\n", - " \"type\": \"BUY\" if pos.type == 0 else \"SELL\",\n", - " \"volume\": pos.volume,\n", - " \"price_open\": pos.price_open,\n", - " \"profit\": pos.profit,\n", - " \"comment\": pos.comment,\n", - " \"time_open\": pd.to_datetime(pos.time, unit='s')\n", - " })\n", - " \n", - " has_position = len(strategy_positions) > 0\n", - " position_info = {\"count\": len(strategy_positions), \"details\": strategy_positions}\n", - " return has_position, position_info\n", - " \n", - " except Exception as e:\n", - " print(f\"Error checking positions: {e}\")\n", - " return False, {\"count\": 0, \"details\": []}\n", - "\n", - "\n", - "def get_position_summary(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"Position-Zusammenfassung\"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " print(f\"\\n📊 POSITION SUMMARY für {symbol} (V1.6 Adaptive Complete)\")\n", - " print(\"=\" * 60)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine aktiven Positionen - bereit für neuen Trade\")\n", - " return False\n", - " \n", - " print(f\"⚠️ {position_info['count']} aktive Position(en) gefunden:\")\n", - " for i, pos in enumerate(position_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\"\\n Position {i}:\")\n", - " print(f\" Ticket: {pos['ticket']}\")\n", - " print(f\" Typ: {pos['type']}\")\n", - " print(f\" Volumen: {pos['volume']}\")\n", - " print(f\" Eröffnungspreis: {pos['price_open']}\")\n", - " print(f\" Profit: {profit_emoji} {pos['profit']:.2f}\")\n", - " print(f\" Eröffnungszeit: {pos['time_open']}\")\n", - " \n", - " print(f\"\\n🛑 TRADING BLOCKIERT - Maximal {max_positions} Position erlaubt\")\n", - " return True\n", - "\n", - "\n", - "def close_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\", force_close=False):\n", - " \"\"\"\n", - " ✅ KORRIGIERT: Schließt bestehende Positionen (optional)\n", - " Diese Funktion fehlte in der ursprünglichen V1.6!\n", - " \"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine Positionen zum Schließen\")\n", - " return True\n", - " \n", - " if not force_close:\n", - " print(f\"⚠️ {position_info['count']} Position(en) gefunden. Verwende force_close=True zum Schließen.\")\n", - " return False\n", - " \n", - " print(f\"🔄 Schließe {position_info['count']} Position(en)...\")\n", - " \n", - " success_count = 0\n", - " for pos in position_info['details']:\n", - " try:\n", - " # Position schließen\n", - " close_request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": pos['volume'],\n", - " \"type\": mt.ORDER_TYPE_SELL if pos['type'] == \"BUY\" else mt.ORDER_TYPE_BUY,\n", - " \"position\": pos['ticket'],\n", - " \"price\": mt.symbol_info_tick(symbol).bid if pos['type'] == \"BUY\" else mt.symbol_info_tick(symbol).ask,\n", - " \"deviation\": 20,\n", - " \"magic\": 234000,\n", - " \"comment\": f\"Close {strategy_name}\",\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC,\n", - " }\n", - " \n", - " result = mt.order_send(close_request)\n", - " \n", - " if result.retcode == mt.TRADE_RETCODE_DONE:\n", - " print(f\"✅ Position {pos['ticket']} erfolgreich geschlossen\")\n", - " success_count += 1\n", - " else:\n", - " print(f\"❌ Fehler beim Schließen von Position {pos['ticket']}: {result.comment}\")\n", - " \n", - " except Exception as e:\n", - " print(f\"❌ Exception beim Schließen von Position {pos['ticket']}: {e}\")\n", - " \n", - " print(f\"📊 {success_count}/{len(position_info['details'])} Positionen erfolgreich geschlossen\")\n", - " return success_count == len(position_info['details'])\n", - "\n", - "\n", - "print(\"✅ Position Control functions defined (COMPLETE with close function!)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 5. Helper Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def get_rates(timeframe=\"h4\", count=200, symbol=\"XAUUSD\"):\n", - " \"\"\"Hole Kursdaten\"\"\"\n", - " timeframes_dict = {\n", - " \"m1\": mt.TIMEFRAME_M1, \"m5\": mt.TIMEFRAME_M5, \"m15\": mt.TIMEFRAME_M15,\n", - " \"m30\": mt.TIMEFRAME_M30, \"h1\": mt.TIMEFRAME_H1, \"h4\": mt.TIMEFRAME_H4, \n", - " \"d1\": mt.TIMEFRAME_D1\n", - " }\n", - " try:\n", - " rates = mt.copy_rates_from_pos(symbol, timeframes_dict[timeframe], 0, count)\n", - " if rates is None: \n", - " return None\n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " print(f\"Error getting rates: {e}\")\n", - " return None\n", - "\n", - "\n", - "def check_risk_limits(symbol, volume=None, order_type=\"buy\", max_risk_per_trade=0.01):\n", - " \"\"\"Risk Management\"\"\"\n", - " try:\n", - " account_info = mt.account_info()\n", - " if not account_info: \n", - " return False\n", - " balance, equity = account_info.balance, account_info.equity\n", - " if equity < balance * 0.8: \n", - " return False\n", - " return True\n", - " except: \n", - " return False\n", - "\n", - "\n", - "def market_order(symbol, volume, order_type, stoploss=0, take_profit=0, deviation=20):\n", - " \"\"\"Market Order Execution\"\"\"\n", - " try:\n", - " price_dict = {'buy': mt.symbol_info_tick(symbol).ask, 'sell': mt.symbol_info_tick(symbol).bid}\n", - " order_type_dict = {'buy': mt.ORDER_TYPE_BUY, 'sell': mt.ORDER_TYPE_SELL}\n", - " \n", - " request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": volume,\n", - " \"type\": order_type_dict[order_type],\n", - " \"price\": price_dict[order_type],\n", - " \"sl\": stoploss,\n", - " \"tp\": take_profit,\n", - " \"deviation\": deviation,\n", - " \"magic\": 234000,\n", - " \"comment\": strategy_name,\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC\n", - " }\n", - " return mt.order_send(request)\n", - " except Exception as e:\n", - " print(f\"Error in market order: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Helper functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6. Market Analysis Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def detect_market_regime(df, lookback=50):\n", - " \"\"\"Market Regime Detection\"\"\"\n", - " try:\n", - " adx_data = ta.adx(df['high'], df['low'], df['close'], length=14)\n", - " adx = adx_data['ADX_14'].iloc[-1] if adx_data is not None and 'ADX_14' in adx_data.columns else 25.0\n", - " \n", - " try:\n", - " bb = ta.bbands(df['close'], length=20)\n", - " if bb is not None and len(bb.columns) >= 3:\n", - " bb_cols = bb.columns.tolist()\n", - " bb_width = ((bb[bb_cols[0]] - bb[bb_cols[2]]) / bb[bb_cols[1]] * 100).iloc[-lookback:].mean()\n", - " else: \n", - " bb_width = 4.0\n", - " except: \n", - " bb_width = 4.0\n", - " \n", - " price_range = df['high'].iloc[-lookback:].max() - df['low'].iloc[-lookback:].min()\n", - " atr_avg = df['atr'].iloc[-lookback:].mean()\n", - " range_ratio = price_range / (atr_avg * lookback) if atr_avg > 0 else 1.0\n", - " vol_cluster = df['atr'].iloc[-10:].std() / df['atr'].iloc[-50:].mean() if len(df) >= 50 else 1.0\n", - " \n", - " if adx > 25 and range_ratio > 1.5:\n", - " regime, strength = 'trending', min(100, adx * 2)\n", - " elif vol_cluster > 1.5:\n", - " regime, strength = 'volatile', min(100, vol_cluster * 50)\n", - " else:\n", - " regime, strength = 'ranging', max(0, 100 - adx * 2)\n", - " \n", - " return {\n", - " 'regime': regime, 'strength': strength, 'adx': adx, \n", - " 'bb_width': bb_width, 'range_ratio': range_ratio, 'vol_cluster': vol_cluster\n", - " }\n", - " except Exception as e:\n", - " return {\n", - " 'regime': 'ranging', 'strength': 50, 'adx': 20, \n", - " 'bb_width': 4.0, 'range_ratio': 1.0, 'vol_cluster': 1.0\n", - " }\n", - "\n", - "\n", - "def calculate_adaptive_confidence_threshold_relaxed(regime_info, base_confidence=60):\n", - " \"\"\"\n", - " RELAXED Version: Niedrigere Schwellen für mehr Signale\n", - " \"\"\"\n", - " regime = regime_info['regime']\n", - " adx = regime_info['adx']\n", - " \n", - " if regime == 'trending':\n", - " if adx > 30:\n", - " return max(50, base_confidence - 20)\n", - " else:\n", - " return base_confidence - 15\n", - " elif regime == 'ranging':\n", - " return base_confidence + 10\n", - " elif regime == 'volatile':\n", - " return base_confidence + 15\n", - " \n", - " return base_confidence\n", - "\n", - "\n", - "def get_enhanced_trend(timeframe=\"H4\", lookback=150, symbol=\"XAUUSD\"):\n", - " \"\"\"Enhanced Trend Analysis\"\"\"\n", - " tf_map = {\"D1\": \"d1\", \"H4\": \"h4\", \"H1\": \"h1\", \"M30\": \"m30\", \"M15\": \"m15\", \"M5\": \"m5\"}\n", - " tf = tf_map.get(timeframe, timeframe.lower())\n", - " \n", - " try:\n", - " df = get_rates(tf, lookback, symbol)\n", - " if df is None or len(df) < 50: \n", - " return None\n", - " \n", - " df['close_smooth'] = savgol_filter(df['close'], min(15, len(df)//10), 3)\n", - " X = np.arange(len(df)).reshape(-1, 1)\n", - " y = df['close_smooth'].values\n", - " model = LinearRegression().fit(X, y)\n", - " slope = model.coef_[0]\n", - " \n", - " regime_info = detect_market_regime(df.iloc[-50:])\n", - " base_threshold = df['atr'].iloc[-1] * 0.0001\n", - " \n", - " if regime_info['regime'] == 'trending':\n", - " slope_threshold = base_threshold * 0.7\n", - " elif regime_info['regime'] == 'ranging':\n", - " slope_threshold = base_threshold * 1.5\n", - " else:\n", - " slope_threshold = base_threshold * 1.2\n", - " \n", - " trend = \"uptrend\" if slope > slope_threshold else \"downtrend\" if slope < -slope_threshold else \"sideways\"\n", - " trend_strength = abs(slope) / slope_threshold if slope_threshold > 0 else 0\n", - " \n", - " return {\n", - " \"trend\": trend, \"slope\": slope, \"slope_threshold\": slope_threshold,\n", - " \"trend_strength\": trend_strength, \"atr\": df['atr'].iloc[-1],\n", - " \"price\": df['close'].iloc[-1], \"regime_info\": regime_info\n", - " }\n", - " except Exception as e:\n", - " print(f\"Error in get_enhanced_trend: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Market analysis functions defined (with RELAXED thresholds)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 7. Extended Top-Down Analysis" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def extended_top_down_v2_adaptive(symbol=\"XAUUSD\", lookback=150):\n", - " \"\"\"\n", - " V1.6 Adaptive Complete Version:\n", - " - Position Control\n", - " - Relaxed Trading Logic\n", - " - Adaptive Rhythm Integration\n", - " \"\"\"\n", - " \n", - " timeframes = [\"D1\", \"H4\", \"H1\", \"M30\", \"M15\", \"M5\"]\n", - " trend_info = {}\n", - " \n", - " print(f\"🔍 Analyzing {symbol} with V1.6 ADAPTIVE COMPLETE parameters...\")\n", - " \n", - " # 1. Alle Timeframes analysieren\n", - " for tf in timeframes:\n", - " trend_info[tf] = get_enhanced_trend(tf, lookback, symbol)\n", - " if trend_info[tf] is None:\n", - " print(f\"⚠️ Keine Daten für {tf}\")\n", - " return None\n", - " \n", - " # 2. Market Regime aus H4 bestimmen\n", - " main_regime = trend_info[\"H4\"][\"regime_info\"]\n", - " \n", - " # 3. RELAXED Adaptive Confidence Threshold\n", - " adaptive_confidence_threshold = calculate_adaptive_confidence_threshold_relaxed(main_regime)\n", - " \n", - " # 4. Standard-Trend\n", - " d1_trend = trend_info[\"D1\"][\"trend\"]\n", - " h4_trend = trend_info[\"H4\"][\"trend\"]\n", - " d1_strength = trend_info[\"D1\"][\"trend_strength\"]\n", - " h4_strength = trend_info[\"H4\"][\"trend_strength\"]\n", - " \n", - " if d1_trend == h4_trend and d1_trend != \"sideways\":\n", - " standard_trend = d1_trend\n", - " standard_strength = (d1_strength * 0.6 + h4_strength * 0.4)\n", - " elif d1_strength > h4_strength * 1.5:\n", - " standard_trend = d1_trend\n", - " standard_strength = d1_strength * 0.8\n", - " elif h4_strength > d1_strength * 1.5:\n", - " standard_trend = h4_trend\n", - " standard_strength = h4_strength * 0.8\n", - " else:\n", - " standard_trend = \"sideways\"\n", - " standard_strength = 0\n", - " \n", - " # 5. RELAXED Fast-Trend\n", - " fast_timeframes = [\"H1\", \"M30\", \"M15\", \"M5\"]\n", - " fast_trends = [trend_info[tf][\"trend\"] for tf in fast_timeframes]\n", - " fast_strengths = [trend_info[tf][\"trend_strength\"] for tf in fast_timeframes]\n", - " \n", - " required_alignment = 2 # RELAXED: Immer 2 von 4\n", - " \n", - " trend_counts = {'uptrend': 0, 'downtrend': 0, 'sideways': 0}\n", - " weighted_strengths = {'uptrend': 0, 'downtrend': 0}\n", - " weights = [1.0, 0.8, 0.6, 0.4]\n", - " \n", - " for i, (trend, strength) in enumerate(zip(fast_trends, fast_strengths)):\n", - " trend_counts[trend] += 1\n", - " if trend != 'sideways':\n", - " weighted_strengths[trend] += strength * weights[i]\n", - " \n", - " max_count = max(trend_counts['uptrend'], trend_counts['downtrend'])\n", - " if max_count >= required_alignment:\n", - " if trend_counts['uptrend'] > trend_counts['downtrend']:\n", - " fast_trend = \"uptrend\"\n", - " elif trend_counts['downtrend'] > trend_counts['uptrend']:\n", - " fast_trend = \"downtrend\"\n", - " else:\n", - " fast_trend = \"uptrend\" if weighted_strengths['uptrend'] > weighted_strengths['downtrend'] else \"downtrend\"\n", - " else:\n", - " fast_trend = \"sideways\"\n", - " \n", - " # 6. Top-Down-Trend\n", - " if standard_trend == fast_trend and standard_trend != \"sideways\":\n", - " top_down_trend = standard_trend\n", - " combined_strength = (standard_strength + weighted_strengths.get(fast_trend, 0)) / 2\n", - " else:\n", - " top_down_trend = \"sideways\"\n", - " combined_strength = 0\n", - " \n", - " # 7. Enhanced Confidence\n", - " tf_weights = {\"D1\": 2.5, \"H4\": 2.0, \"H1\": 1.5, \"M30\": 1.0, \"M15\": 0.8, \"M5\": 0.6}\n", - " \n", - " weighted_matching = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"] \n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] == top_down_trend and trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " weighted_total = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"]\n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " confidence = round((weighted_matching / weighted_total) * 100, 2) if weighted_total > 0 else 0.0\n", - " \n", - " # 8. RELAXED Risk-Adjusted Signal Strength\n", - " atr = trend_info[\"M5\"][\"atr\"]\n", - " rrr = 2.5\n", - " risk_adjusted_strength = confidence * combined_strength * min(2.0, rrr)\n", - " \n", - " # 9. RELAXED Entry Signal\n", - " entry_signal = 0\n", - " signal_quality = \"none\"\n", - " min_strength = 80 # RELAXED: 80 statt 100\n", - " \n", - " if (top_down_trend != \"sideways\" and \n", - " confidence >= adaptive_confidence_threshold and\n", - " risk_adjusted_strength >= min_strength):\n", - " \n", - " entry_signal = 1 if top_down_trend == \"uptrend\" else -1\n", - " \n", - " # RELAXED Signal Quality\n", - " if confidence >= 80 and risk_adjusted_strength >= 130:\n", - " signal_quality = \"excellent\"\n", - " elif confidence >= 70 and risk_adjusted_strength >= 100:\n", - " signal_quality = \"good\"\n", - " else:\n", - " signal_quality = \"fair\"\n", - " \n", - " # 10. 🆕 Adaptive Rhythm Info\n", - " current_interval = rhythm_manager.current_interval\n", - " session = rhythm_manager.get_current_session()\n", - " \n", - " # 11. Debug Output\n", - " debug_data = []\n", - " for tf in timeframes:\n", - " info = trend_info[tf]\n", - " debug_data.append([\n", - " tf, info[\"trend\"], f\"{info['trend_strength']:.2f}\", \n", - " f\"{info['atr']:.4f}\", f\"{info['slope']:.6f}\", f\"{info['price']:.2f}\"\n", - " ])\n", - " \n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE Trend-Analyse für {symbol}\")\n", - " print(f\"⚡ Adaptive Interval: {current_interval} min | Session: {session.upper()}\")\n", - " print(f\"🎯 Market Regime: {main_regime['regime'].upper()} (Strength: {main_regime['strength']:.0f}%)\")\n", - " print(f\"🎚️ Adaptive Threshold: {adaptive_confidence_threshold}% (RELAXED)\")\n", - " print()\n", - " print(tabulate(debug_data, headers=[\"TF\", \"Trend\", \"Strength\", \"ATR\", \"Slope\", \"Price\"], tablefmt=\"psql\"))\n", - " print(f\"\\n➡️ Standard-Trend: {standard_trend} (Strength: {standard_strength:.2f})\")\n", - " print(f\"➡️ Fast-Trend: {fast_trend} (Required: {required_alignment}/4)\")\n", - " print(f\"➡️ Top-Down-Trend: {top_down_trend}\")\n", - " print(f\"➡️ Confidence: {confidence}% (Threshold: {adaptive_confidence_threshold}%)\")\n", - " print(f\"➡️ Risk-Adjusted Strength: {risk_adjusted_strength:.1f} (Min: {min_strength})\")\n", - " print(f\"➡️ Signal Quality: {signal_quality.upper()}\")\n", - " print(f\"\\n🚀 V1.6 Adaptive Complete: Full Features + Adaptive Rhythm\")\n", - " \n", - " return {\n", - " \"symbol\": symbol,\n", - " \"trend_info\": trend_info,\n", - " \"market_regime\": main_regime,\n", - " \"standard_trend\": standard_trend,\n", - " \"fast_trend\": fast_trend,\n", - " \"top_down_trend\": top_down_trend,\n", - " \"confidence\": confidence,\n", - " \"adaptive_threshold\": adaptive_confidence_threshold,\n", - " \"risk_adjusted_strength\": risk_adjusted_strength,\n", - " \"entry_signal\": entry_signal,\n", - " \"signal_quality\": signal_quality,\n", - " \"combined_strength\": combined_strength,\n", - " \"min_strength_used\": min_strength,\n", - " \"required_alignment\": required_alignment,\n", - " \"adaptive_interval\": current_interval,\n", - " \"session\": session\n", - " }\n", - "\n", - "\n", - "print(\"✅ V1.6 Adaptive Complete Top-Down Analysis defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 8. Entry Timing Optimization" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def check_pullback_entry(symbol, signal_info, timeframe=\"M5\"):\n", - " \"\"\"\n", - " Entry Timing Check - in Relaxed Version DISABLED per default\n", - " \"\"\"\n", - " if signal_info[\"entry_signal\"] == 0:\n", - " return False, \"No base signal\"\n", - " \n", - " try:\n", - " df = get_rates(timeframe.lower(), 50, symbol)\n", - " if df is None or len(df) < 20:\n", - " return False, \"Insufficient data\"\n", - " \n", - " df['ema21'] = df['close'].ewm(span=21).mean()\n", - " df['ema50'] = df['close'].ewm(span=50).mean()\n", - " \n", - " current_price = df['close'].iloc[-1]\n", - " ema21 = df['ema21'].iloc[-1]\n", - " ema50 = df['ema50'].iloc[-1]\n", - " signal_direction = signal_info[\"entry_signal\"]\n", - " \n", - " if signal_direction == 1: # Long\n", - " if current_price <= ema21 * 1.002 and ema21 > ema50:\n", - " return True, \"Pullback to EMA21 for Long\"\n", - " elif current_price <= ema21 * 0.998:\n", - " return True, \"Below EMA21 - Good Long Entry\"\n", - " elif signal_direction == -1: # Short\n", - " if current_price >= ema21 * 0.998 and ema21 < ema50:\n", - " return True, \"Pullback to EMA21 for Short\"\n", - " elif current_price >= ema21 * 1.002:\n", - " return True, \"Above EMA21 - Good Short Entry\"\n", - " \n", - " return False, \"Waiting for better entry timing\"\n", - " except Exception as e:\n", - " return True, \"Using immediate entry (fallback)\"\n", - "\n", - "\n", - "print(\"✅ Entry timing functions defined (DISABLED in Relaxed mode)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 9. Execute Trade Function" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def calculate_position_size(self, symbol, stop_loss_pips, max_risk_per_trade=0.02):\n", - " \"\"\"\n", - " Berechnet die Positionsgröße basierend auf Risiko\n", - " \"\"\"\n", - " account_info = mt.account_info()\n", - " if not account_info:\n", - " print(f\"⚠️ Keine Account-Info verfügbar, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " balance = account_info.balance\n", - " risk_amount = balance * max_risk_per_trade\n", - " \n", - " # Symbol-Info holen\n", - " symbol_info = mt.symbol_info(symbol)\n", - " if not symbol_info:\n", - " print(f\"⚠️ Keine Symbol-Info für {symbol}, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " # Pip-Wert berechnen\n", - " point = symbol_info.point\n", - " tick_value = symbol_info.trade_tick_value\n", - " tick_size = symbol_info.trade_tick_size\n", - " \n", - " # Volume berechnen\n", - " pip_value = (tick_value / tick_size) * point\n", - " volume = risk_amount / (stop_loss_pips * pip_value)\n", - " \n", - " # Auf erlaubte Volumenschritte runden\n", - " volume_min = symbol_info.volume_min\n", - " volume_max = symbol_info.volume_max\n", - " volume_step = symbol_info.volume_step\n", - " \n", - " volume = round(volume / volume_step) * volume_step\n", - " volume = max(volume_min, min(volume_max, volume))\n", - " \n", - " print(f\"💰 Position Sizing für {symbol}:\")\n", - " print(f\" Balance: ${balance:.2f}\")\n", - " print(f\" Risiko: ${risk_amount:.2f} ({max_risk_per_trade*100}%)\")\n", - " print(f\" Stop Loss: {stop_loss_pips:.2f} Pips\")\n", - " print(f\" Berechnetes Volume: {volume:.2f} Lots\")\n", - " \n", - " return volume" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#mt.symbol_info(symbol).volume_min\n", - "mt.symbol_info(symbol).volume_step" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def execute_trade_v2_adaptive(", - " symbol=\"XAUUSD\",", - " atr_mult=1.5,", - " base_confidence=60,", - " max_risk_per_trade=0.01,", - " risk_filter=True,", - " min_atr=0.0008,", - " use_pullback_entry=False, # DISABLED", - " max_positions=1,", - " strategy_name=\"TradingBot_V1.6\",", - " debug=True", - "):", - " \"\"\"", - " V1.6 Adaptive Complete Trade-Ausführung:", - " - Position Control", - " - Relaxed Parameter", - " - Adaptive Rhythm Integration", - " \"\"\"", - " ", - " # SCHRITT 1: POSITION CHECK", - " print(f\"\\n🔍 POSITION CHECK für {symbol} (V1.6 Adaptive Complete)\")", - " has_position, position_info = check_existing_positions(symbol, strategy_name)", - " ", - " if has_position and position_info['count'] >= max_positions:", - " if debug:", - " print(f\"🛑 TRADE BLOCKIERT: {position_info['count']}/{max_positions} Positionen aktiv\")", - " for pos in position_info['details']:", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"", - " print(f\" {pos['type']} @ {pos['price_open']} | {profit_emoji} {pos['profit']:.2f}\")", - " return None", - " ", - " print(f\"✅ Position-Check OK: {position_info['count']}/{max_positions}\")", - " ", - " # SCHRITT 2: Signal Analysis", - " signal_info = extended_top_down_v2_adaptive(symbol)", - " if signal_info is None:", - " print(\"❌ Signal-Analyse fehlgeschlagen\")", - " return None", - " ", - " entry_signal = signal_info[\"entry_signal\"]", - " confidence = signal_info[\"confidence\"]", - " adaptive_threshold = signal_info[\"adaptive_threshold\"]", - " signal_quality = signal_info[\"signal_quality\"]", - " market_regime = signal_info[\"market_regime\"]", - " ", - " # SCHRITT 3: Get Price/ATR", - " m5_info = signal_info[\"trend_info\"][\"M5\"]", - " price = m5_info[\"price\"]", - " atr = m5_info[\"atr\"]", - " ", - " # SCHRITT 4: Pre-checks", - " reason = \"\"", - " ", - " if confidence < adaptive_threshold:", - " reason = f\"Confidence {confidence}% < threshold {adaptive_threshold}%\"", - " elif entry_signal == 0:", - " reason = f\"No entry signal\"", - " elif price is None or atr is None:", - " reason = \"Price/ATR not available\"", - " elif risk_filter and atr < min_atr:", - " reason = f\"ATR {atr:.5f} < min_atr {min_atr}\"", - " else:", - " risk_ok = check_risk_limits(symbol, max_risk_per_trade=max_risk_per_trade)", - " if not risk_ok:", - " reason = \"Risk limits exceeded\"", - " ", - " # SCHRITT 5: Execute Trade", - " if not reason:", - " # Final Position Check", - " final_check, _ = check_existing_positions(symbol, strategy_name)", - " if final_check:", - " print(f\"🛑 Position wurde zwischen Checks eröffnet!\")", - " return None", - " ", - " # SL/TP Calculation", - " regime_mult = 1.0", - " if market_regime['regime'] == 'volatile':", - " regime_mult = 1.2", - " elif market_regime['regime'] == 'ranging':", - " regime_mult = 0.9", - " ", - " adjusted_atr_mult = atr_mult * regime_mult", - " ", - " if entry_signal == 1: # Long", - " stop_loss = price - adjusted_atr_mult * atr", - " take_profit = price + adjusted_atr_mult * atr * 2.5", - " else: # Short", - " stop_loss = price + adjusted_atr_mult * atr", - " take_profit = price - adjusted_atr_mult * atr * 2.5", - " ", - " # Position Sizing", - " account_info = mt.account_info()", - " if account_info:", - " balance = account_info.balance", - " risk_amount = balance * max_risk_per_trade", - " if symbol == \"XAUUSD\":", - " # 🎯 ADAPTIVE POSITION SIZING", - " if 'adv_position_mgr' in globals() and adv_position_mgr.adaptive_sizing:", - " volume = adv_position_mgr.adaptive_sizing.calculate_position_size(", - " confidence=confidence,", - " balance=balance,", - " stop_loss_distance=adjusted_atr_mult * atr * 10000, # Convert to pips", - " symbol=symbol", - " )", - " else:", - " volume = round(min(0.1, max(0.01, risk_amount / (adjusted_atr_mult * atr * 100))),2)", - " else:", - " volume = 0.01", - " else:", - " volume = 0.01", - " ", - " # Log Trade Info", - " print(f\"\\n🚀 V1.6 ADAPTIVE COMPLETE TRADE EXECUTION\")", - " print(f\"Direction: {'LONG' if entry_signal == 1 else 'SHORT'}\")", - " print(f\"Price: {price:.5f} | Volume: {volume:.2f}\")", - " print(f\"SL: {stop_loss:.5f} | TP: {take_profit:.5f}\")", - " print(f\"Confidence: {confidence}% | Quality: {signal_quality.upper()}\")", - " print(f\"Regime: {market_regime['regime'].upper()}\")", - " print(f\"Adaptive Interval: {signal_info['adaptive_interval']} min\")", - " print(f\"Session: {signal_info['session'].upper()}\")", - " ", - " # Execute", - " try:", - " order_result = market_order(", - " symbol=symbol,", - " volume=volume,", - " order_type=\"buy\" if entry_signal == 1 else \"sell\",", - " stoploss=stop_loss,", - " take_profit=take_profit", - " )", - " ", - " if order_result and order_result.retcode == mt.TRADE_RETCODE_DONE:", - " print(f\"✅ Trade erfolgreich! Ticket: {order_result.order}\")", - " ", - " # ==========================================", - " # LOG TRADE ENTRY (V1.8)", - " # ==========================================", - " try:", - " # Hole Position Info", - " positions = mt.positions_get(symbol=symbol)", - " if positions and infra:", - " position = positions[0]", - "", - " # Erstelle Trade Data", - " trade_data = {", - " 'ticket': position.ticket,", - " 'position_id': position.identifier,", - " 'symbol': symbol,", - " 'strategy_name': strategy_name,", - " 'type': 'BUY' if entry_signal == 1 else 'SELL',", - " 'volume': volume,", - " 'entry_price': position.price_open,", - " 'sl_price': position.sl,", - " 'tp_price': position.tp,", - " 'entry_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),", - " 'session': rhythm_manager.get_current_session(),", - " 'regime': market_regime['regime'],", - " 'quality': signal_quality,", - " 'confidence': confidence if 'confidence' in locals() else None,", - " 'timeframe_alignment': signal_info.get('required_alignment', 2),", - " 'risk_amount': risk_amount if 'risk_amount' in locals() else None,", - " 'risk_pct': max_risk_per_trade", - " }", - "", - " # Log to Database + Send Telegram", - " infra.log_trade_entry(trade_data)", - " logger.info(\"📱 Trade logged to DB + Telegram notification sent\")", - "", - " except Exception as e:", - " logger.error(f\"⚠️ Infrastructure logging failed: {e}\")", - " # ==========================================", - "", - "", - " # Verify & Log", - " new_check, new_info = check_existing_positions(symbol, strategy_name)", - " print(f\"📊 Positionen: {new_info['count']}\")", - " log_trade_performance_adaptive(signal_info, order_result)", - " else:", - " print(f\"❌ Trade failed: {order_result.comment if order_result else 'No result'}\")", - " ", - " return order_result", - " ", - " except Exception as e:", - " print(f\"❌ Execution failed: {e}\")", - " return None", - " ", - " else:", - " if debug:", - " print(f\"\\n⏸️ TRADE SKIPPED: {reason}\")", - " return None", - "", - "", - "print(\"✅ V1.6 Adaptive Complete Execute Trade defined\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# 🔥 FIX #1: RANGING FILTER WRAPPER (09.12.2025)", - "# ==========================================", - "", - "# Original function wird wrapped", - "_original_execute_trade_v2_adaptive = execute_trade_v2_adaptive", - "", - "def execute_trade_v2_adaptive_with_ranging_filter(", - " symbol=\"XAUUSD\",", - " atr_mult=1.5,", - " base_confidence=60,", - " max_risk_per_trade=0.01,", - " risk_filter=True,", - " min_atr=0.0008,", - " use_pullback_entry=False,", - " max_positions=1,", - " strategy_name=\"TradingBot_V1.6\",", - " debug=True):", - " \"\"\"", - " Wrapper für execute_trade_v2_adaptive mit Ranging Filter", - " Blocks trading in ranging markets - they cause 100% of losses!", - " \"\"\"", - "", - " # Quick check: Get signal info first", - " signal_info = extended_top_down_v2_adaptive(symbol)", - " if signal_info is None:", - " return None", - "", - " market_regime = signal_info.get(\"market_regime\", {})", - " regime = market_regime.get('regime', 'unknown')", - " adx = market_regime.get('adx', 0)", - "", - " # 🛑 RANGING FILTER - Block ALL ranging market trades", - " if regime == 'ranging':", - " if debug:", - " print(f\"\\n🛑 TRADE BLOCKIERT: Ranging Market!\")", - " print(f\" ADX: {adx:.1f} (< 25 = Ranging)\")", - " print(f\" 📊 Ranging Performance: 0% Win Rate, 20 consecutive losses\")", - " print(f\" ✅ Filter is protecting you from losses!\")", - " return None", - "", - " # Additional safety: Even in trending, ADX must be > 25", - " if regime == 'trending' and adx < 25:", - " if debug:", - " print(f\"\\n🛑 TRADE BLOCKIERT: Weak Trend!\")", - " print(f\" ADX: {adx:.1f} (< 25 = too weak)\")", - " return None", - "", - " # ✅ Regime check passed - execute original function", - " if debug:", - " print(f\"✅ REGIME CHECK PASSED: {regime.upper()} (ADX {adx:.1f})\")", - "", - " return _original_execute_trade_v2_adaptive(", - " symbol=symbol,", - " atr_mult=atr_mult,", - " base_confidence=base_confidence,", - " max_risk_per_trade=max_risk_per_trade,", - " risk_filter=risk_filter,", - " min_atr=min_atr,", - " use_pullback_entry=use_pullback_entry,", - " max_positions=max_positions,", - " strategy_name=strategy_name,", - " debug=debug", - " )", - "", - "# Replace original with wrapped version", - "execute_trade_v2_adaptive = execute_trade_v2_adaptive_with_ranging_filter", - "", - "print(\"✅ Ranging Filter activated!\")", - "print(\" 🛑 Blocks ALL ranging market trades\")", - "print(\" ✅ Only allows trending markets with ADX > 25\")", - "" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# 🔥 FIX #2: POSITION MONITOR DB LOGGING (09.12.2025)", - "# ==========================================", - "", - "# Wrap check_open_positions to add DB logging", - "if 'check_open_positions' in globals():", - " _original_check_open_positions = check_open_positions", - "", - " def check_open_positions_with_db_logging():", - " \"\"\"", - " Enhanced position monitor that writes exits to database", - " \"\"\"", - " from datetime import datetime", - "", - " # Get current open positions from MT5", - " positions = mt.positions_get(symbol=symbol)", - "", - " if not positions or len(positions) == 0:", - " # Check if we have positions in DB that should be closed", - " if 'db' in globals():", - " try:", - " open_trades_in_db = db.get_open_trades()", - "", - " for trade in open_trades_in_db:", - " ticket = trade['ticket']", - "", - " # Check if this position is in MT5 history (closed)", - " deals = mt.history_deals_get(ticket=ticket)", - " if deals and len(deals) > 0:", - " # Position was closed - log to DB", - " last_deal = deals[-1]", - "", - " db.close_trade(", - " ticket=ticket,", - " exit_price=last_deal.price,", - " exit_time=datetime.fromtimestamp(last_deal.time),", - " profit=last_deal.profit,", - " status='closed',", - " exit_reason='mt5_detected',", - " commission=last_deal.commission,", - " swap=last_deal.swap", - " )", - "", - " logger.info(f\"💾 Position #{ticket} exit logged to DB (profit: ${last_deal.profit:.2f})\")", - "", - " except Exception as e:", - " logger.error(f\"⚠️ DB logging error: {e}\")", - "", - " # Call original function", - " return _original_check_open_positions()", - "", - " # Replace", - " check_open_positions = check_open_positions_with_db_logging", - " print(\"✅ Position Monitor DB logging activated!\")", - " print(\" 💾 Exits will be written to SQLite database\")", - " print(\" 📊 Drawdown Protection will work correctly\")", - "else:", - " print(\"⚠️ check_open_positions not found - skipping Position Monitor fix\")", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 10. Performance Monitoring & Logging" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def log_trade_performance_adaptive(signal_info, order_result):\n", - " \"\"\"\n", - " Loggt Trade-Performance für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " trade_data = {\n", - " 'timestamp': datetime.now().isoformat(),\n", - " 'version': 'V1.6_Adaptive_Complete',\n", - " 'symbol': signal_info['symbol'],\n", - " 'entry_signal': signal_info['entry_signal'],\n", - " 'confidence': signal_info['confidence'],\n", - " 'adaptive_threshold': signal_info['adaptive_threshold'],\n", - " 'signal_quality': signal_info['signal_quality'],\n", - " 'market_regime': signal_info['market_regime']['regime'],\n", - " 'regime_strength': signal_info['market_regime']['strength'],\n", - " 'risk_adjusted_strength': signal_info['risk_adjusted_strength'],\n", - " 'adaptive_interval': signal_info['adaptive_interval'],\n", - " 'session': signal_info['session'],\n", - " 'relaxed_features': {\n", - " 'pullback_entry_disabled': True,\n", - " 'lower_confidence_threshold': True,\n", - " 'lower_min_strength': True,\n", - " 'fixed_tf_alignment': True\n", - " },\n", - " 'adaptive_features': {\n", - " 'adaptive_rhythm': True,\n", - " 'session_aware': True,\n", - " 'volatility_based': True\n", - " },\n", - " 'position_control_active': True,\n", - " 'order_result': str(order_result) if order_result else None\n", - " }\n", - " \n", - " try:\n", - " filename = f\"trade_performance_v16_{signal_info['symbol']}_{datetime.now().strftime('%Y%m')}.json\"\n", - " try:\n", - " with open(filename, 'r') as f: \n", - " data = json.load(f)\n", - " except FileNotFoundError: \n", - " data = []\n", - " data.append(trade_data)\n", - " with open(filename, 'w') as f: \n", - " json.dump(data, f, indent=2)\n", - " print(f\"📊 Performance logged to {filename}\")\n", - " except Exception as e:\n", - " print(f\"Warning: Could not log performance: {e}\")\n", - "\n", - "\n", - "def analyze_performance_adaptive(symbol=\"XAUUSD\", days_back=30):\n", - " \"\"\"\n", - " Analysiert Performance der V1.6 Adaptive Complete Version\n", - " \"\"\"\n", - " try:\n", - " filename = f\"trade_performance_v16_{symbol}_{datetime.now().strftime('%Y%m')}.json\"\n", - " \n", - " with open(filename, 'r') as f:\n", - " data = json.load(f)\n", - " \n", - " cutoff = datetime.now() - timedelta(days=days_back)\n", - " recent_trades = [\n", - " trade for trade in data \n", - " if datetime.fromisoformat(trade['timestamp']) > cutoff\n", - " ]\n", - " \n", - " if not recent_trades:\n", - " print(f\"No V1.6 trades in last {days_back} days\")\n", - " return\n", - " \n", - " total_trades = len(recent_trades)\n", - " \n", - " # Analysis by regime\n", - " by_regime = {}\n", - " for trade in recent_trades:\n", - " regime = trade['market_regime']\n", - " by_regime[regime] = by_regime.get(regime, 0) + 1\n", - " \n", - " # Analysis by interval\n", - " by_interval = {}\n", - " for trade in recent_trades:\n", - " interval = trade.get('adaptive_interval', 'unknown')\n", - " by_interval[interval] = by_interval.get(interval, 0) + 1\n", - " \n", - " # Analysis by session\n", - " by_session = {}\n", - " for trade in recent_trades:\n", - " session = trade.get('session', 'unknown')\n", - " by_session[session] = by_session.get(session, 0) + 1\n", - " \n", - " # Print results\n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE PERFORMANCE - Last {days_back} days\")\n", - " print(f\"Total Trades: {total_trades}\")\n", - " \n", - " print(f\"\\nBy Market Regime:\")\n", - " for regime, count in by_regime.items():\n", - " print(f\" {regime.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Adaptive Interval:\")\n", - " for interval, count in sorted(by_interval.items()):\n", - " print(f\" {interval} min: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Trading Session:\")\n", - " for session, count in by_session.items():\n", - " print(f\" {session.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " except Exception as e:\n", - " print(f\"Could not analyze performance: {e}\")\n", - "\n", - "\n", - "print(\"✅ Performance Monitoring functions defined (with adaptive features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 11. 🆕 Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# TRADING CHECK: SESSION FILTER + DRAWDOWN PROTECTION", - "# ==========================================", - "", - "from session_filter_patch import (", - " create_session_filtered_check,", - " SESSION_WHITELIST_CONFIG,", - " is_session_allowed", - ")", - "from drawdown_protection import create_protected_trading_check", - "", - "print(\"🔧 Setting up Trading Check...\")", - "", - "# Step 1: Create base session-filtered trading check", - "base_trading_check = create_session_filtered_check(", - " rhythm_manager=rhythm_manager,", - " execute_func=execute_trade_v2_adaptive,", - " symbol=symbol,", - " strategy_name=strategy_name,", - " max_positions=max_positions,", - " logger=logger,", - " datetime=datetime", - ")", - "", - "print(\"✅ Session Filter aktiviert!\")", - "print(\" Deaktivierte Sessions:\")", - "for session, enabled in SESSION_WHITELIST_CONFIG['enabled_sessions'].items():", - " status = \"✅ AKTIV\" if enabled else \"❌ DEAKTIVIERT\"", - " print(f\" • {session.upper():8s}: {status}\")", - "", - "# Step 2: Wrap with Drawdown Protection", - "adaptive_trading_check = create_protected_trading_check(infra, base_trading_check)", - "drawdown_protection = adaptive_trading_check.protection", - "", - "print(\"\\n🛡️ Drawdown Protection aktiviert!\")", - "print(f\" • Daily Loss Limit: ${drawdown_protection.max_daily_loss}\")", - "print(f\" • Weekly Loss Limit: ${drawdown_protection.max_weekly_loss}\")", - "print(f\" • Monthly Loss Limit: ${drawdown_protection.max_monthly_loss}\")", - "print(f\" • Max Consecutive Losses: {drawdown_protection.max_consecutive_losses}\")", - "print(f\" • Cooldown: {drawdown_protection.cooldown_hours}h\")", - "", - "print(\"\\n✅ Trading Check ist jetzt vollständig geschützt!\")", - "print(\" 📊 Session Filter: Aktiv\")", - "print(\" 🛡️ Drawdown Protection: Aktiv\")", - "" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# def adaptive_trading_check():\n", - "# \"\"\"\n", - "# 🆕 V1.6: Adaptive Trading Check\n", - "# Prüft basierend auf optimalem Intervall ob gehandelt werden soll\n", - "# \"\"\"\n", - "# try:\n", - "# optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "# current_minute = datetime.now().minute\n", - " \n", - "# # Trading nur zu berechneten Zeitpunkten\n", - "# if current_minute % optimal_interval == 0:\n", - "# logger.info(f\"\\n⏰ {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} - ADAPTIVE Check\")\n", - "# logger.info(f\"Intervall: {optimal_interval} min\")\n", - " \n", - "# # Führe Trading aus\n", - "# execute_trade_v2_adaptive(\n", - "# symbol=symbol,\n", - "# strategy_name=strategy_name,\n", - "# max_positions=max_positions\n", - "# )\n", - " \n", - "# except Exception as e:\n", - "# logger.error(f\"Fehler im Adaptive Trading Check: {e}\")\n", - "\n", - "\n", - "def print_status_report():\n", - " \"\"\"Status-Report\"\"\"\n", - " print(rhythm_manager.get_status_report())\n", - "\n", - "\n", - "# print(\"✅ Adaptive Scheduler functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 12. ✅ KORRIGIERT: Trading Configuration" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Zentrale Konfiguration (fehlte in ursprünglicher V1.6)\n", - "ADAPTIVE_COMPLETE_CONFIG = {\n", - " 'symbol': symbol,\n", - " 'atr_mult': 1.5,\n", - " 'base_confidence': 60, # RELAXED\n", - " 'max_risk_per_trade': 0.01,\n", - " 'risk_filter': True,\n", - " 'min_atr': 0.0008, # RELAXED\n", - " 'use_pullback_entry': False, # DISABLED\n", - " 'max_positions': max_positions,\n", - " 'strategy_name': strategy_name,\n", - " 'debug': True\n", - "}\n", - "\n", - "print(\"⚙️ V1.6 Adaptive Complete Configuration:\")\n", - "print(\"\\n🛡️ Position Control:\")\n", - "print(f\" Max Positions: {ADAPTIVE_COMPLETE_CONFIG['max_positions']}\")\n", - "print(f\" Strategy: {ADAPTIVE_COMPLETE_CONFIG['strategy_name']}\")\n", - "\n", - "print(\"\\n🚀 Relaxed Parameters:\")\n", - "print(f\" Base Confidence: {ADAPTIVE_COMPLETE_CONFIG['base_confidence']}%\")\n", - "print(f\" Min ATR: {ADAPTIVE_COMPLETE_CONFIG['min_atr']}\")\n", - "print(f\" Pullback Entry: {ADAPTIVE_COMPLETE_CONFIG['use_pullback_entry']}\")\n", - "\n", - "print(\"\\n⚡ Adaptive Features:\")\n", - "print(f\" Dynamic Intervals: 5/15/30 min\")\n", - "print(f\" Session-aware: Yes\")\n", - "print(f\" Volatility-based: Yes\")\n", - "\n", - "print(\"\\n✅ Configuration complete!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 13. ✅ KORRIGIERT: Status & Monitoring Functions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Umfassendes Status Monitoring (fehlte in V1.6)\n", - "def check_adaptive_bot_status():\n", - " \"\"\"\n", - " ✅ NEU: Kombiniertes Status-Check für V1.6 Adaptive Complete\n", - " Kombiniert Position Control + Adaptive Rhythm Status\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔍 V1.6 ADAPTIVE COMPLETE BOT STATUS\")\n", - " print(\"=\"*70)\n", - " \n", - " # System Status\n", - " print(\"\\n📡 SYSTEM STATUS:\")\n", - " print(f\" MT5 Connection: {'✅' if mt.terminal_info() else '❌'}\")\n", - " print(f\" Scheduler Running: {'✅' if scheduler.running else '❌'}\")\n", - " print(f\" Active Jobs: {len(scheduler.get_jobs())}\")\n", - " \n", - " # Adaptive Rhythm Status\n", - " print(\"\\n⚡ ADAPTIVE RHYTHM:\")\n", - " optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - " session = rhythm_manager.get_current_session()\n", - " df = rhythm_manager.get_market_data()\n", - " \n", - " if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\" Current Interval: {optimal_interval} min\")\n", - " print(f\" Trading Session: {session.upper()}\")\n", - " print(f\" ATR (H1): {atr:.2f}\")\n", - " print(f\" Volatility: {vol_level.upper()}\")\n", - " else:\n", - " print(\" ⚠️ Could not fetch market data\")\n", - " \n", - " # Position Status\n", - " print(\"\\n🛡️ POSITION CONTROL:\")\n", - " has_pos, pos_info = check_existing_positions(symbol, strategy_name)\n", - " print(f\" Active Positions: {pos_info['count']}/{max_positions}\")\n", - " print(f\" Trading Status: {'🛑 BLOCKED' if has_pos else '✅ READY'}\")\n", - " \n", - " if has_pos:\n", - " for i, pos in enumerate(pos_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\" Position {i}: {pos['type']} | {profit_emoji} {pos['profit']:.2f}\")\n", - " \n", - " # Signal Status\n", - " print(\"\\n📊 CURRENT SIGNAL:\")\n", - " try:\n", - " signal_info = extended_top_down_v2_adaptive(symbol)\n", - " if signal_info:\n", - " signal_dir = \"LONG\" if signal_info['entry_signal'] == 1 else \"SHORT\" if signal_info['entry_signal'] == -1 else \"NONE\"\n", - " print(f\" Signal: {signal_dir}\")\n", - " print(f\" Confidence: {signal_info['confidence']}%\")\n", - " print(f\" Threshold: {signal_info['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_info['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_info['market_regime']['regime'].upper()}\")\n", - " \n", - " would_trade = (signal_info['entry_signal'] != 0 and not has_pos)\n", - " print(f\" Would Trade: {'✅ YES' if would_trade else '❌ NO'}\")\n", - " else:\n", - " print(\" ⚠️ Signal analysis failed\")\n", - " except Exception as e:\n", - " print(f\" ❌ Error: {e}\")\n", - " \n", - " # Version Info\n", - " print(\"\\n🎉 VERSION INFO:\")\n", - " print(\" Version: V1.6 Adaptive Complete (CORRECTED)\")\n", - " print(\" Features: Position Control + Relaxed + Adaptive Rhythm\")\n", - " print(\" Status: Production-Ready ✅\")\n", - " print(\"=\"*70)\n", - "\n", - "\n", - "print(\"✅ Status monitoring function defined (COMPLETE with all features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 14. 🚀 Start Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Setup Schedulerscheduler = BackgroundScheduler()# ADAPTIVE: Prüft jede Minute, handelt zu optimalen Zeitpunktenscheduler.add_job( func=adaptive_trading_check, trigger='cron', minute='*', id='adaptive_trading_check')# Status-Report alle 30 Minutenscheduler.add_job( func=print_status_report, trigger='cron', minute='0,30', id='status_report')# ==========================================# SCHEDULED REPORTS (V1.8)# ==========================================# Add daily & weekly reportscreate_scheduled_reports(infra, scheduler)print(\"✅ Scheduled reports added:\")print(\" 📊 Daily report: 22:00 UTC\")print(\" 📈 Weekly report: Sunday 23:00 UTC\")# ==========================================# POSITION MONITOR JOB (V1.8)# ==========================================# Add Position Monitor (checks every minute for closed positions)scheduler.add_job( func=position_monitor.check_open_positions, trigger='interval', minutes=1, id='position_monitor')print(\"✅ Position Monitor job added:\")print(\" 📊 Checks every minute for closed positions\")# ==========================================# ==========================================# Start scheduler# ==========================================# ADVANCED POSITION MANAGEMENT JOB# ==========================================# Trailing Stop + Partial TP Check (every minute)scheduler.add_job( func=lambda: adv_position_mgr.check_and_update_positions(symbol), trigger='interval', minutes=1, id='advanced_position_management')print(\"✅ Advanced Position Management job added:\")print(\" 📈 Checks for Trailing Stop updates every minute\")print(\" 🎯 Checks for Partial TP triggers every minute\")scheduler.start()logger.info(\"✅ Scheduler started with session filter + reports\")# Starte Scheduler## ==========================================# ADVANCED POSITION MANAGEMENT JOB# ==========================================# Trailing Stop + Partial TP Check (every minute)scheduler.add_job( func=lambda: adv_position_mgr.check_and_update_positions(symbol), trigger='interval', minutes=1, id='advanced_position_management')print(\"✅ Advanced Position Management job added:\")print(\" 📈 Checks for Trailing Stop updates every minute\")print(\" 🎯 Checks for Partial TP triggers every minute\")scheduler.start()print(\"\\n\" + \"=\"*70)print(\"🚀 TradingBot V1.6 ADAPTIVE COMPLETE - Scheduler gestartet!\")print(\"=\"*70)print(\"\\n🎯 Features aktiv:\")print(\" ✅ Position Control System (Max 1 Position)\")print(\" ✅ Relaxed Trading Parameters\")print(\" ✅ ADAPTIVE RHYTHM (5/15/30 Min)\")print(\" ✅ Volatilitäts-basiert (ATR)\")print(\" ✅ Session-abhängig (Asian/London/NY/Overlap)\")print(\" ✅ Complete Position Management\")print(\" ✅ Umfassendes Status Monitoring\")print(\"\\n⚡ Adaptive Intervall-Matrix:\")print(\" • Overlap (13-16 UTC): 5-15min\")print(\" • London/NY: 5-30min\")print(\" • Asian: 15-30min\")print(\"\\n📊 Status-Reports alle 30 Minuten\")print(\"🔍 Trading-Checks zu adaptiven Zeitpunkten\")print(\"=\"*70)# Zeige initialen Statuscheck_adaptive_bot_status()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 15. ✅ KORRIGIERT: Testing Suite" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Umfassende Testing Suite (fehlte in V1.6)\n", - "\n", - "# Test 1: Position Summary\n", - "print(\"🧪 TEST 1: Position Check\")\n", - "print(\"=\"*50)\n", - "get_position_summary(symbol, strategy_name)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 2: Adaptive Rhythm Status\n", - "print(\"\\n🧪 TEST 2: Adaptive Rhythm\")\n", - "print(\"=\"*50)\n", - "print_status_report()\n", - "\n", - "# Test Details\n", - "optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "session = rhythm_manager.get_current_session()\n", - "df = rhythm_manager.get_market_data()\n", - "\n", - "if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\"\\nDetails:\")\n", - " print(f\" Optimal Interval: {optimal_interval} min\")\n", - " print(f\" Session: {session}\")\n", - " print(f\" ATR: {atr:.2f}\")\n", - " print(f\" Volatility Level: {vol_level}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 3: Signal Analysis\n", - "print(\"\\n🧪 TEST 3: Signal Analysis\")\n", - "print(\"=\"*50)\n", - "\n", - "signal_result = extended_top_down_v2_adaptive(symbol)\n", - "\n", - "if signal_result:\n", - " print(f\"\\n🎯 SIGNAL SUMMARY:\")\n", - " print(f\" Entry Signal: {signal_result['entry_signal']}\")\n", - " print(f\" Confidence: {signal_result['confidence']}%\")\n", - " print(f\" Threshold: {signal_result['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_result['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_result['market_regime']['regime'].upper()}\")\n", - " print(f\" Adaptive Interval: {signal_result['adaptive_interval']} min\")\n", - " print(f\" Session: {signal_result['session'].upper()}\")\n", - " \n", - " if signal_result['entry_signal'] != 0:\n", - " direction = \"LONG\" if signal_result['entry_signal'] == 1 else \"SHORT\"\n", - " print(f\"\\n✅ TRADING SIGNAL: {direction}\")\n", - " else:\n", - " print(f\"\\n⏸️ NO TRADING SIGNAL\")\n", - "else:\n", - " print(\"❌ Signal analysis failed\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 4: Complete Bot Status\n", - "print(\"\\n🧪 TEST 4: Complete Bot Status\")\n", - "print(\"=\"*50)\n", - "check_adaptive_bot_status()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Test 5: Trade Execution Test (DRY RUN)\n", - "print(\"\\n🧪 TEST 5: Trade Execution (DRY RUN)\")\n", - "print(\"=\"*50)\n", - "print(\"\\nTesting trading logic without actual order...\")\n", - "\n", - "# Dies führt die komplette Trading-Logik aus,\n", - "# führt aber nur dann wirklich einen Trade aus,\n", - "# wenn alle Bedingungen erfüllt sind\n", - "\n", - "test_result = execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)\n", - "\n", - "if test_result:\n", - " print(\"\\n✅ Trade würde ausgeführt!\")\n", - "else:\n", - " print(\"\\n⏸️ Kein Trade - Bedingungen nicht erfüllt\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 16. ✅ KORRIGIERT: Management Control Panel" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "scheduler.get_jobs()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ✅ KORRIGIERT: Management Control Panel (fehlte in V1.6)\n", - "def show_adaptive_management_options():\n", - " \"\"\"\n", - " ✅ NEU: Management UI für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔧 V1.6 ADAPTIVE COMPLETE - MANAGEMENT CONTROL PANEL\")\n", - " print(\"=\"*70)\n", - " \n", - " print(\"\\n📊 MONITORING:\")\n", - " print(\" 1. check_adaptive_bot_status() - Complete Status\")\n", - " print(\" 2. get_position_summary() - Position Overview\")\n", - " print(\" 3. print_status_report() - Adaptive Rhythm Status\")\n", - " print(\" 4. analyze_performance_adaptive() - Performance Analysis\")\n", - " \n", - " print(\"\\n🎯 ANALYSIS:\")\n", - " print(\" 5. extended_top_down_v2_adaptive() - Signal Analysis\")\n", - " print(\" 6. rhythm_manager.calculate_optimal_interval() - Current Interval\")\n", - " \n", - " print(\"\\n💼 POSITION MANAGEMENT:\")\n", - " print(\" 7. close_existing_positions(force_close=True) - Close All Positions\")\n", - " \n", - " print(\"\\n🚀 TRADING:\")\n", - " print(\" 8. execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG) - Manual Trade\")\n", - " \n", - " print(\"\\n⚙️ SCHEDULER CONTROL:\")\n", - " print(\" 9. scheduler.get_jobs() - Show Active Jobs\")\n", - " print(\" 10. scheduler.pause() - Pause Scheduler\")\n", - " print(\" 11. scheduler.resume() - Resume Scheduler\")\n", - " print(\" 12. scheduler.shutdown() - Stop Scheduler\")\n", - " \n", - " print(\"\\n🔧 CONFIGURATION:\")\n", - " print(\" 13. ADAPTIVE_COMPLETE_CONFIG - View Config\")\n", - " print(\" 14. rhythm_manager.atr_thresholds - ATR Settings\")\n", - " \n", - " print(\"\\n📝 QUICK COMMANDS:\")\n", - " print(\" • Status: check_adaptive_bot_status()\")\n", - " print(\" • Close: close_existing_positions(symbol, strategy_name, force_close=True)\")\n", - " print(\" • Stop: scheduler.shutdown()\")\n", - " \n", - " print(\"=\"*70)\n", - "\n", - "\n", - "show_adaptive_management_options()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Optional: Close positions manually\n", - "# UNCOMMENT to use:\n", - "# close_existing_positions(symbol, strategy_name, force_close=True)\n", - "\n", - "print(\"💡 To close positions manually, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Optional: ATR-Schwellenwerte anpassen\n", - "# UNCOMMENT to use:\n", - "# rhythm_manager.atr_thresholds = {\n", - "# 'high': 18.0,\n", - "# 'medium': 10.0,\n", - "# 'low': 5.0\n", - "# }\n", - "# print(\"✅ ATR thresholds updated\")\n", - "\n", - "print(\"💡 To adjust ATR thresholds, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Scheduler Control\n", - "print(\"🎛️ SCHEDULER CONTROL\")\n", - "print(\"\\n💡 To pause trading:\")\n", - "print(\"scheduler.pause()\")\n", - "print(\"\\n💡 To resume trading:\")\n", - "print(\"scheduler.resume()\")\n", - "print(\"\\n💡 To stop completely:\")\n", - "print(\"scheduler.shutdown()\")\n", - "\n", - "# UNCOMMENT to stop:\n", - "# scheduler.shutdown()\n", - "# print(\"🔴 Trading Bot stopped\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 17. 📈 V1.6 ADAPTIVE COMPLETE - Summary" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "print(\"\\n\" + \"=\"*70)\n", - "print(\"📈 TRADINGBOT V1.6 ADAPTIVE COMPLETE - SUMMARY\")\n", - "print(\"=\"*70)\n", - "\n", - "print(\"\\n🎉 VERSION: V1.6 ADAPTIVE COMPLETE (CORRECTED & READY!)\")\n", - "\n", - "print(\"\\n✅ ALLE FEATURES INTEGRIERT:\")\n", - "\n", - "print(\"\\n🛡️ Position Control (aus V1.5):\")\n", - "print(\" • Maximal 1 Trade gleichzeitig\")\n", - "print(\" • check_existing_positions()\")\n", - "print(\" • get_position_summary()\")\n", - "print(\" • close_existing_positions() ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🚀 Relaxed Trading Parameters (aus V1.5):\")\n", - "print(\" • 10-20% niedrigere Confidence-Schwellen\")\n", - "print(\" • Disabled Pullback Entry\")\n", - "print(\" • Relaxed Signal-Quality-Filter\")\n", - "print(\" • Niedrigere Min Risk-Adjusted Strength (80)\")\n", - "print(\" • Fixed 2/4 Timeframe Alignment\")\n", - "\n", - "print(\"\\n⚡ Adaptive Rhythm (NEU in V1.6):\")\n", - "print(\" • Adaptive Intervalle: 5/15/30 Minuten\")\n", - "print(\" • Volatilitäts-basiert (ATR)\")\n", - "print(\" • Session-abhängig (Asian/London/NY/Overlap)\")\n", - "print(\" • Intelligente Entscheidungs-Matrix\")\n", - "\n", - "print(\"\\n📊 Monitoring & Management (aus V1.5, angepasst):\")\n", - "print(\" • Performance Logging\")\n", - "print(\" • Performance Analysis\")\n", - "print(\" • Complete Status Monitoring ✅ KORRIGIERT!\")\n", - "print(\" • Management Control Panel ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🤖 Automation:\")\n", - "print(\" • APScheduler Integration\")\n", - "print(\" • Adaptive Trading Checks (jede Minute)\")\n", - "print(\" • Status Reports (alle 30 Min)\")\n", - "\n", - "print(\"\\n🧪 Testing Suite (aus V1.5):\")\n", - "print(\" • Position Tests ✅ KORRIGIERT!\")\n", - "print(\" • Signal Analysis Tests ✅ KORRIGIERT!\")\n", - "print(\" • Adaptive Rhythm Tests\")\n", - "print(\" • Complete Status Tests ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n⚙️ Configuration:\")\n", - "print(\" • ADAPTIVE_COMPLETE_CONFIG ✅ KORRIGIERT!\")\n", - "print(\" • Zentrale Parameter-Verwaltung\")\n", - "\n", - "print(\"\\n🎯 VORTEILE VON V1.6 ADAPTIVE COMPLETE:\")\n", - "print(\" ✅ Maximale Sicherheit (Position Control)\")\n", - "print(\" ✅ Maximale Gelegenheiten (Relaxed Parameters)\")\n", - "print(\" ✅ Maximale Effizienz (Adaptive Rhythm)\")\n", - "print(\" ✅ Vollständige Kontrolle (Complete Management)\")\n", - "print(\" ✅ Production-Ready!\")\n", - "\n", - "print(\"\\n📊 TYPISCHER 24H-ZYKLUS:\")\n", - "print(\" 00:00-08:00 (Asian) → 15-30 min\")\n", - "print(\" 08:00-13:00 (London) → 5-30 min\")\n", - "print(\" 13:00-16:00 (Overlap) → 5-15 min 🔥\")\n", - "print(\" 16:00-21:00 (NY) → 5-30 min\")\n", - "print(\" 21:00-00:00 (After) → 15-30 min\")\n", - "\n", - "print(\"\\n💡 HAUPTFUNKTIONEN:\")\n", - "print(\" • Status: check_adaptive_bot_status()\")\n", - "print(\" • Analyze: extended_top_down_v2_adaptive()\")\n", - "print(\" • Trade: execute_trade_v2_adaptive()\")\n", - "print(\" • Manage: show_adaptive_management_options()\")\n", - "\n", - "print(\"\\n🏆 V1.6 ADAPTIVE COMPLETE - ALLE FUNKTIONEN INTEGRIERT!\")\n", - "print(\" 🛡️ Sicherheit + 🚀 Aggressivität + ⚡ Intelligenz\")\n", - "print(\" Production-Ready & Fully Tested! ✅\")\n", - "\n", - "print(\"\\n\" + \"=\"*70)\n", - "print(\"🎊 Ready for intelligent, safe, and adaptive trading!\")\n", - "print(\"=\"*70)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2025-11-26 11:37:00,014 - INFO - Running job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" (scheduled at 2025-11-26 11:37:00+01:00)\n", - "2025-11-26 11:37:00,014 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-11-26 11:37:00,014 - INFO - Job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" executed successfully\n", - "2025-11-26 11:37:00,102 - INFO - Running job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" (scheduled at 2025-11-26 11:37:00+01:00)\n", - "2025-11-26 11:37:00,103 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-11-26 11:37:00,103 - INFO - Job \"create_session_filtered_check..adaptive_trading_check_filtered (trigger: cron[minute='*'], next run at: 2025-11-26 11:38:00 CET)\" executed successfully\n" - ] - } - ], - "source": [ - "# Prüfe ob Filter aktiv ist\n", - "print(SESSION_WHITELIST_CONFIG)\n", - "\n", - "# Teste manuell verschiedene Sessions\n", - "for session in ['asian', 'london', 'overlap', 'ny']:\n", - " allowed, reason = is_session_allowed(session)\n", - " emoji = \"✅\" if allowed else \"❌\"\n", - " print(f\"{emoji} {session}: {reason}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} \ No newline at end of file diff --git a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_regime_indicator_20251215_105338.ipynb b/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_regime_indicator_20251215_105338.ipynb deleted file mode 100644 index a061a2c..0000000 --- a/TradingBot_V1.6_Adaptive_Complete_CORRECTED_backup_regime_indicator_20251215_105338.ipynb +++ /dev/null @@ -1,3264 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# TradingBot V1.6 - Adaptive Complete Version 🚀🛡️⚡\n", - "\n", - "## 🆕 **NEU in V1.6: Adaptive Trading Rhythm**\n", - "- ⚡ **Adaptive Intervalle** - Automatische Anpassung: 5/15/30 Minuten\n", - "- 📊 **Volatilitäts-basiert** - ATR-gesteuerte Intervall-Wahl\n", - "- 🌍 **Session-abhängig** - Asian/London/NY/Overlap\n", - "- 🎯 **Intelligente Matrix** - Optimale Kombination aus Session + Volatilität\n", - "\n", - "## ✅ **Features aus V1.5 Complete Relaxed:**\n", - "- 🛡️ **Position Control System** - Maximal 1 Trade gleichzeitig\n", - "- 📊 **Performance Monitoring & Logging**\n", - "- 🤖 **APScheduler Integration** - Automatisierung\n", - "- 🔧 **Position Management Funktionen** - VOLLSTÄNDIG!\n", - "- 🚀 **Relaxed Parameter** - Niedrigere Schwellen für mehr Signale\n", - "- 🧪 **Umfassende Testing Suite**\n", - "- 🎛️ **Management Control Panel**\n", - "\n", - "## 🎯 **Adaptive Rhythm Schema:**\n", - "```\n", - "Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - "───────────┼──────────┼──────────────┼─────────────\n", - "Overlap │ 5min │ 15min │ 15min\n", - "London/NY │ 5min │ 15min │ 30min\n", - "Asian │ 15min │ 30min │ 30min\n", - "```\n", - "\n", - "## 🎉 **V1.6 COMPLETE - Das Beste aus beiden Welten:**\n", - "- ✅ Alle Funktionen aus V1.5\n", - "- ✅ Neue adaptive Features aus V1.6\n", - "- ✅ Production-Ready!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Imports und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ All imports successful - V1.6 Adaptive Complete (CORRECTED)\n" - ] - } - ], - "source": [ - "# Standard Imports\n", - "import pandas as pd\n", - "import numpy as np\n", - "import MetaTrader5 as mt\n", - "import pandas_ta as ta\n", - "from scipy.signal import savgol_filter, find_peaks\n", - "from sklearn.linear_model import LinearRegression\n", - "from tabulate import tabulate\n", - "from datetime import datetime, timedelta, time\n", - "import json\n", - "import keyring as kr\n", - "\n", - "# V1.6: Zusätzliche Imports für Adaptive Rhythm\n", - "import pytz\n", - "import logging\n", - "from apscheduler.schedulers.background import BackgroundScheduler\n", - "\n", - "# Setup Logging\n", - "logging.basicConfig(\n", - " level=logging.INFO,\n", - " format='%(asctime)s - %(levelname)s - %(message)s'\n", - ")\n", - "logger = logging.getLogger(__name__)\n", - "\n", - "print(\"✅ All imports successful - V1.6 Adaptive Complete (CORRECTED)\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Infrastructure modules loaded\n" - ] - } - ], - "source": [ - "# ==========================================\n", - "# INFRASTRUCTURE IMPORTS (V1.8)\n", - "# ==========================================\n", - "\n", - "from infrastructure_patch import (\n", - " TradingInfrastructure,\n", - " create_scheduled_reports\n", - ")\n", - "from trading_database import TradingDatabase\n", - "from telegram_notifier import TelegramNotifier\n", - "\n", - "print(\"✅ Infrastructure modules loaded\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. 🆕 Adaptive Rhythm Manager (NEU in V1.6)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Adaptive Rhythm Manager defined\n" - ] - } - ], - "source": [ - "class AdaptiveRhythmManager:\n", - " \"\"\"\n", - " 🆕 V1.6 Feature: Adaptive Trading Rhythm\n", - " \n", - " Verwaltet adaptiven Trading-Rhythmus basierend auf:\n", - " - Marktvolatilität (ATR)\n", - " - Trading-Session (Asian/London/NY/Overlap)\n", - " - Marktregime\n", - " \"\"\"\n", - " \n", - " def __init__(self, symbol=\"XAUUSD\"):\n", - " self.symbol = symbol\n", - " self.current_interval = 5\n", - " \n", - " # Zeitintervalle in Minuten\n", - " self.intervals = {\n", - " 'fast': 5, # Hohe Volatilität, aktive Sessions\n", - " 'medium': 15, # Moderate Volatilität, Standard\n", - " 'slow': 30 # Niedrige Volatilität, ruhige Sessions\n", - " }\n", - " \n", - " # ATR-Schwellenwerte für XAUUSD (Gold)\n", - " self.atr_thresholds = {\n", - " 'high': 15.0, # Hohe Volatilität\n", - " 'medium': 8.0, # Moderate Volatilität\n", - " 'low': 5.0 # Niedrige Volatilität\n", - " }\n", - " \n", - " # Session-Zeiten (UTC)\n", - " self.sessions = {\n", - " 'asian': (time(0, 0), time(8, 0)), # 00:00-08:00 UTC\n", - " 'london': (time(8, 0), time(16, 0)), # 08:00-16:00 UTC\n", - " 'ny': (time(13, 0), time(21, 0)), # 13:00-21:00 UTC\n", - " 'overlap': (time(13, 0), time(16, 0)) # London-NY Overlap\n", - " }\n", - " \n", - " def get_current_session(self):\n", - " \"\"\"Ermittelt die aktuelle Trading-Session\"\"\"\n", - " now_utc = datetime.now(pytz.UTC).time()\n", - " \n", - " # Overlap hat höchste Priorität\n", - " if self.sessions['overlap'][0] <= now_utc <= self.sessions['overlap'][1]:\n", - " return 'overlap'\n", - " elif self.sessions['london'][0] <= now_utc < self.sessions['london'][1]:\n", - " return 'london'\n", - " elif self.sessions['ny'][0] <= now_utc < self.sessions['ny'][1]:\n", - " return 'ny'\n", - " return 'asian'\n", - " \n", - " def get_volatility_level(self, atr_value):\n", - " \"\"\"Klassifiziert die Volatilität basierend auf ATR\"\"\"\n", - " if atr_value >= self.atr_thresholds['high']:\n", - " return 'high'\n", - " elif atr_value >= self.atr_thresholds['medium']:\n", - " return 'medium'\n", - " return 'low'\n", - " \n", - " def get_market_data(self):\n", - " \"\"\"Hole Marktdaten für ATR-Analyse\"\"\"\n", - " try:\n", - " rates = mt.copy_rates_from_pos(self.symbol, mt.TIMEFRAME_H1, 0, 50)\n", - " if rates is None:\n", - " return None\n", - " \n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " logger.error(f\"Fehler beim Laden der Marktdaten: {e}\")\n", - " return None\n", - " \n", - " def calculate_optimal_interval(self):\n", - " \"\"\"Berechnet optimales Trading-Intervall\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is None:\n", - " return self.current_interval\n", - " \n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " optimal_interval = self._determine_interval(session, volatility)\n", - " \n", - " # Logge Änderungen\n", - " if optimal_interval != self.current_interval:\n", - " logger.info(f\"🔄 Rhythmus-Änderung: {self.current_interval}m → {optimal_interval}m\")\n", - " logger.info(f\" Session: {session}, Volatilität: {volatility} (ATR: {current_atr:.2f})\")\n", - " \n", - " self.current_interval = optimal_interval\n", - " return optimal_interval\n", - " \n", - " def _determine_interval(self, session, volatility):\n", - " \"\"\"\n", - " Intervall-Entscheidungs-Matrix:\n", - " \n", - " Session │ Hohe Vol │ Mittlere Vol │ Niedrige Vol\n", - " ───────────┼──────────┼──────────────┼─────────────\n", - " Overlap │ 5min │ 15min │ 15min\n", - " London/NY │ 5min │ 15min │ 30min\n", - " Asian │ 15min │ 30min │ 30min\n", - " \"\"\"\n", - " if session == 'overlap':\n", - " return self.intervals['fast'] if volatility == 'high' else self.intervals['medium']\n", - " elif session in ['london', 'ny']:\n", - " if volatility == 'high':\n", - " return self.intervals['fast']\n", - " elif volatility == 'medium':\n", - " return self.intervals['medium']\n", - " return self.intervals['slow']\n", - " else: # asian\n", - " return self.intervals['medium'] if volatility == 'high' else self.intervals['slow']\n", - " \n", - " def get_status_report(self):\n", - " \"\"\"Erstellt Status-Report\"\"\"\n", - " session = self.get_current_session()\n", - " df = self.get_market_data()\n", - " \n", - " if df is not None:\n", - " current_atr = df['atr'].iloc[-1]\n", - " volatility = self.get_volatility_level(current_atr)\n", - " else:\n", - " current_atr = 0\n", - " volatility = 'unknown'\n", - " \n", - " return f\"\"\"\n", - "╔════════════════════════════════════════════════════════╗\n", - "║ ADAPTIVE RHYTHM STATUS - {datetime.now().strftime('%H:%M:%S UTC')} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ Aktuelles Intervall: {self.current_interval:>2} Minuten ║\n", - "║ Trading Session: {session.upper():<15} ║\n", - "║ Volatilitätslevel: {volatility.upper():<15} ║\n", - "║ ATR (H1): {current_atr:>6.2f} ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ INTERVALL-SCHEMA: ║\n", - "║ • Overlap (13-16 UTC): 5-15 Min (aktivste Phase) ║\n", - "║ • London/NY: 5-30 Min (volatilitätsabh.) ║\n", - "║ • Asian Session: 15-30 Min (ruhigere Phase) ║\n", - "╚════════════════════════════════════════════════════════╝\n", - "\"\"\"\n", - "\n", - "print(\"✅ Adaptive Rhythm Manager defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. MT5 Login und Setup" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Login successful: True\n", - "Symbol: XAUUSD\n", - "Strategy: TradingBot_V1.6\n", - "Max Positions: 1\n", - "Version: V1.6 COMPLETE - Adaptive + Full Features! 🚀🛡️⚡\n", - "\n", - "\n", - "╔════════════════════════════════════════════════════════╗\n", - "║ ADAPTIVE RHYTHM STATUS - 09:26:57 UTC ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ Aktuelles Intervall: 5 Minuten ║\n", - "║ Trading Session: LONDON ║\n", - "║ Volatilitätslevel: MEDIUM ║\n", - "║ ATR (H1): 9.59 ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ INTERVALL-SCHEMA: ║\n", - "║ • Overlap (13-16 UTC): 5-15 Min (aktivste Phase) ║\n", - "║ • London/NY: 5-30 Min (volatilitätsabh.) ║\n", - "║ • Asian Session: 15-30 Min (ruhigere Phase) ║\n", - "╚════════════════════════════════════════════════════════╝\n", - "\n" - ] - } - ], - "source": [ - "# MT5 Login\n", - "mt.initialize()\n", - "login = 10800246\n", - "server = 'VantageInternational-Demo'\n", - "password = kr.get_password(server, str(login))\n", - "login_result = mt.login(login, password, server)\n", - "print(f\"Login successful: {login_result}\")\n", - "\n", - "# Trading Parameter\n", - "symbol = \"XAUUSD\"\n", - "strategy_name = \"TradingBot_V1.6\"\n", - "max_positions = 1\n", - "\n", - "print(f\"Symbol: {symbol}\")\n", - "print(f\"Strategy: {strategy_name}\")\n", - "print(f\"Max Positions: {max_positions}\")\n", - "print(f\"Version: V1.6 COMPLETE - Adaptive + Full Features! 🚀🛡️⚡\")\n", - "\n", - "# 🆕 Initialisiere Adaptive Rhythm Manager\n", - "rhythm_manager = AdaptiveRhythmManager(symbol)\n", - "print(\"\\n\" + rhythm_manager.get_status_report())" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "🔧 Initializing Infrastructure...\n", - "✅ Database initialized: trading_bot.db\n", - "✅ Telegram Bot connected: @Xausd_digger_bot\n", - "✅ Telegram notifications enabled\n", - "✅ Infrastructure ready!\n", - " Database: ✅\n", - " Telegram: ✅\n" - ] - } - ], - "source": [ - "# ==========================================\n", - "# INITIALIZE INFRASTRUCTURE (V1.8)\n", - "# ==========================================\n", - "\n", - "print(\"🔧 Initializing Infrastructure...\")\n", - "\n", - "# Initialize Infrastructure\n", - "infra = TradingInfrastructure(\n", - " db_path=\"trading_bot.db\",\n", - " enable_telegram=True,\n", - " enable_database=True\n", - ")\n", - "\n", - "# Bot Started Notification\n", - "from session_filter_patch import SESSION_WHITELIST_CONFIG\n", - "\n", - "bot_config = {\n", - " 'version': 'V1.8',\n", - " 'enabled_sessions': SESSION_WHITELIST_CONFIG['enabled_sessions'],\n", - " 'base_confidence': SESSION_WHITELIST_CONFIG['base_confidence'],\n", - " 'max_risk_per_trade': SESSION_WHITELIST_CONFIG['max_risk_per_trade']\n", - "}\n", - "\n", - "infra.send_bot_started(bot_config)\n", - "\n", - "print(\"✅ Infrastructure ready!\")\n", - "print(f\" Database: {'✅' if infra.enable_database else '❌'}\")\n", - "print(f\" Telegram: {'✅' if infra.enable_telegram else '❌'}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2025-12-10 09:26:58,891 - INFO - 🎯 Advanced Position Manager initialized\n", - "2025-12-10 09:26:58,892 - INFO - Adaptive Sizing: ✅\n", - "2025-12-10 09:26:58,893 - INFO - Trailing Stop: ✅\n", - "2025-12-10 09:26:58,894 - INFO - Partial TP: ✅\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "🎯 Initializing Advanced Position Management...\n", - "✅ Advanced Position Management activated!\n", - " 📊 Adaptive Position Sizing: ACTIVE\n", - " • High Confidence (≥80%): 1.5x risk\n", - " • Medium Confidence (≥70%): 1.0x risk\n", - " • Low Confidence (<70%): 0.5x risk\n", - "\n", - " 📈 Trailing Stop-Loss: ACTIVE\n", - " • Break-Even at 50% progress to TP\n", - " • Lock 50% profit at 75% progress\n", - "\n", - " 🎯 Partial Take Profit: ACTIVE\n", - " • TP1 at 1.5R (close 50%)\n", - " • TP2 at 2.5R (let 50% run)\n" - ] - } - ], - "source": [ - "# ==========================================\n", - "# ADVANCED POSITION MANAGEMENT SETUP\n", - "# ==========================================\n", - "\n", - "from advanced_position_management import AdvancedPositionManager\n", - "\n", - "print(\"🎯 Initializing Advanced Position Management...\")\n", - "\n", - "# Initialize Manager with all features\n", - "adv_position_mgr = AdvancedPositionManager(\n", - " enable_adaptive_sizing=True, # ✅ Adaptive Position Sizing\n", - " enable_trailing_stop=True, # ✅ Trailing Stop-Loss\n", - " enable_partial_tp=True # ✅ Partial Take Profit\n", - ")\n", - "\n", - "print(\"✅ Advanced Position Management activated!\")\n", - "print(\" 📊 Adaptive Position Sizing: ACTIVE\")\n", - "print(\" • High Confidence (≥80%): 1.5x risk\")\n", - "print(\" • Medium Confidence (≥70%): 1.0x risk\")\n", - "print(\" • Low Confidence (<70%): 0.5x risk\")\n", - "print(\"\")\n", - "print(\" 📈 Trailing Stop-Loss: ACTIVE\")\n", - "print(\" • Break-Even at 50% progress to TP\")\n", - "print(\" • Lock 50% profit at 75% progress\")\n", - "print(\"\")\n", - "print(\" 🎯 Partial Take Profit: ACTIVE\")\n", - "print(\" • TP1 at 1.5R (close 50%)\")\n", - "print(\" • TP2 at 2.5R (let 50% run)\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "🔧 Initializing Position Monitor...\n", - "✅ Position Monitor ready!\n", - " Will check for closed positions every minute\n", - " Closed trades will be automatically logged with:\n", - " • Exit price & time\n", - " • Profit/Loss calculation\n", - " • Exit reason (TP/SL/Manual)\n", - " • Telegram notification\n" - ] - } - ], - "source": [ - "# ==========================================\n", - "# POSITION MONITOR SETUP (V1.8)\n", - "# ==========================================\n", - "\n", - "from position_monitor import PositionMonitor\n", - "\n", - "print(\"🔧 Initializing Position Monitor...\")\n", - "\n", - "# Create Position Monitor\n", - "position_monitor = PositionMonitor(infra.db, infra.telegram)\n", - "\n", - "print(\"✅ Position Monitor ready!\")\n", - "print(\" Will check for closed positions every minute\")\n", - "print(\" Closed trades will be automatically logged with:\")\n", - "print(\" • Exit price & time\")\n", - "print(\" • Profit/Loss calculation\")\n", - "print(\" • Exit reason (TP/SL/Manual)\")\n", - "print(\" • Telegram notification\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. 🛡️ Position Control Functions (VOLLSTÄNDIG!)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Position Control functions defined (COMPLETE with close function!)\n" - ] - } - ], - "source": [ - "def check_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"\n", - " Überprüft ob bereits Positionen für das Symbol und die Strategie existieren\n", - " \"\"\"\n", - " try:\n", - " positions = mt.positions_get(symbol=symbol)\n", - " \n", - " if positions is None:\n", - " return False, {\"count\": 0, \"details\": []}\n", - " \n", - " strategy_positions = []\n", - " for pos in positions:\n", - " if strategy_name in pos.comment:\n", - " strategy_positions.append({\n", - " \"ticket\": pos.ticket,\n", - " \"type\": \"BUY\" if pos.type == 0 else \"SELL\",\n", - " \"volume\": pos.volume,\n", - " \"price_open\": pos.price_open,\n", - " \"profit\": pos.profit,\n", - " \"comment\": pos.comment,\n", - " \"time_open\": pd.to_datetime(pos.time, unit='s')\n", - " })\n", - " \n", - " has_position = len(strategy_positions) > 0\n", - " position_info = {\"count\": len(strategy_positions), \"details\": strategy_positions}\n", - " return has_position, position_info\n", - " \n", - " except Exception as e:\n", - " print(f\"Error checking positions: {e}\")\n", - " return False, {\"count\": 0, \"details\": []}\n", - "\n", - "\n", - "def get_position_summary(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\"):\n", - " \"\"\"Position-Zusammenfassung\"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " print(f\"\\n📊 POSITION SUMMARY für {symbol} (V1.6 Adaptive Complete)\")\n", - " print(\"=\" * 60)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine aktiven Positionen - bereit für neuen Trade\")\n", - " return False\n", - " \n", - " print(f\"⚠️ {position_info['count']} aktive Position(en) gefunden:\")\n", - " for i, pos in enumerate(position_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\"\\n Position {i}:\")\n", - " print(f\" Ticket: {pos['ticket']}\")\n", - " print(f\" Typ: {pos['type']}\")\n", - " print(f\" Volumen: {pos['volume']}\")\n", - " print(f\" Eröffnungspreis: {pos['price_open']}\")\n", - " print(f\" Profit: {profit_emoji} {pos['profit']:.2f}\")\n", - " print(f\" Eröffnungszeit: {pos['time_open']}\")\n", - " \n", - " print(f\"\\n🛑 TRADING BLOCKIERT - Maximal {max_positions} Position erlaubt\")\n", - " return True\n", - "\n", - "\n", - "def close_existing_positions(symbol=\"XAUUSD\", strategy_name=\"TradingBot_V1.6\", force_close=False):\n", - " \"\"\"\n", - " ✅ KORRIGIERT: Schließt bestehende Positionen (optional)\n", - " Diese Funktion fehlte in der ursprünglichen V1.6!\n", - " \"\"\"\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " if not has_position:\n", - " print(\"✅ Keine Positionen zum Schließen\")\n", - " return True\n", - " \n", - " if not force_close:\n", - " print(f\"⚠️ {position_info['count']} Position(en) gefunden. Verwende force_close=True zum Schließen.\")\n", - " return False\n", - " \n", - " print(f\"🔄 Schließe {position_info['count']} Position(en)...\")\n", - " \n", - " success_count = 0\n", - " for pos in position_info['details']:\n", - " try:\n", - " # Position schließen\n", - " close_request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": pos['volume'],\n", - " \"type\": mt.ORDER_TYPE_SELL if pos['type'] == \"BUY\" else mt.ORDER_TYPE_BUY,\n", - " \"position\": pos['ticket'],\n", - " \"price\": mt.symbol_info_tick(symbol).bid if pos['type'] == \"BUY\" else mt.symbol_info_tick(symbol).ask,\n", - " \"deviation\": 20,\n", - " \"magic\": 234000,\n", - " \"comment\": f\"Close {strategy_name}\",\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC,\n", - " }\n", - " \n", - " result = mt.order_send(close_request)\n", - " \n", - " if result.retcode == mt.TRADE_RETCODE_DONE:\n", - " print(f\"✅ Position {pos['ticket']} erfolgreich geschlossen\")\n", - " success_count += 1\n", - " else:\n", - " print(f\"❌ Fehler beim Schließen von Position {pos['ticket']}: {result.comment}\")\n", - " \n", - " except Exception as e:\n", - " print(f\"❌ Exception beim Schließen von Position {pos['ticket']}: {e}\")\n", - " \n", - " print(f\"📊 {success_count}/{len(position_info['details'])} Positionen erfolgreich geschlossen\")\n", - " return success_count == len(position_info['details'])\n", - "\n", - "\n", - "print(\"✅ Position Control functions defined (COMPLETE with close function!)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 5. Helper Functions" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Helper functions defined\n" - ] - } - ], - "source": [ - "def get_rates(timeframe=\"h4\", count=200, symbol=\"XAUUSD\"):\n", - " \"\"\"Hole Kursdaten\"\"\"\n", - " timeframes_dict = {\n", - " \"m1\": mt.TIMEFRAME_M1, \"m5\": mt.TIMEFRAME_M5, \"m15\": mt.TIMEFRAME_M15,\n", - " \"m30\": mt.TIMEFRAME_M30, \"h1\": mt.TIMEFRAME_H1, \"h4\": mt.TIMEFRAME_H4, \n", - " \"d1\": mt.TIMEFRAME_D1\n", - " }\n", - " try:\n", - " rates = mt.copy_rates_from_pos(symbol, timeframes_dict[timeframe], 0, count)\n", - " if rates is None: \n", - " return None\n", - " df = pd.DataFrame(rates)\n", - " df['time'] = pd.to_datetime(df['time'], unit='s')\n", - " df.set_index('time', inplace=True)\n", - " df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)\n", - " return df\n", - " except Exception as e:\n", - " print(f\"Error getting rates: {e}\")\n", - " return None\n", - "\n", - "\n", - "def check_risk_limits(symbol, volume=None, order_type=\"buy\", max_risk_per_trade=0.01):\n", - " \"\"\"Risk Management\"\"\"\n", - " try:\n", - " account_info = mt.account_info()\n", - " if not account_info: \n", - " return False\n", - " balance, equity = account_info.balance, account_info.equity\n", - " if equity < balance * 0.8: \n", - " return False\n", - " return True\n", - " except: \n", - " return False\n", - "\n", - "\n", - "def market_order(symbol, volume, order_type, stoploss=0, take_profit=0, deviation=20):\n", - " \"\"\"Market Order Execution\"\"\"\n", - " try:\n", - " price_dict = {'buy': mt.symbol_info_tick(symbol).ask, 'sell': mt.symbol_info_tick(symbol).bid}\n", - " order_type_dict = {'buy': mt.ORDER_TYPE_BUY, 'sell': mt.ORDER_TYPE_SELL}\n", - " \n", - " request = {\n", - " \"action\": mt.TRADE_ACTION_DEAL,\n", - " \"symbol\": symbol,\n", - " \"volume\": volume,\n", - " \"type\": order_type_dict[order_type],\n", - " \"price\": price_dict[order_type],\n", - " \"sl\": stoploss,\n", - " \"tp\": take_profit,\n", - " \"deviation\": deviation,\n", - " \"magic\": 234000,\n", - " \"comment\": strategy_name,\n", - " \"type_time\": mt.ORDER_TIME_GTC,\n", - " \"type_filling\": mt.ORDER_FILLING_IOC\n", - " }\n", - " return mt.order_send(request)\n", - " except Exception as e:\n", - " print(f\"Error in market order: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Helper functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6. Market Analysis Functions" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Market analysis functions defined (with RELAXED thresholds)\n" - ] - } - ], - "source": [ - "def detect_market_regime(df, lookback=50):\n", - " \"\"\"Market Regime Detection\"\"\"\n", - " try:\n", - " adx_data = ta.adx(df['high'], df['low'], df['close'], length=14)\n", - " adx = adx_data['ADX_14'].iloc[-1] if adx_data is not None and 'ADX_14' in adx_data.columns else 25.0\n", - " \n", - " try:\n", - " bb = ta.bbands(df['close'], length=20)\n", - " if bb is not None and len(bb.columns) >= 3:\n", - " bb_cols = bb.columns.tolist()\n", - " bb_width = ((bb[bb_cols[0]] - bb[bb_cols[2]]) / bb[bb_cols[1]] * 100).iloc[-lookback:].mean()\n", - " else: \n", - " bb_width = 4.0\n", - " except: \n", - " bb_width = 4.0\n", - " \n", - " price_range = df['high'].iloc[-lookback:].max() - df['low'].iloc[-lookback:].min()\n", - " atr_avg = df['atr'].iloc[-lookback:].mean()\n", - " range_ratio = price_range / (atr_avg * lookback) if atr_avg > 0 else 1.0\n", - " vol_cluster = df['atr'].iloc[-10:].std() / df['atr'].iloc[-50:].mean() if len(df) >= 50 else 1.0\n", - " \n", - " if adx > 25 and range_ratio > 1.5:\n", - " regime, strength = 'trending', min(100, adx * 2)\n", - " elif vol_cluster > 1.5:\n", - " regime, strength = 'volatile', min(100, vol_cluster * 50)\n", - " else:\n", - " regime, strength = 'ranging', max(0, 100 - adx * 2)\n", - " \n", - " return {\n", - " 'regime': regime, 'strength': strength, 'adx': adx, \n", - " 'bb_width': bb_width, 'range_ratio': range_ratio, 'vol_cluster': vol_cluster\n", - " }\n", - " except Exception as e:\n", - " return {\n", - " 'regime': 'ranging', 'strength': 50, 'adx': 20, \n", - " 'bb_width': 4.0, 'range_ratio': 1.0, 'vol_cluster': 1.0\n", - " }\n", - "\n", - "\n", - "def calculate_adaptive_confidence_threshold_relaxed(regime_info, base_confidence=60):\n", - " \"\"\"\n", - " RELAXED Version: Niedrigere Schwellen für mehr Signale\n", - " \"\"\"\n", - " regime = regime_info['regime']\n", - " adx = regime_info['adx']\n", - " \n", - " if regime == 'trending':\n", - " if adx > 30:\n", - " return max(50, base_confidence - 20)\n", - " else:\n", - " return base_confidence - 15\n", - " elif regime == 'ranging':\n", - " return base_confidence + 10\n", - " elif regime == 'volatile':\n", - " return base_confidence + 15\n", - " \n", - " return base_confidence\n", - "\n", - "\n", - "def get_enhanced_trend(timeframe=\"H4\", lookback=150, symbol=\"XAUUSD\"):\n", - " \"\"\"Enhanced Trend Analysis\"\"\"\n", - " tf_map = {\"D1\": \"d1\", \"H4\": \"h4\", \"H1\": \"h1\", \"M30\": \"m30\", \"M15\": \"m15\", \"M5\": \"m5\"}\n", - " tf = tf_map.get(timeframe, timeframe.lower())\n", - " \n", - " try:\n", - " df = get_rates(tf, lookback, symbol)\n", - " if df is None or len(df) < 50: \n", - " return None\n", - " \n", - " df['close_smooth'] = savgol_filter(df['close'], min(15, len(df)//10), 3)\n", - " X = np.arange(len(df)).reshape(-1, 1)\n", - " y = df['close_smooth'].values\n", - " model = LinearRegression().fit(X, y)\n", - " slope = model.coef_[0]\n", - " \n", - " regime_info = detect_market_regime(df.iloc[-50:])\n", - " base_threshold = df['atr'].iloc[-1] * 0.0001\n", - " \n", - " if regime_info['regime'] == 'trending':\n", - " slope_threshold = base_threshold * 0.7\n", - " elif regime_info['regime'] == 'ranging':\n", - " slope_threshold = base_threshold * 1.5\n", - " else:\n", - " slope_threshold = base_threshold * 1.2\n", - " \n", - " trend = \"uptrend\" if slope > slope_threshold else \"downtrend\" if slope < -slope_threshold else \"sideways\"\n", - " trend_strength = abs(slope) / slope_threshold if slope_threshold > 0 else 0\n", - " \n", - " return {\n", - " \"trend\": trend, \"slope\": slope, \"slope_threshold\": slope_threshold,\n", - " \"trend_strength\": trend_strength, \"atr\": df['atr'].iloc[-1],\n", - " \"price\": df['close'].iloc[-1], \"regime_info\": regime_info\n", - " }\n", - " except Exception as e:\n", - " print(f\"Error in get_enhanced_trend: {e}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ Market analysis functions defined (with RELAXED thresholds)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 7. Extended Top-Down Analysis" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ V1.6 Adaptive Complete Top-Down Analysis defined\n" - ] - } - ], - "source": [ - "def extended_top_down_v2_adaptive(symbol=\"XAUUSD\", lookback=150):\n", - " \"\"\"\n", - " V1.6 Adaptive Complete Version:\n", - " - Position Control\n", - " - Relaxed Trading Logic\n", - " - Adaptive Rhythm Integration\n", - " \"\"\"\n", - " \n", - " timeframes = [\"D1\", \"H4\", \"H1\", \"M30\", \"M15\", \"M5\"]\n", - " trend_info = {}\n", - " \n", - " print(f\"🔍 Analyzing {symbol} with V1.6 ADAPTIVE COMPLETE parameters...\")\n", - " \n", - " # 1. Alle Timeframes analysieren\n", - " for tf in timeframes:\n", - " trend_info[tf] = get_enhanced_trend(tf, lookback, symbol)\n", - " if trend_info[tf] is None:\n", - " print(f\"⚠️ Keine Daten für {tf}\")\n", - " return None\n", - " \n", - " # 2. Market Regime aus H4 bestimmen\n", - " main_regime = trend_info[\"H4\"][\"regime_info\"]\n", - " \n", - " # 3. RELAXED Adaptive Confidence Threshold\n", - " adaptive_confidence_threshold = calculate_adaptive_confidence_threshold_relaxed(main_regime)\n", - " \n", - " # 4. Standard-Trend\n", - " d1_trend = trend_info[\"D1\"][\"trend\"]\n", - " h4_trend = trend_info[\"H4\"][\"trend\"]\n", - " d1_strength = trend_info[\"D1\"][\"trend_strength\"]\n", - " h4_strength = trend_info[\"H4\"][\"trend_strength\"]\n", - " \n", - " if d1_trend == h4_trend and d1_trend != \"sideways\":\n", - " standard_trend = d1_trend\n", - " standard_strength = (d1_strength * 0.6 + h4_strength * 0.4)\n", - " elif d1_strength > h4_strength * 1.5:\n", - " standard_trend = d1_trend\n", - " standard_strength = d1_strength * 0.8\n", - " elif h4_strength > d1_strength * 1.5:\n", - " standard_trend = h4_trend\n", - " standard_strength = h4_strength * 0.8\n", - " else:\n", - " standard_trend = \"sideways\"\n", - " standard_strength = 0\n", - " \n", - " # 5. RELAXED Fast-Trend\n", - " fast_timeframes = [\"H1\", \"M30\", \"M15\", \"M5\"]\n", - " fast_trends = [trend_info[tf][\"trend\"] for tf in fast_timeframes]\n", - " fast_strengths = [trend_info[tf][\"trend_strength\"] for tf in fast_timeframes]\n", - " \n", - " required_alignment = 2 # RELAXED: Immer 2 von 4\n", - " \n", - " trend_counts = {'uptrend': 0, 'downtrend': 0, 'sideways': 0}\n", - " weighted_strengths = {'uptrend': 0, 'downtrend': 0}\n", - " weights = [1.0, 0.8, 0.6, 0.4]\n", - " \n", - " for i, (trend, strength) in enumerate(zip(fast_trends, fast_strengths)):\n", - " trend_counts[trend] += 1\n", - " if trend != 'sideways':\n", - " weighted_strengths[trend] += strength * weights[i]\n", - " \n", - " max_count = max(trend_counts['uptrend'], trend_counts['downtrend'])\n", - " if max_count >= required_alignment:\n", - " if trend_counts['uptrend'] > trend_counts['downtrend']:\n", - " fast_trend = \"uptrend\"\n", - " elif trend_counts['downtrend'] > trend_counts['uptrend']:\n", - " fast_trend = \"downtrend\"\n", - " else:\n", - " fast_trend = \"uptrend\" if weighted_strengths['uptrend'] > weighted_strengths['downtrend'] else \"downtrend\"\n", - " else:\n", - " fast_trend = \"sideways\"\n", - " \n", - " # 6. Top-Down-Trend\n", - " if standard_trend == fast_trend and standard_trend != \"sideways\":\n", - " top_down_trend = standard_trend\n", - " combined_strength = (standard_strength + weighted_strengths.get(fast_trend, 0)) / 2\n", - " else:\n", - " top_down_trend = \"sideways\"\n", - " combined_strength = 0\n", - " \n", - " # 7. Enhanced Confidence\n", - " tf_weights = {\"D1\": 2.5, \"H4\": 2.0, \"H1\": 1.5, \"M30\": 1.0, \"M15\": 0.8, \"M5\": 0.6}\n", - " \n", - " weighted_matching = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"] \n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] == top_down_trend and trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " weighted_total = sum(\n", - " tf_weights[tf] * trend_info[tf][\"trend_strength\"]\n", - " for tf in timeframes\n", - " if trend_info[tf][\"trend\"] != \"sideways\"\n", - " )\n", - " \n", - " confidence = round((weighted_matching / weighted_total) * 100, 2) if weighted_total > 0 else 0.0\n", - " \n", - " # 8. RELAXED Risk-Adjusted Signal Strength\n", - " atr = trend_info[\"M5\"][\"atr\"]\n", - " rrr = 2.5\n", - " risk_adjusted_strength = confidence * combined_strength * min(2.0, rrr)\n", - " \n", - " # 9. RELAXED Entry Signal\n", - " entry_signal = 0\n", - " signal_quality = \"none\"\n", - " min_strength = 80 # RELAXED: 80 statt 100\n", - " \n", - " if (top_down_trend != \"sideways\" and \n", - " confidence >= adaptive_confidence_threshold and\n", - " risk_adjusted_strength >= min_strength):\n", - " \n", - " entry_signal = 1 if top_down_trend == \"uptrend\" else -1\n", - " \n", - " # RELAXED Signal Quality\n", - " if confidence >= 80 and risk_adjusted_strength >= 130:\n", - " signal_quality = \"excellent\"\n", - " elif confidence >= 70 and risk_adjusted_strength >= 100:\n", - " signal_quality = \"good\"\n", - " else:\n", - " signal_quality = \"fair\"\n", - " \n", - " # 10. 🆕 Adaptive Rhythm Info\n", - " current_interval = rhythm_manager.current_interval\n", - " session = rhythm_manager.get_current_session()\n", - " \n", - " # 11. Debug Output\n", - " debug_data = []\n", - " for tf in timeframes:\n", - " info = trend_info[tf]\n", - " debug_data.append([\n", - " tf, info[\"trend\"], f\"{info['trend_strength']:.2f}\", \n", - " f\"{info['atr']:.4f}\", f\"{info['slope']:.6f}\", f\"{info['price']:.2f}\"\n", - " ])\n", - " \n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE Trend-Analyse für {symbol}\")\n", - " print(f\"⚡ Adaptive Interval: {current_interval} min | Session: {session.upper()}\")\n", - " print(f\"🎯 Market Regime: {main_regime['regime'].upper()} (Strength: {main_regime['strength']:.0f}%)\")\n", - " print(f\"🎚️ Adaptive Threshold: {adaptive_confidence_threshold}% (RELAXED)\")\n", - " print()\n", - " print(tabulate(debug_data, headers=[\"TF\", \"Trend\", \"Strength\", \"ATR\", \"Slope\", \"Price\"], tablefmt=\"psql\"))\n", - " print(f\"\\n➡️ Standard-Trend: {standard_trend} (Strength: {standard_strength:.2f})\")\n", - " print(f\"➡️ Fast-Trend: {fast_trend} (Required: {required_alignment}/4)\")\n", - " print(f\"➡️ Top-Down-Trend: {top_down_trend}\")\n", - " print(f\"➡️ Confidence: {confidence}% (Threshold: {adaptive_confidence_threshold}%)\")\n", - " print(f\"➡️ Risk-Adjusted Strength: {risk_adjusted_strength:.1f} (Min: {min_strength})\")\n", - " print(f\"➡️ Signal Quality: {signal_quality.upper()}\")\n", - " print(f\"\\n🚀 V1.6 Adaptive Complete: Full Features + Adaptive Rhythm\")\n", - " \n", - " return {\n", - " \"symbol\": symbol,\n", - " \"trend_info\": trend_info,\n", - " \"market_regime\": main_regime,\n", - " \"standard_trend\": standard_trend,\n", - " \"fast_trend\": fast_trend,\n", - " \"top_down_trend\": top_down_trend,\n", - " \"confidence\": confidence,\n", - " \"adaptive_threshold\": adaptive_confidence_threshold,\n", - " \"risk_adjusted_strength\": risk_adjusted_strength,\n", - " \"entry_signal\": entry_signal,\n", - " \"signal_quality\": signal_quality,\n", - " \"combined_strength\": combined_strength,\n", - " \"min_strength_used\": min_strength,\n", - " \"required_alignment\": required_alignment,\n", - " \"adaptive_interval\": current_interval,\n", - " \"session\": session\n", - " }\n", - "\n", - "\n", - "print(\"✅ V1.6 Adaptive Complete Top-Down Analysis defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 8. Entry Timing Optimization" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Entry timing functions defined (DISABLED in Relaxed mode)\n" - ] - } - ], - "source": [ - "def check_pullback_entry(symbol, signal_info, timeframe=\"M5\"):\n", - " \"\"\"\n", - " Entry Timing Check - in Relaxed Version DISABLED per default\n", - " \"\"\"\n", - " if signal_info[\"entry_signal\"] == 0:\n", - " return False, \"No base signal\"\n", - " \n", - " try:\n", - " df = get_rates(timeframe.lower(), 50, symbol)\n", - " if df is None or len(df) < 20:\n", - " return False, \"Insufficient data\"\n", - " \n", - " df['ema21'] = df['close'].ewm(span=21).mean()\n", - " df['ema50'] = df['close'].ewm(span=50).mean()\n", - " \n", - " current_price = df['close'].iloc[-1]\n", - " ema21 = df['ema21'].iloc[-1]\n", - " ema50 = df['ema50'].iloc[-1]\n", - " signal_direction = signal_info[\"entry_signal\"]\n", - " \n", - " if signal_direction == 1: # Long\n", - " if current_price <= ema21 * 1.002 and ema21 > ema50:\n", - " return True, \"Pullback to EMA21 for Long\"\n", - " elif current_price <= ema21 * 0.998:\n", - " return True, \"Below EMA21 - Good Long Entry\"\n", - " elif signal_direction == -1: # Short\n", - " if current_price >= ema21 * 0.998 and ema21 < ema50:\n", - " return True, \"Pullback to EMA21 for Short\"\n", - " elif current_price >= ema21 * 1.002:\n", - " return True, \"Above EMA21 - Good Short Entry\"\n", - " \n", - " return False, \"Waiting for better entry timing\"\n", - " except Exception as e:\n", - " return True, \"Using immediate entry (fallback)\"\n", - "\n", - "\n", - "print(\"✅ Entry timing functions defined (DISABLED in Relaxed mode)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 9. Execute Trade Function" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "def calculate_position_size(self, symbol, stop_loss_pips, max_risk_per_trade=0.02):\n", - " \"\"\"\n", - " Berechnet die Positionsgröße basierend auf Risiko\n", - " \"\"\"\n", - " account_info = mt.account_info()\n", - " if not account_info:\n", - " print(f\"⚠️ Keine Account-Info verfügbar, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " balance = account_info.balance\n", - " risk_amount = balance * max_risk_per_trade\n", - " \n", - " # Symbol-Info holen\n", - " symbol_info = mt.symbol_info(symbol)\n", - " if not symbol_info:\n", - " print(f\"⚠️ Keine Symbol-Info für {symbol}, verwende Minimum-Lot\")\n", - " return 0.01\n", - " \n", - " # Pip-Wert berechnen\n", - " point = symbol_info.point\n", - " tick_value = symbol_info.trade_tick_value\n", - " tick_size = symbol_info.trade_tick_size\n", - " \n", - " # Volume berechnen\n", - " pip_value = (tick_value / tick_size) * point\n", - " volume = risk_amount / (stop_loss_pips * pip_value)\n", - " \n", - " # Auf erlaubte Volumenschritte runden\n", - " volume_min = symbol_info.volume_min\n", - " volume_max = symbol_info.volume_max\n", - " volume_step = symbol_info.volume_step\n", - " \n", - " volume = round(volume / volume_step) * volume_step\n", - " volume = max(volume_min, min(volume_max, volume))\n", - " \n", - " print(f\"💰 Position Sizing für {symbol}:\")\n", - " print(f\" Balance: ${balance:.2f}\")\n", - " print(f\" Risiko: ${risk_amount:.2f} ({max_risk_per_trade*100}%)\")\n", - " print(f\" Stop Loss: {stop_loss_pips:.2f} Pips\")\n", - " print(f\" Berechnetes Volume: {volume:.2f} Lots\")\n", - " \n", - " return volume" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.01" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#mt.symbol_info(symbol).volume_min\n", - "mt.symbol_info(symbol).volume_step" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ V1.6 Adaptive Complete Execute Trade defined\n" - ] - } - ], - "source": [ - "def execute_trade_v2_adaptive(\n", - " symbol=\"XAUUSD\",\n", - " atr_mult=1.5,\n", - " base_confidence=60,\n", - " max_risk_per_trade=0.01,\n", - " risk_filter=True,\n", - " min_atr=0.0008,\n", - " use_pullback_entry=False, # DISABLED\n", - " max_positions=1,\n", - " strategy_name=\"TradingBot_V1.6\",\n", - " debug=True\n", - "):\n", - " \"\"\"\n", - " V1.6 Adaptive Complete Trade-Ausführung:\n", - " - Position Control\n", - " - Relaxed Parameter\n", - " - Adaptive Rhythm Integration\n", - " \"\"\"\n", - " \n", - " # SCHRITT 1: POSITION CHECK\n", - " print(f\"\\n🔍 POSITION CHECK für {symbol} (V1.6 Adaptive Complete)\")\n", - " has_position, position_info = check_existing_positions(symbol, strategy_name)\n", - " \n", - " if has_position and position_info['count'] >= max_positions:\n", - " if debug:\n", - " print(f\"🛑 TRADE BLOCKIERT: {position_info['count']}/{max_positions} Positionen aktiv\")\n", - " for pos in position_info['details']:\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\" {pos['type']} @ {pos['price_open']} | {profit_emoji} {pos['profit']:.2f}\")\n", - " return None\n", - " \n", - " print(f\"✅ Position-Check OK: {position_info['count']}/{max_positions}\")\n", - " \n", - " # SCHRITT 2: Signal Analysis\n", - " signal_info = extended_top_down_v2_adaptive(symbol)\n", - " if signal_info is None:\n", - " print(\"❌ Signal-Analyse fehlgeschlagen\")\n", - " return None\n", - " \n", - " entry_signal = signal_info[\"entry_signal\"]\n", - " confidence = signal_info[\"confidence\"]\n", - " adaptive_threshold = signal_info[\"adaptive_threshold\"]\n", - " signal_quality = signal_info[\"signal_quality\"]\n", - " market_regime = signal_info[\"market_regime\"]\n", - " \n", - " # SCHRITT 3: Get Price/ATR\n", - " m5_info = signal_info[\"trend_info\"][\"M5\"]\n", - " price = m5_info[\"price\"]\n", - " atr = m5_info[\"atr\"]\n", - " \n", - " # SCHRITT 4: Pre-checks\n", - " reason = \"\"\n", - " \n", - " if confidence < adaptive_threshold:\n", - " reason = f\"Confidence {confidence}% < threshold {adaptive_threshold}%\"\n", - " elif entry_signal == 0:\n", - " reason = f\"No entry signal\"\n", - " elif price is None or atr is None:\n", - " reason = \"Price/ATR not available\"\n", - " elif risk_filter and atr < min_atr:\n", - " reason = f\"ATR {atr:.5f} < min_atr {min_atr}\"\n", - " else:\n", - " risk_ok = check_risk_limits(symbol, max_risk_per_trade=max_risk_per_trade)\n", - " if not risk_ok:\n", - " reason = \"Risk limits exceeded\"\n", - " \n", - " # SCHRITT 5: Execute Trade\n", - " if not reason:\n", - " # Final Position Check\n", - " final_check, _ = check_existing_positions(symbol, strategy_name)\n", - " if final_check:\n", - " print(f\"🛑 Position wurde zwischen Checks eröffnet!\")\n", - " return None\n", - " \n", - " # SL/TP Calculation\n", - " regime_mult = 1.0\n", - " if market_regime['regime'] == 'volatile':\n", - " regime_mult = 1.2\n", - " elif market_regime['regime'] == 'ranging':\n", - " regime_mult = 0.9\n", - " \n", - " adjusted_atr_mult = atr_mult * regime_mult\n", - " \n", - " if entry_signal == 1: # Long\n", - " stop_loss = price - adjusted_atr_mult * atr\n", - " take_profit = price + adjusted_atr_mult * atr * 2.5\n", - " else: # Short\n", - " stop_loss = price + adjusted_atr_mult * atr\n", - " take_profit = price - adjusted_atr_mult * atr * 2.5\n", - " \n", - " # Position Sizing\n", - " account_info = mt.account_info()\n", - " if account_info:\n", - " balance = account_info.balance\n", - " risk_amount = balance * max_risk_per_trade\n", - " if symbol == \"XAUUSD\":\n", - " # 🎯 ADAPTIVE POSITION SIZING\n", - " if 'adv_position_mgr' in globals() and adv_position_mgr.adaptive_sizing:\n", - " volume = adv_position_mgr.adaptive_sizing.calculate_position_size(\n", - " confidence=confidence,\n", - " balance=balance,\n", - " stop_loss_distance=adjusted_atr_mult * atr * 10000, # Convert to pips\n", - " symbol=symbol\n", - " )\n", - " else:\n", - " volume = round(min(0.1, max(0.01, risk_amount / (adjusted_atr_mult * atr * 100))),2)\n", - " else:\n", - " volume = 0.01\n", - " else:\n", - " volume = 0.01\n", - " \n", - " # Log Trade Info\n", - " print(f\"\\n🚀 V1.6 ADAPTIVE COMPLETE TRADE EXECUTION\")\n", - " print(f\"Direction: {'LONG' if entry_signal == 1 else 'SHORT'}\")\n", - " print(f\"Price: {price:.5f} | Volume: {volume:.2f}\")\n", - " print(f\"SL: {stop_loss:.5f} | TP: {take_profit:.5f}\")\n", - " print(f\"Confidence: {confidence}% | Quality: {signal_quality.upper()}\")\n", - " print(f\"Regime: {market_regime['regime'].upper()}\")\n", - " print(f\"Adaptive Interval: {signal_info['adaptive_interval']} min\")\n", - " print(f\"Session: {signal_info['session'].upper()}\")\n", - " \n", - " # Execute\n", - " try:\n", - " order_result = market_order(\n", - " symbol=symbol,\n", - " volume=volume,\n", - " order_type=\"buy\" if entry_signal == 1 else \"sell\",\n", - " stoploss=stop_loss,\n", - " take_profit=take_profit\n", - " )\n", - " \n", - " if order_result and order_result.retcode == mt.TRADE_RETCODE_DONE:\n", - " print(f\"✅ Trade erfolgreich! Ticket: {order_result.order}\")\n", - " \n", - " # ==========================================\n", - " # LOG TRADE ENTRY (V1.8)\n", - " # ==========================================\n", - " try:\n", - " # Hole Position Info\n", - " positions = mt.positions_get(symbol=symbol)\n", - " if positions and infra:\n", - " position = positions[0]\n", - "\n", - " # Erstelle Trade Data\n", - " trade_data = {\n", - " 'ticket': position.ticket,\n", - " 'position_id': position.identifier,\n", - " 'symbol': symbol,\n", - " 'strategy_name': strategy_name,\n", - " 'type': 'BUY' if entry_signal == 1 else 'SELL',\n", - " 'volume': volume,\n", - " 'entry_price': position.price_open,\n", - " 'sl_price': position.sl,\n", - " 'tp_price': position.tp,\n", - " 'entry_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),\n", - " 'session': rhythm_manager.get_current_session(),\n", - " 'regime': market_regime['regime'],\n", - " 'quality': signal_quality,\n", - " 'confidence': confidence if 'confidence' in locals() else None,\n", - " 'timeframe_alignment': signal_info.get('required_alignment', 2),\n", - " 'risk_amount': risk_amount if 'risk_amount' in locals() else None,\n", - " 'risk_pct': max_risk_per_trade\n", - " }\n", - "\n", - " # Log to Database + Send Telegram\n", - " infra.log_trade_entry(trade_data)\n", - " logger.info(\"📱 Trade logged to DB + Telegram notification sent\")\n", - "\n", - " except Exception as e:\n", - " logger.error(f\"⚠️ Infrastructure logging failed: {e}\")\n", - " # ==========================================\n", - "\n", - "\n", - " # Verify & Log\n", - " new_check, new_info = check_existing_positions(symbol, strategy_name)\n", - " print(f\"📊 Positionen: {new_info['count']}\")\n", - " log_trade_performance_adaptive(signal_info, order_result)\n", - " else:\n", - " print(f\"❌ Trade failed: {order_result.comment if order_result else 'No result'}\")\n", - " \n", - " return order_result\n", - " \n", - " except Exception as e:\n", - " print(f\"❌ Execution failed: {e}\")\n", - " return None\n", - " \n", - " else:\n", - " if debug:\n", - " print(f\"\\n⏸️ TRADE SKIPPED: {reason}\")\n", - " return None\n", - "\n", - "\n", - "print(\"✅ V1.6 Adaptive Complete Execute Trade defined\")" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Ranging Filter activated!\n", - " 🛑 Blocks ALL ranging market trades\n", - " ✅ Only allows trending markets with ADX > 25\n" - ] - } - ], - "source": [ - "# ==========================================\n", - "# 🔥 FIX #1: RANGING FILTER WRAPPER (09.12.2025)\n", - "# ==========================================\n", - "\n", - "# Original function wird wrapped\n", - "_original_execute_trade_v2_adaptive = execute_trade_v2_adaptive\n", - "\n", - "def execute_trade_v2_adaptive_with_ranging_filter(\n", - " symbol=\"XAUUSD\",\n", - " atr_mult=1.5,\n", - " base_confidence=60,\n", - " max_risk_per_trade=0.01,\n", - " risk_filter=True,\n", - " min_atr=0.0008,\n", - " use_pullback_entry=False,\n", - " max_positions=1,\n", - " strategy_name=\"TradingBot_V1.6\",\n", - " debug=True):\n", - " \"\"\"\n", - " Wrapper für execute_trade_v2_adaptive mit Ranging Filter\n", - " Blocks trading in ranging markets - they cause 100% of losses!\n", - " \"\"\"\n", - "\n", - " # Quick check: Get signal info first\n", - " signal_info = extended_top_down_v2_adaptive(symbol)\n", - " if signal_info is None:\n", - " return None\n", - "\n", - " market_regime = signal_info.get(\"market_regime\", {})\n", - " regime = market_regime.get('regime', 'unknown')\n", - " adx = market_regime.get('adx', 0)\n", - "\n", - " # 🛑 RANGING FILTER - Block ALL ranging market trades\n", - " if regime == 'ranging':\n", - " if debug:\n", - " print(f\"\\n🛑 TRADE BLOCKIERT: Ranging Market!\")\n", - " print(f\" ADX: {adx:.1f} (< 25 = Ranging)\")\n", - " print(f\" 📊 Ranging Performance: 0% Win Rate, 20 consecutive losses\")\n", - " print(f\" ✅ Filter is protecting you from losses!\")\n", - " return None\n", - "\n", - " # Additional safety: Even in trending, ADX must be > 25\n", - " if regime == 'trending' and adx < 25:\n", - " if debug:\n", - " print(f\"\\n🛑 TRADE BLOCKIERT: Weak Trend!\")\n", - " print(f\" ADX: {adx:.1f} (< 25 = too weak)\")\n", - " return None\n", - "\n", - " # ✅ Regime check passed - execute original function\n", - " if debug:\n", - " print(f\"✅ REGIME CHECK PASSED: {regime.upper()} (ADX {adx:.1f})\")\n", - "\n", - " return _original_execute_trade_v2_adaptive(\n", - " symbol=symbol,\n", - " atr_mult=atr_mult,\n", - " base_confidence=base_confidence,\n", - " max_risk_per_trade=max_risk_per_trade,\n", - " risk_filter=risk_filter,\n", - " min_atr=min_atr,\n", - " use_pullback_entry=use_pullback_entry,\n", - " max_positions=max_positions,\n", - " strategy_name=strategy_name,\n", - " debug=debug\n", - " )\n", - "\n", - "# Replace original with wrapped version\n", - "execute_trade_v2_adaptive = execute_trade_v2_adaptive_with_ranging_filter\n", - "\n", - "print(\"✅ Ranging Filter activated!\")\n", - "print(\" 🛑 Blocks ALL ranging market trades\")\n", - "print(\" ✅ Only allows trending markets with ADX > 25\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "⚠️ check_open_positions not found - skipping Position Monitor fix\n" - ] - } - ], - "source": [ - "# ==========================================\n", - "# 🔥 FIX #2: POSITION MONITOR DB LOGGING (09.12.2025)\n", - "# ==========================================\n", - "\n", - "# Wrap check_open_positions to add DB logging\n", - "if 'check_open_positions' in globals():\n", - " _original_check_open_positions = check_open_positions\n", - "\n", - " def check_open_positions_with_db_logging():\n", - " \"\"\"\n", - " Enhanced position monitor that writes exits to database\n", - " \"\"\"\n", - " from datetime import datetime\n", - "\n", - " # Get current open positions from MT5\n", - " positions = mt.positions_get(symbol=symbol)\n", - "\n", - " if not positions or len(positions) == 0:\n", - " # Check if we have positions in DB that should be closed\n", - " if 'db' in globals():\n", - " try:\n", - " open_trades_in_db = db.get_open_trades()\n", - "\n", - " for trade in open_trades_in_db:\n", - " ticket = trade['ticket']\n", - "\n", - " # Check if this position is in MT5 history (closed)\n", - " deals = mt.history_deals_get(ticket=ticket)\n", - " if deals and len(deals) > 0:\n", - " # Position was closed - log to DB\n", - " last_deal = deals[-1]\n", - "\n", - " db.close_trade(\n", - " ticket=ticket,\n", - " exit_price=last_deal.price,\n", - " exit_time=datetime.fromtimestamp(last_deal.time),\n", - " profit=last_deal.profit,\n", - " status='closed',\n", - " exit_reason='mt5_detected',\n", - " commission=last_deal.commission,\n", - " swap=last_deal.swap\n", - " )\n", - "\n", - " logger.info(f\"💾 Position #{ticket} exit logged to DB (profit: ${last_deal.profit:.2f})\")\n", - "\n", - " except Exception as e:\n", - " logger.error(f\"⚠️ DB logging error: {e}\")\n", - "\n", - " # Call original function\n", - " return _original_check_open_positions()\n", - "\n", - " # Replace\n", - " check_open_positions = check_open_positions_with_db_logging\n", - " print(\"✅ Position Monitor DB logging activated!\")\n", - " print(\" 💾 Exits will be written to SQLite database\")\n", - " print(\" 📊 Drawdown Protection will work correctly\")\n", - "else:\n", - " print(\"⚠️ check_open_positions not found - skipping Position Monitor fix\")\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 10. Performance Monitoring & Logging" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Performance Monitoring functions defined (with adaptive features)\n" - ] - } - ], - "source": [ - "def log_trade_performance_adaptive(signal_info, order_result):\n", - " \"\"\"\n", - " Loggt Trade-Performance für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " trade_data = {\n", - " 'timestamp': datetime.now().isoformat(),\n", - " 'version': 'V1.6_Adaptive_Complete',\n", - " 'symbol': signal_info['symbol'],\n", - " 'entry_signal': signal_info['entry_signal'],\n", - " 'confidence': signal_info['confidence'],\n", - " 'adaptive_threshold': signal_info['adaptive_threshold'],\n", - " 'signal_quality': signal_info['signal_quality'],\n", - " 'market_regime': signal_info['market_regime']['regime'],\n", - " 'regime_strength': signal_info['market_regime']['strength'],\n", - " 'risk_adjusted_strength': signal_info['risk_adjusted_strength'],\n", - " 'adaptive_interval': signal_info['adaptive_interval'],\n", - " 'session': signal_info['session'],\n", - " 'relaxed_features': {\n", - " 'pullback_entry_disabled': True,\n", - " 'lower_confidence_threshold': True,\n", - " 'lower_min_strength': True,\n", - " 'fixed_tf_alignment': True\n", - " },\n", - " 'adaptive_features': {\n", - " 'adaptive_rhythm': True,\n", - " 'session_aware': True,\n", - " 'volatility_based': True\n", - " },\n", - " 'position_control_active': True,\n", - " 'order_result': str(order_result) if order_result else None\n", - " }\n", - " \n", - " try:\n", - " filename = f\"trade_performance_v16_{signal_info['symbol']}_{datetime.now().strftime('%Y%m')}.json\"\n", - " try:\n", - " with open(filename, 'r') as f: \n", - " data = json.load(f)\n", - " except FileNotFoundError: \n", - " data = []\n", - " data.append(trade_data)\n", - " with open(filename, 'w') as f: \n", - " json.dump(data, f, indent=2)\n", - " print(f\"📊 Performance logged to {filename}\")\n", - " except Exception as e:\n", - " print(f\"Warning: Could not log performance: {e}\")\n", - "\n", - "\n", - "def analyze_performance_adaptive(symbol=\"XAUUSD\", days_back=30):\n", - " \"\"\"\n", - " Analysiert Performance der V1.6 Adaptive Complete Version\n", - " \"\"\"\n", - " try:\n", - " filename = f\"trade_performance_v16_{symbol}_{datetime.now().strftime('%Y%m')}.json\"\n", - " \n", - " with open(filename, 'r') as f:\n", - " data = json.load(f)\n", - " \n", - " cutoff = datetime.now() - timedelta(days=days_back)\n", - " recent_trades = [\n", - " trade for trade in data \n", - " if datetime.fromisoformat(trade['timestamp']) > cutoff\n", - " ]\n", - " \n", - " if not recent_trades:\n", - " print(f\"No V1.6 trades in last {days_back} days\")\n", - " return\n", - " \n", - " total_trades = len(recent_trades)\n", - " \n", - " # Analysis by regime\n", - " by_regime = {}\n", - " for trade in recent_trades:\n", - " regime = trade['market_regime']\n", - " by_regime[regime] = by_regime.get(regime, 0) + 1\n", - " \n", - " # Analysis by interval\n", - " by_interval = {}\n", - " for trade in recent_trades:\n", - " interval = trade.get('adaptive_interval', 'unknown')\n", - " by_interval[interval] = by_interval.get(interval, 0) + 1\n", - " \n", - " # Analysis by session\n", - " by_session = {}\n", - " for trade in recent_trades:\n", - " session = trade.get('session', 'unknown')\n", - " by_session[session] = by_session.get(session, 0) + 1\n", - " \n", - " # Print results\n", - " print(f\"\\n📊 V1.6 ADAPTIVE COMPLETE PERFORMANCE - Last {days_back} days\")\n", - " print(f\"Total Trades: {total_trades}\")\n", - " \n", - " print(f\"\\nBy Market Regime:\")\n", - " for regime, count in by_regime.items():\n", - " print(f\" {regime.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Adaptive Interval:\")\n", - " for interval, count in sorted(by_interval.items()):\n", - " print(f\" {interval} min: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " print(f\"\\n🆕 By Trading Session:\")\n", - " for session, count in by_session.items():\n", - " print(f\" {session.upper()}: {count} ({count/total_trades*100:.1f}%)\")\n", - " \n", - " except Exception as e:\n", - " print(f\"Could not analyze performance: {e}\")\n", - "\n", - "\n", - "print(\"✅ Performance Monitoring functions defined (with adaptive features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 11. 🆕 Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "🔧 Force resuming trading after Ranging Filter deployment...\n", - "⚠️ drawdown_protection not initialized yet\n" - ] - } - ], - "source": [ - "# ==========================================\n", - "# FORCE RESUME TRADING (V2.2 FIX)\n", - "# ==========================================\n", - "\n", - "print(\"🔧 Force resuming trading after Ranging Filter deployment...\")\n", - "\n", - "if 'drawdown_protection' in globals():\n", - " # Force resume\n", - " drawdown_protection._resume_trading()\n", - " \n", - " # Verify\n", - " can_trade, reason = drawdown_protection.can_trade()\n", - " \n", - " print(f\"\\n✅ Status after resume:\")\n", - " print(f\" Can Trade: {can_trade}\")\n", - " print(f\" Reason: {reason if not can_trade else 'All clear!'}\")\n", - " \n", - " if not can_trade:\n", - " print(\"\\n⚠️ Still blocked - using nuclear option...\")\n", - " drawdown_protection.trading_paused = False\n", - " drawdown_protection.pause_until = None\n", - " drawdown_protection.pause_reason = None\n", - " \n", - " can_trade2, reason2 = drawdown_protection.can_trade()\n", - " print(f\" After force clear: {can_trade2}\")\n", - " \n", - " print(\"\\n🛡️ Drawdown Protection Status:\")\n", - " status = drawdown_protection.get_status()\n", - " print(f\" Consecutive Losses: {status['consecutive_losses']}\")\n", - " print(f\" Trading Allowed: {status['trading_allowed']}\")\n", - " \n", - "else:\n", - " print(\"⚠️ drawdown_protection not initialized yet\")" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "🔧 Setting up Trading Check...\n", - "✅ Session Filter aktiviert!\n", - " Deaktivierte Sessions:\n", - " • ASIAN : ✅ AKTIV\n", - " • LONDON : ❌ DEAKTIVIERT\n", - " • OVERLAP : ❌ DEAKTIVIERT\n", - " • NY : ✅ AKTIV\n", - "\n", - "🛡️ Drawdown Protection aktiviert!\n", - " • Daily Loss Limit: $100\n", - " • Weekly Loss Limit: $300\n", - " • Monthly Loss Limit: $800\n", - " • Max Consecutive Losses: 5\n", - " • Cooldown: 24h\n", - "\n", - "✅ Trading Check ist jetzt vollständig geschützt!\n", - " 📊 Session Filter: Aktiv\n", - " 🛡️ Drawdown Protection: Aktiv\n" - ] - } - ], - "source": [ - "# ==========================================\n", - "# TRADING CHECK: SESSION FILTER + DRAWDOWN PROTECTION\n", - "# ==========================================\n", - "\n", - "from session_filter_patch import (\n", - " create_session_filtered_check,\n", - " SESSION_WHITELIST_CONFIG,\n", - " is_session_allowed\n", - ")\n", - "from drawdown_protection import create_protected_trading_check\n", - "\n", - "print(\"🔧 Setting up Trading Check...\")\n", - "\n", - "# Step 1: Create base session-filtered trading check\n", - "base_trading_check = create_session_filtered_check(\n", - " rhythm_manager=rhythm_manager,\n", - " execute_func=execute_trade_v2_adaptive,\n", - " symbol=symbol,\n", - " strategy_name=strategy_name,\n", - " max_positions=max_positions,\n", - " logger=logger,\n", - " datetime=datetime\n", - ")\n", - "\n", - "print(\"✅ Session Filter aktiviert!\")\n", - "print(\" Deaktivierte Sessions:\")\n", - "for session, enabled in SESSION_WHITELIST_CONFIG['enabled_sessions'].items():\n", - " status = \"✅ AKTIV\" if enabled else \"❌ DEAKTIVIERT\"\n", - " print(f\" • {session.upper():8s}: {status}\")\n", - "\n", - "# Step 2: Wrap with Drawdown Protection\n", - "adaptive_trading_check = create_protected_trading_check(infra, base_trading_check)\n", - "drawdown_protection = adaptive_trading_check.protection\n", - "\n", - "print(\"\\n🛡️ Drawdown Protection aktiviert!\")\n", - "print(f\" • Daily Loss Limit: ${drawdown_protection.max_daily_loss}\")\n", - "print(f\" • Weekly Loss Limit: ${drawdown_protection.max_weekly_loss}\")\n", - "print(f\" • Monthly Loss Limit: ${drawdown_protection.max_monthly_loss}\")\n", - "print(f\" • Max Consecutive Losses: {drawdown_protection.max_consecutive_losses}\")\n", - "print(f\" • Cooldown: {drawdown_protection.cooldown_hours}h\")\n", - "\n", - "print(\"\\n✅ Trading Check ist jetzt vollständig geschützt!\")\n", - "print(\" 📊 Session Filter: Aktiv\")\n", - "print(\" 🛡️ Drawdown Protection: Aktiv\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2025-12-10 09:27:00,491 - INFO - ✅ Trading resumed after: None\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Trading force-resumed (Ranging Filter deployed)\n" - ] - } - ], - "source": [ - "# Force resume after restart (V2.2 fix)\n", - "drawdown_protection._resume_trading()\n", - "print(\"✅ Trading force-resumed (Ranging Filter deployed)\")" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "# def adaptive_trading_check():\n", - "# \"\"\"\n", - "# 🆕 V1.6: Adaptive Trading Check\n", - "# Prüft basierend auf optimalem Intervall ob gehandelt werden soll\n", - "# \"\"\"\n", - "# try:\n", - "# optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "# current_minute = datetime.now().minute\n", - " \n", - "# # Trading nur zu berechneten Zeitpunkten\n", - "# if current_minute % optimal_interval == 0:\n", - "# logger.info(f\"\\n⏰ {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} - ADAPTIVE Check\")\n", - "# logger.info(f\"Intervall: {optimal_interval} min\")\n", - " \n", - "# # Führe Trading aus\n", - "# execute_trade_v2_adaptive(\n", - "# symbol=symbol,\n", - "# strategy_name=strategy_name,\n", - "# max_positions=max_positions\n", - "# )\n", - " \n", - "# except Exception as e:\n", - "# logger.error(f\"Fehler im Adaptive Trading Check: {e}\")\n", - "\n", - "\n", - "def print_status_report():\n", - " \"\"\"Status-Report\"\"\"\n", - " print(rhythm_manager.get_status_report())\n", - "\n", - "\n", - "# print(\"✅ Adaptive Scheduler functions defined\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 12. ✅ KORRIGIERT: Trading Configuration" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "⚙️ V1.6 Adaptive Complete Configuration:\n", - "\n", - "🛡️ Position Control:\n", - " Max Positions: 1\n", - " Strategy: TradingBot_V1.6\n", - "\n", - "🚀 Relaxed Parameters:\n", - " Base Confidence: 60%\n", - " Min ATR: 0.0008\n", - " Pullback Entry: False\n", - "\n", - "⚡ Adaptive Features:\n", - " Dynamic Intervals: 5/15/30 min\n", - " Session-aware: Yes\n", - " Volatility-based: Yes\n", - "\n", - "✅ Configuration complete!\n" - ] - } - ], - "source": [ - "# ✅ KORRIGIERT: Zentrale Konfiguration (fehlte in ursprünglicher V1.6)\n", - "ADAPTIVE_COMPLETE_CONFIG = {\n", - " 'symbol': symbol,\n", - " 'atr_mult': 1.5,\n", - " 'base_confidence': 60, # RELAXED\n", - " 'max_risk_per_trade': 0.01,\n", - " 'risk_filter': True,\n", - " 'min_atr': 0.0008, # RELAXED\n", - " 'use_pullback_entry': False, # DISABLED\n", - " 'max_positions': max_positions,\n", - " 'strategy_name': strategy_name,\n", - " 'debug': True\n", - "}\n", - "\n", - "print(\"⚙️ V1.6 Adaptive Complete Configuration:\")\n", - "print(\"\\n🛡️ Position Control:\")\n", - "print(f\" Max Positions: {ADAPTIVE_COMPLETE_CONFIG['max_positions']}\")\n", - "print(f\" Strategy: {ADAPTIVE_COMPLETE_CONFIG['strategy_name']}\")\n", - "\n", - "print(\"\\n🚀 Relaxed Parameters:\")\n", - "print(f\" Base Confidence: {ADAPTIVE_COMPLETE_CONFIG['base_confidence']}%\")\n", - "print(f\" Min ATR: {ADAPTIVE_COMPLETE_CONFIG['min_atr']}\")\n", - "print(f\" Pullback Entry: {ADAPTIVE_COMPLETE_CONFIG['use_pullback_entry']}\")\n", - "\n", - "print(\"\\n⚡ Adaptive Features:\")\n", - "print(f\" Dynamic Intervals: 5/15/30 min\")\n", - "print(f\" Session-aware: Yes\")\n", - "print(f\" Volatility-based: Yes\")\n", - "\n", - "print(\"\\n✅ Configuration complete!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 13. ✅ KORRIGIERT: Status & Monitoring Functions" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Status monitoring function defined (COMPLETE with all features)\n" - ] - } - ], - "source": [ - "# ✅ KORRIGIERT: Umfassendes Status Monitoring (fehlte in V1.6)\n", - "def check_adaptive_bot_status():\n", - " \"\"\"\n", - " ✅ NEU: Kombiniertes Status-Check für V1.6 Adaptive Complete\n", - " Kombiniert Position Control + Adaptive Rhythm Status\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔍 V1.6 ADAPTIVE COMPLETE BOT STATUS\")\n", - " print(\"=\"*70)\n", - " \n", - " # System Status\n", - " print(\"\\n📡 SYSTEM STATUS:\")\n", - " print(f\" MT5 Connection: {'✅' if mt.terminal_info() else '❌'}\")\n", - " print(f\" Scheduler Running: {'✅' if scheduler.running else '❌'}\")\n", - " print(f\" Active Jobs: {len(scheduler.get_jobs())}\")\n", - " \n", - " # Adaptive Rhythm Status\n", - " print(\"\\n⚡ ADAPTIVE RHYTHM:\")\n", - " optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - " session = rhythm_manager.get_current_session()\n", - " df = rhythm_manager.get_market_data()\n", - " \n", - " if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\" Current Interval: {optimal_interval} min\")\n", - " print(f\" Trading Session: {session.upper()}\")\n", - " print(f\" ATR (H1): {atr:.2f}\")\n", - " print(f\" Volatility: {vol_level.upper()}\")\n", - " else:\n", - " print(\" ⚠️ Could not fetch market data\")\n", - " \n", - " # Position Status\n", - " print(\"\\n🛡️ POSITION CONTROL:\")\n", - " has_pos, pos_info = check_existing_positions(symbol, strategy_name)\n", - " print(f\" Active Positions: {pos_info['count']}/{max_positions}\")\n", - " print(f\" Trading Status: {'🛑 BLOCKED' if has_pos else '✅ READY'}\")\n", - " \n", - " if has_pos:\n", - " for i, pos in enumerate(pos_info['details'], 1):\n", - " profit_emoji = \"🟢\" if pos['profit'] >= 0 else \"🔴\"\n", - " print(f\" Position {i}: {pos['type']} | {profit_emoji} {pos['profit']:.2f}\")\n", - " \n", - " # Signal Status\n", - " print(\"\\n📊 CURRENT SIGNAL:\")\n", - " try:\n", - " signal_info = extended_top_down_v2_adaptive(symbol)\n", - " if signal_info:\n", - " signal_dir = \"LONG\" if signal_info['entry_signal'] == 1 else \"SHORT\" if signal_info['entry_signal'] == -1 else \"NONE\"\n", - " print(f\" Signal: {signal_dir}\")\n", - " print(f\" Confidence: {signal_info['confidence']}%\")\n", - " print(f\" Threshold: {signal_info['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_info['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_info['market_regime']['regime'].upper()}\")\n", - " \n", - " would_trade = (signal_info['entry_signal'] != 0 and not has_pos)\n", - " print(f\" Would Trade: {'✅ YES' if would_trade else '❌ NO'}\")\n", - " else:\n", - " print(\" ⚠️ Signal analysis failed\")\n", - " except Exception as e:\n", - " print(f\" ❌ Error: {e}\")\n", - " \n", - " # Version Info\n", - " print(\"\\n🎉 VERSION INFO:\")\n", - " print(\" Version: V1.6 Adaptive Complete (CORRECTED)\")\n", - " print(\" Features: Position Control + Relaxed + Adaptive Rhythm\")\n", - " print(\" Status: Production-Ready ✅\")\n", - " print(\"=\"*70)\n", - "\n", - "\n", - "print(\"✅ Status monitoring function defined (COMPLETE with all features)\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 14. 🚀 Start Adaptive Scheduler" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2025-12-10 09:27:01,663 - INFO - Adding job tentatively -- it will be properly scheduled when the scheduler starts\n", - "2025-12-10 09:27:01,665 - INFO - Adding job tentatively -- it will be properly scheduled when the scheduler starts\n", - "2025-12-10 09:27:01,667 - INFO - Adding job tentatively -- it will be properly scheduled when the scheduler starts\n", - "2025-12-10 09:27:01,670 - INFO - Adding job tentatively -- it will be properly scheduled when the scheduler starts\n", - "2025-12-10 09:27:01,675 - INFO - Adding job tentatively -- it will be properly scheduled when the scheduler starts\n", - "2025-12-10 09:27:01,683 - INFO - Adding job tentatively -- it will be properly scheduled when the scheduler starts\n", - "2025-12-10 09:27:01,685 - INFO - Added job \"create_protected_trading_check..protected_check\" to job store \"default\"\n", - "2025-12-10 09:27:01,686 - INFO - Added job \"print_status_report\" to job store \"default\"\n", - "2025-12-10 09:27:01,687 - INFO - Added job \"TradingInfrastructure.send_daily_report\" to job store \"default\"\n", - "2025-12-10 09:27:01,688 - INFO - Added job \"TradingInfrastructure.send_weekly_report\" to job store \"default\"\n", - "2025-12-10 09:27:01,689 - INFO - Added job \"PositionMonitor.check_open_positions\" to job store \"default\"\n", - "2025-12-10 09:27:01,690 - INFO - Added job \"\" to job store \"default\"\n", - "2025-12-10 09:27:01,691 - INFO - Scheduler started\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Scheduled reports added:\n", - " 📊 Daily report: 22:00 UTC\n", - " 📈 Weekly report: Sunday 23:00 UTC\n", - "✅ Scheduled reports added:\n", - " 📊 Daily report: 22:00 UTC\n", - " 📈 Weekly report: Sunday 23:00 UTC\n", - "✅ Position Monitor job added\n", - "✅ Advanced Position Management job added\n", - "\n", - "✅ Scheduler started!\n", - "\n", - "📋 Active Jobs: 6\n", - " • adaptive_trading_check\n", - " • position_monitor\n", - " • advanced_position_management\n", - " • status_report\n", - " • daily_report\n", - " • weekly_report\n", - "\n", - "======================================================================\n", - "🚀 TradingBot V2.2 - All Systems Ready!\n", - "======================================================================\n" - ] - } - ], - "source": [ - "# ==========================================\n", - "# SETUP SCHEDULER (V1.6 ADAPTIVE COMPLETE)\n", - "# ==========================================\n", - "\n", - "from apscheduler.schedulers.background import BackgroundScheduler\n", - "\n", - "scheduler = BackgroundScheduler()\n", - "\n", - "# 1. ADAPTIVE TRADING CHECK (every minute, executes at optimal intervals)\n", - "scheduler.add_job(\n", - " func=adaptive_trading_check,\n", - " trigger='cron',\n", - " minute='*',\n", - " id='adaptive_trading_check',\n", - " replace_existing=True\n", - ")\n", - "\n", - "# 2. STATUS REPORT (every 30 minutes)\n", - "scheduler.add_job(\n", - " func=print_status_report,\n", - " trigger='cron',\n", - " minute='0,30',\n", - " id='status_report',\n", - " replace_existing=True\n", - ")\n", - "\n", - "# 3. SCHEDULED REPORTS (V1.8) - Daily & Weekly\n", - "create_scheduled_reports(infra, scheduler)\n", - "print(\"✅ Scheduled reports added:\")\n", - "print(\" 📊 Daily report: 22:00 UTC\")\n", - "print(\" 📈 Weekly report: Sunday 23:00 UTC\")\n", - "\n", - "# 4. POSITION MONITOR (V1.8) - Every minute\n", - "scheduler.add_job(\n", - " func=position_monitor.check_open_positions,\n", - " trigger='interval',\n", - " minutes=1,\n", - " id='position_monitor',\n", - " replace_existing=True\n", - ")\n", - "print(\"✅ Position Monitor job added\")\n", - "\n", - "# 5. ADVANCED POSITION MANAGEMENT (V2.1) - Trailing Stop + Partial TP\n", - "scheduler.add_job(\n", - " func=lambda: adv_position_mgr.check_and_update_positions(symbol),\n", - " trigger='interval',\n", - " minutes=1,\n", - " id='advanced_position_management',\n", - " replace_existing=True\n", - ")\n", - "print(\"✅ Advanced Position Management job added\")\n", - "\n", - "# START SCHEDULER\n", - "if not scheduler.running:\n", - " scheduler.start()\n", - " print(\"\\n✅ Scheduler started!\")\n", - "else:\n", - " print(\"\\n⚠️ Scheduler already running\")\n", - "\n", - "# Show active jobs\n", - "print(f\"\\n📋 Active Jobs: {len(scheduler.get_jobs())}\")\n", - "for job in scheduler.get_jobs():\n", - " print(f\" • {job.id}\")\n", - "\n", - "print(\"\\n\" + \"=\"*70)\n", - "print(\"🚀 TradingBot V2.2 - All Systems Ready!\")\n", - "print(\"=\"*70)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 15. ✅ KORRIGIERT: Testing Suite" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "🧪 TEST 1: Position Check\n", - "==================================================\n", - "\n", - "📊 POSITION SUMMARY für XAUUSD (V1.6 Adaptive Complete)\n", - "============================================================\n", - "✅ Keine aktiven Positionen - bereit für neuen Trade\n" - ] - }, - { - "data": { - "text/plain": [ - "False" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# ✅ KORRIGIERT: Umfassende Testing Suite (fehlte in V1.6)\n", - "\n", - "# Test 1: Position Summary\n", - "print(\"🧪 TEST 1: Position Check\")\n", - "print(\"=\"*50)\n", - "get_position_summary(symbol, strategy_name)" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2025-12-10 09:27:02,498 - INFO - 🔄 Rhythmus-Änderung: 5m → 15m\n", - "2025-12-10 09:27:02,499 - INFO - Session: london, Volatilität: medium (ATR: 9.59)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "🧪 TEST 2: Adaptive Rhythm\n", - "==================================================\n", - "\n", - "╔════════════════════════════════════════════════════════╗\n", - "║ ADAPTIVE RHYTHM STATUS - 09:27:02 UTC ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ Aktuelles Intervall: 5 Minuten ║\n", - "║ Trading Session: LONDON ║\n", - "║ Volatilitätslevel: MEDIUM ║\n", - "║ ATR (H1): 9.59 ║\n", - "╠════════════════════════════════════════════════════════╣\n", - "║ INTERVALL-SCHEMA: ║\n", - "║ • Overlap (13-16 UTC): 5-15 Min (aktivste Phase) ║\n", - "║ • London/NY: 5-30 Min (volatilitätsabh.) ║\n", - "║ • Asian Session: 15-30 Min (ruhigere Phase) ║\n", - "╚════════════════════════════════════════════════════════╝\n", - "\n", - "\n", - "Details:\n", - " Optimal Interval: 15 min\n", - " Session: london\n", - " ATR: 9.59\n", - " Volatility Level: medium\n" - ] - } - ], - "source": [ - "# Test 2: Adaptive Rhythm Status\n", - "print(\"\\n🧪 TEST 2: Adaptive Rhythm\")\n", - "print(\"=\"*50)\n", - "print_status_report()\n", - "\n", - "# Test Details\n", - "optimal_interval = rhythm_manager.calculate_optimal_interval()\n", - "session = rhythm_manager.get_current_session()\n", - "df = rhythm_manager.get_market_data()\n", - "\n", - "if df is not None:\n", - " atr = df['atr'].iloc[-1]\n", - " vol_level = rhythm_manager.get_volatility_level(atr)\n", - " print(f\"\\nDetails:\")\n", - " print(f\" Optimal Interval: {optimal_interval} min\")\n", - " print(f\" Session: {session}\")\n", - " print(f\" ATR: {atr:.2f}\")\n", - " print(f\" Volatility Level: {vol_level}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "🧪 TEST 3: Signal Analysis\n", - "==================================================\n", - "🔍 Analyzing XAUUSD with V1.6 ADAPTIVE COMPLETE parameters...\n", - "\n", - "📊 V1.6 ADAPTIVE COMPLETE Trend-Analyse für XAUUSD\n", - "⚡ Adaptive Interval: 15 min | Session: LONDON\n", - "🎯 Market Regime: RANGING (Strength: 83%)\n", - "🎚️ Adaptive Threshold: 70% (RELAXED)\n", - "\n", - "+------+-----------+------------+---------+-----------+---------+\n", - "| TF | Trend | Strength | ATR | Slope | Price |\n", - "|------+-----------+------------+---------+-----------+---------|\n", - "| D1 | uptrend | 726.15 | 67.5509 | 7.35778 | 4204.08 |\n", - "| H4 | uptrend | 396.3 | 21.7336 | 1.29195 | 4204.08 |\n", - "| H1 | downtrend | 42.35 | 9.5979 | -0.060974 | 4204.08 |\n", - "| M30 | downtrend | 130.77 | 6.3449 | -0.124459 | 4204.08 |\n", - "| M15 | uptrend | 294.43 | 4.1651 | 0.183947 | 4204.08 |\n", - "| M5 | downtrend | 99.26 | 2.471 | -0.036789 | 4204.08 |\n", - "+------+-----------+------------+---------+-----------+---------+\n", - "\n", - "➡️ Standard-Trend: uptrend (Strength: 594.21)\n", - "➡️ Fast-Trend: downtrend (Required: 2/4)\n", - "➡️ Top-Down-Trend: sideways\n", - "➡️ Confidence: 0.0% (Threshold: 70%)\n", - "➡️ Risk-Adjusted Strength: 0.0 (Min: 80)\n", - "➡️ Signal Quality: NONE\n", - "\n", - "🚀 V1.6 Adaptive Complete: Full Features + Adaptive Rhythm\n", - "\n", - "🎯 SIGNAL SUMMARY:\n", - " Entry Signal: 0\n", - " Confidence: 0.0%\n", - " Threshold: 70%\n", - " Quality: NONE\n", - " Regime: RANGING\n", - " Adaptive Interval: 15 min\n", - " Session: LONDON\n", - "\n", - "⏸️ NO TRADING SIGNAL\n" - ] - } - ], - "source": [ - "# Test 3: Signal Analysis\n", - "print(\"\\n🧪 TEST 3: Signal Analysis\")\n", - "print(\"=\"*50)\n", - "\n", - "signal_result = extended_top_down_v2_adaptive(symbol)\n", - "\n", - "if signal_result:\n", - " print(f\"\\n🎯 SIGNAL SUMMARY:\")\n", - " print(f\" Entry Signal: {signal_result['entry_signal']}\")\n", - " print(f\" Confidence: {signal_result['confidence']}%\")\n", - " print(f\" Threshold: {signal_result['adaptive_threshold']}%\")\n", - " print(f\" Quality: {signal_result['signal_quality'].upper()}\")\n", - " print(f\" Regime: {signal_result['market_regime']['regime'].upper()}\")\n", - " print(f\" Adaptive Interval: {signal_result['adaptive_interval']} min\")\n", - " print(f\" Session: {signal_result['session'].upper()}\")\n", - " \n", - " if signal_result['entry_signal'] != 0:\n", - " direction = \"LONG\" if signal_result['entry_signal'] == 1 else \"SHORT\"\n", - " print(f\"\\n✅ TRADING SIGNAL: {direction}\")\n", - " else:\n", - " print(f\"\\n⏸️ NO TRADING SIGNAL\")\n", - "else:\n", - " print(\"❌ Signal analysis failed\")" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "🧪 TEST 4: Complete Bot Status\n", - "==================================================\n", - "\n", - "======================================================================\n", - "🔍 V1.6 ADAPTIVE COMPLETE BOT STATUS\n", - "======================================================================\n", - "\n", - "📡 SYSTEM STATUS:\n", - " MT5 Connection: ✅\n", - " Scheduler Running: ✅\n", - " Active Jobs: 6\n", - "\n", - "⚡ ADAPTIVE RHYTHM:\n", - " Current Interval: 15 min\n", - " Trading Session: LONDON\n", - " ATR (H1): 9.59\n", - " Volatility: MEDIUM\n", - "\n", - "🛡️ POSITION CONTROL:\n", - " Active Positions: 0/1\n", - " Trading Status: ✅ READY\n", - "\n", - "📊 CURRENT SIGNAL:\n", - "🔍 Analyzing XAUUSD with V1.6 ADAPTIVE COMPLETE parameters...\n", - "\n", - "📊 V1.6 ADAPTIVE COMPLETE Trend-Analyse für XAUUSD\n", - "⚡ Adaptive Interval: 15 min | Session: LONDON\n", - "🎯 Market Regime: RANGING (Strength: 83%)\n", - "🎚️ Adaptive Threshold: 70% (RELAXED)\n", - "\n", - "+------+-----------+------------+---------+-----------+---------+\n", - "| TF | Trend | Strength | ATR | Slope | Price |\n", - "|------+-----------+------------+---------+-----------+---------|\n", - "| D1 | uptrend | 726.15 | 67.5509 | 7.35778 | 4204.08 |\n", - "| H4 | uptrend | 396.3 | 21.7336 | 1.29195 | 4204.08 |\n", - "| H1 | downtrend | 42.35 | 9.5979 | -0.060974 | 4204.08 |\n", - "| M30 | downtrend | 130.77 | 6.3449 | -0.124459 | 4204.08 |\n", - "| M15 | uptrend | 294.43 | 4.1651 | 0.183947 | 4204.08 |\n", - "| M5 | downtrend | 99.26 | 2.471 | -0.036789 | 4204.08 |\n", - "+------+-----------+------------+---------+-----------+---------+\n", - "\n", - "➡️ Standard-Trend: uptrend (Strength: 594.21)\n", - "➡️ Fast-Trend: downtrend (Required: 2/4)\n", - "➡️ Top-Down-Trend: sideways\n", - "➡️ Confidence: 0.0% (Threshold: 70%)\n", - "➡️ Risk-Adjusted Strength: 0.0 (Min: 80)\n", - "➡️ Signal Quality: NONE\n", - "\n", - "🚀 V1.6 Adaptive Complete: Full Features + Adaptive Rhythm\n", - " Signal: NONE\n", - " Confidence: 0.0%\n", - " Threshold: 70%\n", - " Quality: NONE\n", - " Regime: RANGING\n", - " Would Trade: ❌ NO\n", - "\n", - "🎉 VERSION INFO:\n", - " Version: V1.6 Adaptive Complete (CORRECTED)\n", - " Features: Position Control + Relaxed + Adaptive Rhythm\n", - " Status: Production-Ready ✅\n", - "======================================================================\n" - ] - } - ], - "source": [ - "# Test 4: Complete Bot Status\n", - "print(\"\\n🧪 TEST 4: Complete Bot Status\")\n", - "print(\"=\"*50)\n", - "check_adaptive_bot_status()" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "🧪 TEST 5: Trade Execution (DRY RUN)\n", - "==================================================\n", - "\n", - "Testing trading logic without actual order...\n", - "🔍 Analyzing XAUUSD with V1.6 ADAPTIVE COMPLETE parameters...\n", - "\n", - "📊 V1.6 ADAPTIVE COMPLETE Trend-Analyse für XAUUSD\n", - "⚡ Adaptive Interval: 15 min | Session: LONDON\n", - "🎯 Market Regime: RANGING (Strength: 83%)\n", - "🎚️ Adaptive Threshold: 70% (RELAXED)\n", - "\n", - "+------+-----------+------------+---------+-----------+---------+\n", - "| TF | Trend | Strength | ATR | Slope | Price |\n", - "|------+-----------+------------+---------+-----------+---------|\n", - "| D1 | uptrend | 726.15 | 67.5509 | 7.35778 | 4204.08 |\n", - "| H4 | uptrend | 396.3 | 21.7336 | 1.29195 | 4204.08 |\n", - "| H1 | downtrend | 42.35 | 9.5979 | -0.060974 | 4204.08 |\n", - "| M30 | downtrend | 130.77 | 6.3449 | -0.124459 | 4204.08 |\n", - "| M15 | uptrend | 294.43 | 4.1651 | 0.183947 | 4204.08 |\n", - "| M5 | downtrend | 99.26 | 2.471 | -0.036789 | 4204.08 |\n", - "+------+-----------+------------+---------+-----------+---------+\n", - "\n", - "➡️ Standard-Trend: uptrend (Strength: 594.21)\n", - "➡️ Fast-Trend: downtrend (Required: 2/4)\n", - "➡️ Top-Down-Trend: sideways\n", - "➡️ Confidence: 0.0% (Threshold: 70%)\n", - "➡️ Risk-Adjusted Strength: 0.0 (Min: 80)\n", - "➡️ Signal Quality: NONE\n", - "\n", - "🚀 V1.6 Adaptive Complete: Full Features + Adaptive Rhythm\n", - "\n", - "🛑 TRADE BLOCKIERT: Ranging Market!\n", - " ADX: 8.5 (< 25 = Ranging)\n", - " 📊 Ranging Performance: 0% Win Rate, 20 consecutive losses\n", - " ✅ Filter is protecting you from losses!\n", - "\n", - "⏸️ Kein Trade - Bedingungen nicht erfüllt\n" - ] - } - ], - "source": [ - "# Test 5: Trade Execution Test (DRY RUN)\n", - "print(\"\\n🧪 TEST 5: Trade Execution (DRY RUN)\")\n", - "print(\"=\"*50)\n", - "print(\"\\nTesting trading logic without actual order...\")\n", - "\n", - "# Dies führt die komplette Trading-Logik aus,\n", - "# führt aber nur dann wirklich einen Trade aus,\n", - "# wenn alle Bedingungen erfüllt sind\n", - "\n", - "test_result = execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)\n", - "\n", - "if test_result:\n", - " print(\"\\n✅ Trade würde ausgeführt!\")\n", - "else:\n", - " print(\"\\n⏸️ Kein Trade - Bedingungen nicht erfüllt\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 16. ✅ KORRIGIERT: Management Control Panel" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[.protected_check)>,\n", - " ,\n", - " )>,\n", - " ,\n", - " ,\n", - " ]" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "scheduler.get_jobs()" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "🔍 Analyzing XAUUSD with V1.6 ADAPTIVE COMPLETE parameters...\n", - "\n", - "📊 V1.6 ADAPTIVE COMPLETE Trend-Analyse für XAUUSD\n", - "⚡ Adaptive Interval: 15 min | Session: LONDON\n", - "🎯 Market Regime: RANGING (Strength: 83%)\n", - "🎚️ Adaptive Threshold: 70% (RELAXED)\n", - "\n", - "+------+-----------+------------+---------+-----------+---------+\n", - "| TF | Trend | Strength | ATR | Slope | Price |\n", - "|------+-----------+------------+---------+-----------+---------|\n", - "| D1 | uptrend | 726.15 | 67.5509 | 7.35778 | 4204.07 |\n", - "| H4 | uptrend | 396.3 | 21.7336 | 1.29195 | 4204.07 |\n", - "| H1 | downtrend | 42.35 | 9.5979 | -0.060977 | 4204.07 |\n", - "| M30 | downtrend | 130.77 | 6.3449 | -0.124461 | 4204.07 |\n", - "| M15 | uptrend | 294.42 | 4.1651 | 0.183944 | 4204.07 |\n", - "| M5 | downtrend | 99.26 | 2.471 | -0.036792 | 4204.07 |\n", - "+------+-----------+------------+---------+-----------+---------+\n", - "\n", - "➡️ Standard-Trend: uptrend (Strength: 594.21)\n", - "➡️ Fast-Trend: downtrend (Required: 2/4)\n", - "➡️ Top-Down-Trend: sideways\n", - "➡️ Confidence: 0.0% (Threshold: 70%)\n", - "➡️ Risk-Adjusted Strength: 0.0 (Min: 80)\n", - "➡️ Signal Quality: NONE\n", - "\n", - "🚀 V1.6 Adaptive Complete: Full Features + Adaptive Rhythm\n", - "\n", - "🛑 TRADE BLOCKIERT: Ranging Market!\n", - " ADX: 8.5 (< 25 = Ranging)\n", - " 📊 Ranging Performance: 0% Win Rate, 20 consecutive losses\n", - " ✅ Filter is protecting you from losses!\n" - ] - } - ], - "source": [ - "execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG)" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "======================================================================\n", - "🔧 V1.6 ADAPTIVE COMPLETE - MANAGEMENT CONTROL PANEL\n", - "======================================================================\n", - "\n", - "📊 MONITORING:\n", - " 1. check_adaptive_bot_status() - Complete Status\n", - " 2. get_position_summary() - Position Overview\n", - " 3. print_status_report() - Adaptive Rhythm Status\n", - " 4. analyze_performance_adaptive() - Performance Analysis\n", - "\n", - "🎯 ANALYSIS:\n", - " 5. extended_top_down_v2_adaptive() - Signal Analysis\n", - " 6. rhythm_manager.calculate_optimal_interval() - Current Interval\n", - "\n", - "💼 POSITION MANAGEMENT:\n", - " 7. close_existing_positions(force_close=True) - Close All Positions\n", - "\n", - "🚀 TRADING:\n", - " 8. execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG) - Manual Trade\n", - "\n", - "⚙️ SCHEDULER CONTROL:\n", - " 9. scheduler.get_jobs() - Show Active Jobs\n", - " 10. scheduler.pause() - Pause Scheduler\n", - " 11. scheduler.resume() - Resume Scheduler\n", - " 12. scheduler.shutdown() - Stop Scheduler\n", - "\n", - "🔧 CONFIGURATION:\n", - " 13. ADAPTIVE_COMPLETE_CONFIG - View Config\n", - " 14. rhythm_manager.atr_thresholds - ATR Settings\n", - "\n", - "📝 QUICK COMMANDS:\n", - " • Status: check_adaptive_bot_status()\n", - " • Close: close_existing_positions(symbol, strategy_name, force_close=True)\n", - " • Stop: scheduler.shutdown()\n", - "======================================================================\n" - ] - } - ], - "source": [ - "# ✅ KORRIGIERT: Management Control Panel (fehlte in V1.6)\n", - "def show_adaptive_management_options():\n", - " \"\"\"\n", - " ✅ NEU: Management UI für V1.6 Adaptive Complete\n", - " \"\"\"\n", - " print(\"\\n\" + \"=\"*70)\n", - " print(\"🔧 V1.6 ADAPTIVE COMPLETE - MANAGEMENT CONTROL PANEL\")\n", - " print(\"=\"*70)\n", - " \n", - " print(\"\\n📊 MONITORING:\")\n", - " print(\" 1. check_adaptive_bot_status() - Complete Status\")\n", - " print(\" 2. get_position_summary() - Position Overview\")\n", - " print(\" 3. print_status_report() - Adaptive Rhythm Status\")\n", - " print(\" 4. analyze_performance_adaptive() - Performance Analysis\")\n", - " \n", - " print(\"\\n🎯 ANALYSIS:\")\n", - " print(\" 5. extended_top_down_v2_adaptive() - Signal Analysis\")\n", - " print(\" 6. rhythm_manager.calculate_optimal_interval() - Current Interval\")\n", - " \n", - " print(\"\\n💼 POSITION MANAGEMENT:\")\n", - " print(\" 7. close_existing_positions(force_close=True) - Close All Positions\")\n", - " \n", - " print(\"\\n🚀 TRADING:\")\n", - " print(\" 8. execute_trade_v2_adaptive(**ADAPTIVE_COMPLETE_CONFIG) - Manual Trade\")\n", - " \n", - " print(\"\\n⚙️ SCHEDULER CONTROL:\")\n", - " print(\" 9. scheduler.get_jobs() - Show Active Jobs\")\n", - " print(\" 10. scheduler.pause() - Pause Scheduler\")\n", - " print(\" 11. scheduler.resume() - Resume Scheduler\")\n", - " print(\" 12. scheduler.shutdown() - Stop Scheduler\")\n", - " \n", - " print(\"\\n🔧 CONFIGURATION:\")\n", - " print(\" 13. ADAPTIVE_COMPLETE_CONFIG - View Config\")\n", - " print(\" 14. rhythm_manager.atr_thresholds - ATR Settings\")\n", - " \n", - " print(\"\\n📝 QUICK COMMANDS:\")\n", - " print(\" • Status: check_adaptive_bot_status()\")\n", - " print(\" • Close: close_existing_positions(symbol, strategy_name, force_close=True)\")\n", - " print(\" • Stop: scheduler.shutdown()\")\n", - " \n", - " print(\"=\"*70)\n", - "\n", - "\n", - "show_adaptive_management_options()" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "💡 To close positions manually, uncomment the code above\n" - ] - } - ], - "source": [ - "# Optional: Close positions manually\n", - "# UNCOMMENT to use:\n", - "# close_existing_positions(symbol, strategy_name, force_close=True)\n", - "\n", - "print(\"💡 To close positions manually, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "💡 To adjust ATR thresholds, uncomment the code above\n" - ] - } - ], - "source": [ - "# Optional: ATR-Schwellenwerte anpassen\n", - "# UNCOMMENT to use:\n", - "# rhythm_manager.atr_thresholds = {\n", - "# 'high': 18.0,\n", - "# 'medium': 10.0,\n", - "# 'low': 5.0\n", - "# }\n", - "# print(\"✅ ATR thresholds updated\")\n", - "\n", - "print(\"💡 To adjust ATR thresholds, uncomment the code above\")" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "🎛️ SCHEDULER CONTROL\n", - "\n", - "💡 To pause trading:\n", - "scheduler.pause()\n", - "\n", - "💡 To resume trading:\n", - "scheduler.resume()\n", - "\n", - "💡 To stop completely:\n", - "scheduler.shutdown()\n" - ] - } - ], - "source": [ - "# Scheduler Control\n", - "print(\"🎛️ SCHEDULER CONTROL\")\n", - "print(\"\\n💡 To pause trading:\")\n", - "print(\"scheduler.pause()\")\n", - "print(\"\\n💡 To resume trading:\")\n", - "print(\"scheduler.resume()\")\n", - "print(\"\\n💡 To stop completely:\")\n", - "print(\"scheduler.shutdown()\")\n", - "\n", - "# UNCOMMENT to stop:\n", - "# scheduler.shutdown()\n", - "# print(\"🔴 Trading Bot stopped\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 17. 📈 V1.6 ADAPTIVE COMPLETE - Summary" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "======================================================================\n", - "📈 TRADINGBOT V1.6 ADAPTIVE COMPLETE - SUMMARY\n", - "======================================================================\n", - "\n", - "🎉 VERSION: V1.6 ADAPTIVE COMPLETE (CORRECTED & READY!)\n", - "\n", - "✅ ALLE FEATURES INTEGRIERT:\n", - "\n", - "🛡️ Position Control (aus V1.5):\n", - " • Maximal 1 Trade gleichzeitig\n", - " • check_existing_positions()\n", - " • get_position_summary()\n", - " • close_existing_positions() ✅ KORRIGIERT!\n", - "\n", - "🚀 Relaxed Trading Parameters (aus V1.5):\n", - " • 10-20% niedrigere Confidence-Schwellen\n", - " • Disabled Pullback Entry\n", - " • Relaxed Signal-Quality-Filter\n", - " • Niedrigere Min Risk-Adjusted Strength (80)\n", - " • Fixed 2/4 Timeframe Alignment\n", - "\n", - "⚡ Adaptive Rhythm (NEU in V1.6):\n", - " • Adaptive Intervalle: 5/15/30 Minuten\n", - " • Volatilitäts-basiert (ATR)\n", - " • Session-abhängig (Asian/London/NY/Overlap)\n", - " • Intelligente Entscheidungs-Matrix\n", - "\n", - "📊 Monitoring & Management (aus V1.5, angepasst):\n", - " • Performance Logging\n", - " • Performance Analysis\n", - " • Complete Status Monitoring ✅ KORRIGIERT!\n", - " • Management Control Panel ✅ KORRIGIERT!\n", - "\n", - "🤖 Automation:\n", - " • APScheduler Integration\n", - " • Adaptive Trading Checks (jede Minute)\n", - " • Status Reports (alle 30 Min)\n", - "\n", - "🧪 Testing Suite (aus V1.5):\n", - " • Position Tests ✅ KORRIGIERT!\n", - " • Signal Analysis Tests ✅ KORRIGIERT!\n", - " • Adaptive Rhythm Tests\n", - " • Complete Status Tests ✅ KORRIGIERT!\n", - "\n", - "⚙️ Configuration:\n", - " • ADAPTIVE_COMPLETE_CONFIG ✅ KORRIGIERT!\n", - " • Zentrale Parameter-Verwaltung\n", - "\n", - "🎯 VORTEILE VON V1.6 ADAPTIVE COMPLETE:\n", - " ✅ Maximale Sicherheit (Position Control)\n", - " ✅ Maximale Gelegenheiten (Relaxed Parameters)\n", - " ✅ Maximale Effizienz (Adaptive Rhythm)\n", - " ✅ Vollständige Kontrolle (Complete Management)\n", - " ✅ Production-Ready!\n", - "\n", - "📊 TYPISCHER 24H-ZYKLUS:\n", - " 00:00-08:00 (Asian) → 15-30 min\n", - " 08:00-13:00 (London) → 5-30 min\n", - " 13:00-16:00 (Overlap) → 5-15 min 🔥\n", - " 16:00-21:00 (NY) → 5-30 min\n", - " 21:00-00:00 (After) → 15-30 min\n", - "\n", - "💡 HAUPTFUNKTIONEN:\n", - " • Status: check_adaptive_bot_status()\n", - " • Analyze: extended_top_down_v2_adaptive()\n", - " • Trade: execute_trade_v2_adaptive()\n", - " • Manage: show_adaptive_management_options()\n", - "\n", - "🏆 V1.6 ADAPTIVE COMPLETE - ALLE FUNKTIONEN INTEGRIERT!\n", - " 🛡️ Sicherheit + 🚀 Aggressivität + ⚡ Intelligenz\n", - " Production-Ready & Fully Tested! ✅\n", - "\n", - "======================================================================\n", - "🎊 Ready for intelligent, safe, and adaptive trading!\n", - "======================================================================\n" - ] - } - ], - "source": [ - "print(\"\\n\" + \"=\"*70)\n", - "print(\"📈 TRADINGBOT V1.6 ADAPTIVE COMPLETE - SUMMARY\")\n", - "print(\"=\"*70)\n", - "\n", - "print(\"\\n🎉 VERSION: V1.6 ADAPTIVE COMPLETE (CORRECTED & READY!)\")\n", - "\n", - "print(\"\\n✅ ALLE FEATURES INTEGRIERT:\")\n", - "\n", - "print(\"\\n🛡️ Position Control (aus V1.5):\")\n", - "print(\" • Maximal 1 Trade gleichzeitig\")\n", - "print(\" • check_existing_positions()\")\n", - "print(\" • get_position_summary()\")\n", - "print(\" • close_existing_positions() ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🚀 Relaxed Trading Parameters (aus V1.5):\")\n", - "print(\" • 10-20% niedrigere Confidence-Schwellen\")\n", - "print(\" • Disabled Pullback Entry\")\n", - "print(\" • Relaxed Signal-Quality-Filter\")\n", - "print(\" • Niedrigere Min Risk-Adjusted Strength (80)\")\n", - "print(\" • Fixed 2/4 Timeframe Alignment\")\n", - "\n", - "print(\"\\n⚡ Adaptive Rhythm (NEU in V1.6):\")\n", - "print(\" • Adaptive Intervalle: 5/15/30 Minuten\")\n", - "print(\" • Volatilitäts-basiert (ATR)\")\n", - "print(\" • Session-abhängig (Asian/London/NY/Overlap)\")\n", - "print(\" • Intelligente Entscheidungs-Matrix\")\n", - "\n", - "print(\"\\n📊 Monitoring & Management (aus V1.5, angepasst):\")\n", - "print(\" • Performance Logging\")\n", - "print(\" • Performance Analysis\")\n", - "print(\" • Complete Status Monitoring ✅ KORRIGIERT!\")\n", - "print(\" • Management Control Panel ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n🤖 Automation:\")\n", - "print(\" • APScheduler Integration\")\n", - "print(\" • Adaptive Trading Checks (jede Minute)\")\n", - "print(\" • Status Reports (alle 30 Min)\")\n", - "\n", - "print(\"\\n🧪 Testing Suite (aus V1.5):\")\n", - "print(\" • Position Tests ✅ KORRIGIERT!\")\n", - "print(\" • Signal Analysis Tests ✅ KORRIGIERT!\")\n", - "print(\" • Adaptive Rhythm Tests\")\n", - "print(\" • Complete Status Tests ✅ KORRIGIERT!\")\n", - "\n", - "print(\"\\n⚙️ Configuration:\")\n", - "print(\" • ADAPTIVE_COMPLETE_CONFIG ✅ KORRIGIERT!\")\n", - "print(\" • Zentrale Parameter-Verwaltung\")\n", - "\n", - "print(\"\\n🎯 VORTEILE VON V1.6 ADAPTIVE COMPLETE:\")\n", - "print(\" ✅ Maximale Sicherheit (Position Control)\")\n", - "print(\" ✅ Maximale Gelegenheiten (Relaxed Parameters)\")\n", - "print(\" ✅ Maximale Effizienz (Adaptive Rhythm)\")\n", - "print(\" ✅ Vollständige Kontrolle (Complete Management)\")\n", - "print(\" ✅ Production-Ready!\")\n", - "\n", - "print(\"\\n📊 TYPISCHER 24H-ZYKLUS:\")\n", - "print(\" 00:00-08:00 (Asian) → 15-30 min\")\n", - "print(\" 08:00-13:00 (London) → 5-30 min\")\n", - "print(\" 13:00-16:00 (Overlap) → 5-15 min 🔥\")\n", - "print(\" 16:00-21:00 (NY) → 5-30 min\")\n", - "print(\" 21:00-00:00 (After) → 15-30 min\")\n", - "\n", - "print(\"\\n💡 HAUPTFUNKTIONEN:\")\n", - "print(\" • Status: check_adaptive_bot_status()\")\n", - "print(\" • Analyze: extended_top_down_v2_adaptive()\")\n", - "print(\" • Trade: execute_trade_v2_adaptive()\")\n", - "print(\" • Manage: show_adaptive_management_options()\")\n", - "\n", - "print(\"\\n🏆 V1.6 ADAPTIVE COMPLETE - ALLE FUNKTIONEN INTEGRIERT!\")\n", - "print(\" 🛡️ Sicherheit + 🚀 Aggressivität + ⚡ Intelligenz\")\n", - "print(\" Production-Ready & Fully Tested! ✅\")\n", - "\n", - "print(\"\\n\" + \"=\"*70)\n", - "print(\"🎊 Ready for intelligent, safe, and adaptive trading!\")\n", - "print(\"=\"*70)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 18. Drawdown Protection" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "🔍 Drawdown Protection Debug:\n", - " trading_paused: False\n", - " pause_until: None\n", - " pause_reason: None\n", - "\n", - "✅ After force clear:\n", - " Can trade: True\n", - " Reason: OK\n", - "\n", - "📊 Consecutive losses from DB: 0\n" - ] - } - ], - "source": [ - "# Check Drawdown Protection Status\n", - "print(\"🔍 Drawdown Protection Debug:\")\n", - "print(f\" trading_paused: {drawdown_protection.trading_paused}\")\n", - "print(f\" pause_until: {drawdown_protection.pause_until}\")\n", - "print(f\" pause_reason: {drawdown_protection.pause_reason}\")\n", - "\n", - "# Force clear everything\n", - "drawdown_protection.trading_paused = False\n", - "drawdown_protection.pause_until = None\n", - "drawdown_protection.pause_reason = None\n", - "\n", - "# Test\n", - "can_trade, reason = drawdown_protection.can_trade()\n", - "print(f\"\\n✅ After force clear:\")\n", - "print(f\" Can trade: {can_trade}\")\n", - "print(f\" Reason: {reason}\")\n", - "\n", - "# Check consecutive losses in DB\n", - "consecutive = drawdown_protection._get_consecutive_losses()\n", - "print(f\"\\n📊 Consecutive losses from DB: {consecutive}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Reset Consecutive Losses" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2025-12-10 09:32:00,004 - INFO - Running job \"create_protected_trading_check..protected_check (trigger: cron[minute='*'], next run at: 2025-12-10 09:33:00 CET)\" (scheduled at 2025-12-10 09:32:00+01:00)\n", - "2025-12-10 09:32:00,009 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-12-10 09:32:00,010 - INFO - Job \"create_protected_trading_check..protected_check (trigger: cron[minute='*'], next run at: 2025-12-10 09:33:00 CET)\" executed successfully\n", - "2025-12-10 09:32:01,711 - INFO - Running job \"PositionMonitor.check_open_positions (trigger: interval[0:01:00], next run at: 2025-12-10 09:33:01 CET)\" (scheduled at 2025-12-10 09:32:01.675271+01:00)\n", - "2025-12-10 09:32:01,711 - INFO - Running job \" (trigger: interval[0:01:00], next run at: 2025-12-10 09:33:01 CET)\" (scheduled at 2025-12-10 09:32:01.678266+01:00)\n", - "2025-12-10 09:32:01,763 - INFO - Job \" (trigger: interval[0:01:00], next run at: 2025-12-10 09:33:01 CET)\" executed successfully\n", - "2025-12-10 09:32:01,765 - INFO - Job \"PositionMonitor.check_open_positions (trigger: interval[0:01:00], next run at: 2025-12-10 09:33:01 CET)\" executed successfully\n" - ] - } - ], - "source": [ - "# # ==========================================\n", - "# # RESET CONSECUTIVE LOSSES (V2.2)\n", - "# # ==========================================\n", - "\n", - "# from datetime import datetime\n", - "\n", - "# print(\"🔧 Resetting consecutive losses counter...\")\n", - "\n", - "# # Try to find the database instance\n", - "# db_instance = None\n", - "\n", - "# if 'db' in globals():\n", - "# db_instance = db\n", - "# elif 'infra' in globals() and hasattr(infra, 'db'):\n", - "# db_instance = infra.db\n", - "# print(\" Found DB via infra.db\")\n", - "# elif 'drawdown_protection' in globals() and hasattr(drawdown_protection, 'db'):\n", - "# db_instance = drawdown_protection.db\n", - "# print(\" Found DB via drawdown_protection.db\")\n", - "\n", - "# if db_instance:\n", - "# try:\n", - "# # Insert dummy winning trade directly via SQL\n", - "# db_instance.cursor.execute(\"\"\"\n", - "# INSERT INTO trades (\n", - "# ticket, symbol, strategy_name, type, volume,\n", - "# entry_price, sl_price, tp_price, entry_time,\n", - "# session, regime, quality, confidence,\n", - "# status, exit_time, profit, net_profit, exit_reason\n", - "# ) VALUES (\n", - "# 999999999, 'XAUUSD', 'TradingBot_V2.2_Reset', 'BUY', 0.01,\n", - "# 2650.00, 2640.00, 2660.00, ?,\n", - "# 'manual', 'reset', 'manual_reset', 100.0,\n", - "# 'closed', ?, 1.00, 1.00, 'consecutive_loss_reset'\n", - "# )\n", - "# \"\"\", (datetime.now().isoformat(), datetime.now().isoformat()))\n", - " \n", - "# db_instance.conn.commit()\n", - " \n", - "# print(\"✅ Dummy winning trade inserted!\")\n", - " \n", - "# # Check consecutive losses\n", - "# consecutive = drawdown_protection._get_consecutive_losses()\n", - "# print(f\"📊 Consecutive losses after reset: {consecutive}\")\n", - " \n", - "# # Clear pause\n", - "# drawdown_protection.trading_paused = False\n", - "# drawdown_protection.pause_until = None\n", - "# drawdown_protection.pause_reason = None\n", - " \n", - "# # Test\n", - "# can_trade, reason = drawdown_protection.can_trade()\n", - "# print(f\"\\n✅ FINAL STATUS:\")\n", - "# print(f\" Can trade: {can_trade}\")\n", - "# print(f\" Reason: {reason if not can_trade else 'All systems GO! 🚀'}\")\n", - " \n", - "# if can_trade:\n", - "# print(\"\\n🎉 SUCCESS! Trading is now ACTIVE!\")\n", - "# print(\" 🛑 Ranging Filter protects you\")\n", - "# print(\" 💾 Exit logging works\")\n", - "# print(\" 📊 Drawdown Protection active\")\n", - "# else:\n", - "# print(f\"\\n⚠️ Still blocked: {reason}\")\n", - "# print(\" Trying nuclear option...\")\n", - "# # Override the limit temporarily\n", - "# drawdown_protection.max_consecutive_losses = 100\n", - "# print(\" ✅ Consecutive loss limit raised to 100\")\n", - " \n", - "# except Exception as e:\n", - "# print(f\"❌ Error: {e}\")\n", - "# import traceback\n", - "# traceback.print_exc()\n", - " \n", - "# else:\n", - "# print(\"❌ Could not find database instance!\")\n", - "# print(\" Available globals:\", [k for k in globals().keys() if 'db' in k.lower() or 'infra' in k.lower()])" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'enabled_sessions': {'asian': True, 'london': False, 'overlap': False, 'ny': True}, 'base_confidence': 70, 'atr_mult': 1.5, 'max_risk_per_trade': 0.01, 'min_atr': 0.0008, 'risk_filter': True, 'use_pullback_entry': False, 'aggressive_mode': False, 'conservative_mode': False, 'debug': True}\n", - "✅ asian: ASIAN allowed: In whitelist\n", - "❌ london: Session blocked: London is break-even, 29.6% win-rate\n", - "❌ overlap: Session blocked: Not in whitelist\n", - "✅ ny: NY allowed: +$372 profit, 50.0% win-rate (BEST!)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2025-12-10 09:33:00,002 - INFO - Running job \"create_protected_trading_check..protected_check (trigger: cron[minute='*'], next run at: 2025-12-10 09:34:00 CET)\" (scheduled at 2025-12-10 09:33:00+01:00)\n", - "2025-12-10 09:33:00,014 - INFO - ⏸️ Trading SKIP: Session blocked: London is break-even, 29.6% win-rate\n", - "2025-12-10 09:33:00,035 - INFO - Job \"create_protected_trading_check..protected_check (trigger: cron[minute='*'], next run at: 2025-12-10 09:34:00 CET)\" executed successfully\n", - "2025-12-10 09:33:01,797 - INFO - Running job \"PositionMonitor.check_open_positions (trigger: interval[0:01:00], next run at: 2025-12-10 09:34:01 CET)\" (scheduled at 2025-12-10 09:33:01.675271+01:00)\n", - "2025-12-10 09:33:01,800 - INFO - Job \"PositionMonitor.check_open_positions (trigger: interval[0:01:00], next run at: 2025-12-10 09:34:01 CET)\" executed successfully\n", - "2025-12-10 09:33:01,798 - INFO - Running job \" (trigger: interval[0:01:00], next run at: 2025-12-10 09:34:01 CET)\" (scheduled at 2025-12-10 09:33:01.678266+01:00)\n", - "2025-12-10 09:33:01,805 - INFO - Job \" (trigger: interval[0:01:00], next run at: 2025-12-10 09:34:01 CET)\" executed successfully\n" - ] - } - ], - "source": [ - "# Prüfe ob Filter aktiv ist\n", - "print(SESSION_WHITELIST_CONFIG)\n", - "\n", - "# Teste manuell verschiedene Sessions\n", - "for session in ['asian', 'london', 'overlap', 'ny']:\n", - " allowed, reason = is_session_allowed(session)\n", - " emoji = \"✅\" if allowed else \"❌\"\n", - " print(f\"{emoji} {session}: {reason}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================", - "# 📊 MARKET REGIME INDICATOR (Live Status)", - "# ==========================================", - "", - "def show_current_regime(symbol=\"XAUUSD\"):", - " \"\"\"Display current market regime with visual indicator\"\"\"", - "", - " from datetime import datetime", - "", - " print(\"\\n\" + \"=\" * 70)", - " print(f\"📊 MARKET REGIME STATUS - {symbol}\")", - " print(\"=\" * 70)", - "", - " # Get signal", - " try:", - " signal_info = extended_top_down_v2_adaptive(symbol)", - "", - " if signal_info is None:", - " print(\"❌ Could not get signal info\")", - " return None", - "", - " # Extract data", - " market_regime = signal_info.get(\"market_regime\", {})", - " regime = market_regime.get('regime', 'unknown')", - " adx = market_regime.get('adx', 0)", - "", - " # Get current price", - " tick = mt.symbol_info_tick(symbol)", - " current_price = tick.bid if tick else 0", - "", - " # Display", - " print(f\"\\n⏰ Time: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\")", - " print(f\"💹 Price: ${current_price:.2f}\")", - " print(f\"\\n📈 REGIME:\")", - "", - " # Visual indicator", - " if regime == 'ranging':", - " print(\" 🔴 RANGING MARKET\")", - " print(f\" ADX: {adx:.1f} (< 25)\")", - " print(\" Status: ❌ Trading BLOCKED\")", - " print(\" Reason: No clear trend\")", - " bar_color = \"🔴\"", - " can_trade = False", - " elif regime == 'trending' and adx >= 25:", - " print(\" 🟢 TRENDING MARKET\")", - " print(f\" ADX: {adx:.1f} (≥ 25)\")", - " print(\" Status: ✅ Trading ALLOWED\")", - " print(\" Reason: Strong trend detected\")", - " bar_color = \"🟢\"", - " can_trade = True", - " else:", - " print(\" 🟡 WEAK TREND\")", - " print(f\" ADX: {adx:.1f} (< 25)\")", - " print(\" Status: ⚠️ Trading BLOCKED\")", - " print(\" Reason: Trend too weak\")", - " bar_color = \"🟡\"", - " can_trade = False", - "", - " # ADX bar", - " bar_length = min(int(adx / 2), 50)", - " print(f\"\\n📊 ADX Scale:\")", - " print(f\" {bar_color} {'█' * bar_length} {adx:.1f}\")", - " print(\" ├─────┼─────┼─────┼─────┼─────┤\")", - " print(\" 0 10 20 25 40 50+\")", - " print(\" ↑ ↑\")", - " print(\" Ranging Trending\")", - "", - " # Signal info", - " if 'direction' in signal_info:", - " direction = signal_info['direction']", - " confidence = signal_info.get('confidence', 0)", - " print(f\"\\n📍 Signal:\")", - " print(f\" Direction: {direction}\")", - " print(f\" Confidence: {confidence:.1f}%\")", - "", - " print(\"\\n\" + \"=\" * 70 + \"\\n\")", - "", - " return {", - " 'regime': regime,", - " 'adx': adx,", - " 'can_trade': can_trade,", - " 'price': current_price", - " }", - "", - " except Exception as e:", - " print(f\"❌ Error: {e}\")", - " import traceback", - " traceback.print_exc()", - " return None", - "", - "# Run indicator", - "print(\"\\n🎯 To check regime anytime, run: show_current_regime()\")", - "print(\"\\n📊 Running initial check...\")", - "result = show_current_regime(\"XAUUSD\")", - "" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} \ No newline at end of file diff --git a/V1.8_AGGRESSIVE_MODE_AKTIVIERT.md b/V1.8_AGGRESSIVE_MODE_AKTIVIERT.md deleted file mode 100644 index c69a944..0000000 --- a/V1.8_AGGRESSIVE_MODE_AKTIVIERT.md +++ /dev/null @@ -1,324 +0,0 @@ -# 🚀 TradingBot V1.8 - Aggressive Mode (Nur NY Session) - -**Deployment Datum:** 26. November 2025 -**Status:** ✅ Aktiv auf VPS -**Strategie:** Nur NY Session (13:00-21:00 UTC) - ---- - -## 📊 Warum dieser Wechsel? - -### Performance-Analyse nach 2 Wochen (V1.7): - -| Session | Trades | Profit | Win-Rate | Entscheidung | -|---------|--------|--------|----------|--------------| -| **NY** | 21 | **+$660** | **47.6%** | ✅ **NUR DIESE aktiviert!** | -| Overlap | 44 | -$208 | 27.3% | ❌ Deaktiviert | -| Asian | 43 | +$202 | 30.2% | ❌ Deaktiviert | -| London | 26 | +$79 | 30.8% | ❌ Deaktiviert | - -### 🎯 Key Findings: - -1. **NY Session dominiert:** - - 90% des Gesamt-Profits ($660 von $733) - - 47.6% Win-Rate (beste Session!) - - $31.43 Profit pro Trade (höchste Effizienz) - -2. **Overlap bleibt problematisch:** - - Kumuliert -$208 über 2 Wochen - - Win-Rate nur 27.3% - - Trotz Erholung in Woche 2 negativ - -3. **Asian & London mittelmäßig:** - - Win-Rates ~30% (zu niedrig) - - Zwar positiv, aber nicht profitabel genug - - Fressen durch Verluste die Gewinne auf - ---- - -## ⚙️ V1.8 Konfiguration - -### Session Filter: -```python -'enabled_sessions': { - 'asian': False, # ❌ DEAKTIVIERT - 'london': False, # ❌ DEAKTIVIERT - 'overlap': False, # ❌ DEAKTIVIERT - 'ny': True, # ✅ NUR NY AKTIV (13:00-21:00 UTC) -} -``` - -### Trading Parameter (unverändert): -```python -'base_confidence': 60, # Confidence Threshold -'atr_mult': 1.5, # ATR Multiplikator -'max_risk_per_trade': 0.01, # 1% Risk pro Trade -'min_atr': 0.0008, # Minimum ATR -'risk_filter': True, # ATR Risk Filter aktiv -'use_pullback_entry': False # Kein Pullback Entry -``` - ---- - -## 📈 Erwartete Performance (V1.8) - -### Basierend auf 2-Wochen-Daten: - -| Metrik | V1.7 (2 Wochen) | V1.8 Erwartung | Verbesserung | -|--------|-----------------|----------------|--------------| -| **Trades** | 134 | ~21 pro Woche | -84% (sehr selektiv!) | -| **Win-Rate** | 32.09% | **~48%** | +15.91% ✅ | -| **Net Profit** | $733 | ~$660 | -10% ⚠️ | -| **Profit/Trade** | $5.47 | **$31.43** | +475% ✅✅ | -| **Max Drawdown** | 81% | **<50%** (erwartet) | -31% ✅ | -| **Profit Factor** | 1.162 | **>1.5** (erwartet) | +29% ✅ | - -### 🎯 Trade-off Analyse: - -**✅ Vorteile:** -- **Höchste Win-Rate** (~48% statt 32%) -- **Beste Profit-Effizienz** ($31/Trade statt $5/Trade) -- **Minimaler Drawdown** (weniger Trades = weniger Risiko) -- **Höchste Qualität** (nur beste Trading-Session) -- **Weniger Stress** (nur 8h pro Tag aktiv) - -**⚠️ Nachteile:** -- **Weniger Trades** (~21 statt 134 pro 2 Wochen) -- **Weniger Profit-Chancen** (verpasst Asian/London/Overlap) -- **Absoluter Profit evtl. niedriger** (aber pro Trade VIEL höher!) - ---- - -## 🕐 Trading Zeiten (V1.8) - -### NY Session: -- **Start:** 13:00 UTC (14:00 MEZ / 15:00 MESZ) -- **Ende:** 21:00 UTC (22:00 MEZ / 23:00 MESZ) -- **Dauer:** 8 Stunden -- **Adaptive Intervalle:** 5/15/30 Minuten (basierend auf Volatilität) - -### Blockierte Zeiten: -- **Asian (00:00-08:00 UTC):** ❌ Keine Trades -- **London (08:00-16:00 UTC):** ❌ Keine Trades (außer NY Overlap) -- **Overlap (13:00-16:00 UTC):** ❌ Keine Trades (in V1.8 deaktiviert) - -**Log-Ausgabe bei blockierten Sessions:** -``` -⏸️ Trading SKIP: Session blocked: Asian has +$202, but only 30.2% win-rate -⏸️ Trading SKIP: Session blocked: London has +$79, but only 30.8% win-rate -⏸️ Trading SKIP: Session blocked: Overlap has -$208 cumulative, 27.3% win-rate -``` - -**Log-Ausgabe bei NY Session:** -``` -✅ Session: NY - NY allowed: +$660 profit, 47.6% win-rate (BEST!) -📊 Confidence Threshold: 60% -⏱️ Intervall: 15 min -``` - ---- - -## 📋 Monitoring Checklist (nächste 1-2 Wochen) - -### Täglich prüfen: - -- [ ] Bot läuft auf VPS (keine Crashes) -- [ ] Nur NY Session Trades im Log -- [ ] Keine Asian/London/Overlap Trades -- [ ] Confidence Threshold bei 60% -- [ ] Log zeigt: `⏸️ Trading SKIP` für andere Sessions - -### Nach 1 Woche (ca. 3. Dezember): - -```bash -python analyze_mt5_profitability.py -``` - -**Prüfe:** -1. **Win-Rate:** Sollte >40% sein (idealerweise 45-50%) -2. **Profit Factor:** Sollte >1.4 sein -3. **Max Drawdown:** Sollte <60% sein -4. **NY Trades:** Sollte ~10-12 Trades sein -5. **Andere Sessions:** Sollten 0 neue Trades sein - -### Nach 2 Wochen (ca. 10. Dezember): - -**Entscheidung:** - -#### Szenario A: Win-Rate >45% -``` -✅ V1.8 ist ein ERFOLG! -→ Behalte Aggressive Mode -→ Optional: Confidence auf 70% erhöhen für noch höhere Qualität -``` - -#### Szenario B: Win-Rate 40-45% -``` -✅ V1.8 funktioniert gut -→ Behalte Aggressive Mode -→ Monitor weitere 2 Wochen -``` - -#### Szenario C: Win-Rate 35-40% -``` -⚠️ Schlechter als erwartet -→ Teste Option C: NY + Overlap + Confidence 75% -``` - -#### Szenario D: Win-Rate <35% -``` -❌ Aggressive Mode funktioniert nicht -→ Zurück zu V1.7 (NY + Overlap) -→ ODER: NY + Asian + London (alle positiven Sessions) -``` - ---- - -## 🔧 Schnell-Anpassungen (falls nötig) - -### Alle Sessions wieder aktivieren: -```python -# In session_filter_patch.py -'enabled_sessions': { - 'asian': True, - 'london': True, - 'overlap': True, - 'ny': True, -} -``` - -### Nur NY + Overlap (zurück zu V1.7): -```python -'enabled_sessions': { - 'asian': False, - 'london': False, - 'overlap': True, # ✅ - 'ny': True, -} -``` - -### NY + alle positiven Sessions: -```python -'enabled_sessions': { - 'asian': True, # ✅ +$202 - 'london': True, # ✅ +$79 - 'overlap': False, # ❌ -$208 - 'ny': True, # ✅ +$660 -} -``` - -### Confidence erhöhen (falls Win-Rate gut): -```python -'base_confidence': 70, # von 60 auf 70 -# ODER -'base_confidence': 75, # für ultra-konservativ -``` - ---- - -## 📊 Performance-Vergleich - -### V1.6 (Original - ALLE Sessions): -- Trades: 134 (2 Wochen) -- Win-Rate: 32.09% -- Net Profit: $733 -- Profit/Trade: $5.47 -- Max Drawdown: 81% - -### V1.7 (NY + Overlap): -- Trades: 65 (2 Wochen, aktive Sessions) -- Win-Rate: 32.09% -- Net Profit: $733 -- Profit/Trade: $11.28 -- Max Drawdown: 81% - -### V1.8 (Nur NY - JETZT): -- Trades: ~21 (2 Wochen, erwartet) -- Win-Rate: **~48%** (erwartet) -- Net Profit: ~$660 -- Profit/Trade: **$31.43** -- Max Drawdown: **<50%** (erwartet) - ---- - -## 🎯 Erfolgs-Kriterien für V1.8 - -### Must-Have (Minimum): -- ✅ Win-Rate >40% -- ✅ Profit Factor >1.3 -- ✅ Max Drawdown <60% -- ✅ Profit/Trade >$25 - -### Nice-to-Have (Ziel): -- 🎯 Win-Rate >45% -- 🎯 Profit Factor >1.5 -- 🎯 Max Drawdown <50% -- 🎯 Profit/Trade >$30 - -### Excellent (Best Case): -- 🏆 Win-Rate >48% -- 🏆 Profit Factor >1.7 -- 🏆 Max Drawdown <40% -- 🏆 Profit/Trade >$35 - ---- - -## 🔄 Nächste Phasen (Roadmap) - -### Phase 2A (nach V1.8 Validierung): -**Falls V1.8 erfolgreich (Win-Rate >45%):** -- Confidence Threshold auf 70-75% erhöhen -- Erwartung: Win-Rate >50%, weniger Trades, höchste Qualität - -### Phase 2B (Infrastructure): -- SQLite Migration für besseres Datenmanagement -- Telegram Notifications für Mobile Monitoring -- Automatische Performance-Reports - -### Phase 3 (Advanced): -- Backtesting Framework für historische Analyse -- ML Signal Filter (Random Forest / XGBoost) -- Multi-Symbol Support (XAUUSD + andere Paare) - ---- - -## 📚 Dokumentation - -- **Diese Datei:** V1.8 Aggressive Mode Dokumentation -- [V1.7_SESSION_FILTER_AKTIVIERT.md](V1.7_SESSION_FILTER_AKTIVIERT.md) - Vorherige Version -- [CONFIDENCE_THRESHOLD_GUIDE.md](CONFIDENCE_THRESHOLD_GUIDE.md) - Threshold Anleitung -- [SESSION_FILTER_INSTALLATION.md](SESSION_FILTER_INSTALLATION.md) - Installation Guide -- [session_filter_patch.py](session_filter_patch.py) - Config Datei - ---- - -## ✅ Deployment Checklist - -- [x] Config angepasst (nur NY Session) -- [x] File auf VPS kopiert -- [x] Bot neu gestartet -- [x] Log prüfen: Nur NY Trades -- [ ] Nach 1 Woche: Performance analysieren -- [ ] Nach 2 Wochen: Entscheidung für nächste Phase - ---- - -## 🎲 Zusammenfassung - -**TradingBot V1.8** ist jetzt im **Ultra-Selektiven Modus**: -- Nur die **beste Trading-Session** (NY) -- Höchste **Win-Rate** (~48%) -- Beste **Profit-Effizienz** ($31/Trade) -- Minimales **Risiko** (weniger Drawdown) - -**Trade-off:** -Weniger Trades = weniger absolute Profit-Chancen, ABER: Jeder Trade hat deutlich höhere Erfolgswahrscheinlichkeit! - -**Philosophie:** -"Qualität über Quantität" - Lieber 10 gute Trades als 100 mittelmäßige! - ---- - -**Viel Erfolg mit V1.8! 🚀** - -Melde dich in 1-2 Wochen mit den Performance-Daten! diff --git a/VPS_STATUS_CHECK.md b/VPS_STATUS_CHECK.md deleted file mode 100644 index 9e52423..0000000 --- a/VPS_STATUS_CHECK.md +++ /dev/null @@ -1,172 +0,0 @@ -# 🔍 VPS Status Check - Trading Bot V1.8 - -## Datum: 2025-12-05 - -### 📋 DEPLOYMENT STATUS - -#### Files auf VPS: -- [ ] position_monitor.py (mit History-Fix) uploaded -- [ ] fix_closed_positions.py uploaded -- [ ] clean_invalid_exits.py uploaded -- [ ] trading_database.py (updated) uploaded -- [ ] trading_dashboard.py (updated) uploaded -- [ ] performance_analysis_simple.py uploaded - -#### Ausgeführte Scripts: -- [ ] `clean_invalid_exits.py` ausgeführt -- [ ] `fix_closed_positions.py` ausgeführt -- [ ] Notebook neu gestartet (`Kernel → Restart & Run All`) - -#### Services Running: -- [ ] Position Monitor läuft (prüfen mit `scheduler.get_jobs()`) -- [ ] Streamlit Dashboard läuft (Port 8501) -- [ ] MT5 verbunden -- [ ] Telegram Bot aktiv - ---- - -## 🧪 VERIFICATION TESTS - -### Test 1: Position Monitor Active -```python -# In Jupyter Notebook Cell ausführen: -scheduler.get_jobs() -``` -**Erwartete Ausgabe:** -``` -[ - , - , - , - , - # ← Muss vorhanden sein! -] -``` -- [ ] ✅ position_monitor Job ist aktiv - -### Test 2: Database Status -```python -# In Jupyter Notebook oder via SQL: -import sqlite3 -conn = sqlite3.connect('trading_bot.db') -cursor = conn.cursor() - -cursor.execute(""" - SELECT - COUNT(*) as total, - SUM(CASE WHEN status = 'open' THEN 1 ELSE 0 END) as open, - SUM(CASE WHEN status = 'closed' THEN 1 ELSE 0 END) as closed, - SUM(CASE WHEN status = 'historical' THEN 1 ELSE 0 END) as historical - FROM trades -""") -print(cursor.fetchone()) -``` -**Erwartete Ausgabe:** -``` -(total_trades, open_trades, closed_trades, historical_trades) -``` -- [ ] ✅ Mindestens 4 closed trades mit Profit-Daten - -### Test 3: Geschlossene Trades haben Exit-Daten -```python -cursor.execute(""" - SELECT ticket, net_profit, exit_reason, exit_time - FROM trades - WHERE status = 'closed' - LIMIT 5 -""") -for row in cursor.fetchall(): - print(row) -``` -**Erwartete Ausgabe:** Trades mit net_profit ≠ NULL -- [ ] ✅ Exit-Daten sind vorhanden - -### Test 4: Position Monitor funktioniert -```python -# Manuell testen: -position_monitor.check_open_positions() -``` -**Erwartete Ausgabe:** Keine Errors, evtl. Warnings für offene Positionen -- [ ] ✅ Läuft ohne Errors - -### Test 5: Dashboard erreichbar -- Browser öffnen: `http://localhost:8501` (auf VPS) -- Oder von extern: `http://:8501` -- [ ] ✅ Dashboard lädt -- [ ] ✅ Dashboard zeigt Trades -- [ ] ✅ Filter funktioniert (Live/Historical/All) -- [ ] ✅ Profit-Daten werden angezeigt - ---- - -## 📊 CURRENT METRICS - -### Trades in Database: -- Total Trades: ______ -- Open Trades: ______ -- Closed Trades: ______ -- Historical Trades: ______ - -### Performance (Live Trades only): -- Win Rate: ______% -- Total Profit: $______ -- Average Profit/Trade: $______ - -### Session Distribution (Live): -- NY: ______ trades -- Asian: ______ trades -- London: ______ trades -- Overlap: ______ trades - -**Session Filter Working?** -- [ ] ✅ Nur NY Trades (wenn V1.8 config aktiv) -- [ ] ⚠️ Andere Sessions aktiv (Config prüfen!) - ---- - -## 🔴 ISSUES FOUND - -### Problem 1: _________________________ -**Status:** [ ] Open / [ ] Fixed -**Lösung:** _________________________ - -### Problem 2: _________________________ -**Status:** [ ] Open / [ ] Fixed -**Lösung:** _________________________ - ---- - -## ✅ NEXT STEPS - -### Sofort: -1. [ ] Verifiziere alle Tests oben -2. [ ] Prüfe ob neue Exits automatisch erkannt werden -3. [ ] Warte auf nächsten Trade-Close und prüfe Update - -### Kurzfristig (diese Woche): -1. [ ] Sammle 10+ geschlossene Trades -2. [ ] Führe Performance-Analyse aus -3. [ ] Evaluiere Session Filter Performance - -### Mittelfristig (nächste Woche): -1. [ ] Entscheide: NY only vs NY+Asian -2. [ ] Optimiere Confidence Threshold (falls nötig) -3. [ ] Setup automatische Backups (trading_bot.db) - ---- - -## 📝 NOTES - -**Wichtige Beobachtungen:** -- _________________________ -- _________________________ - -**Fragen:** -- _________________________ -- _________________________ - ---- - -**Status:** 🟢 Running / 🟡 Partial / 🔴 Issues -**Last Updated:** 2025-12-05 ________ -**Updated By:** _________________________ diff --git a/activate_enhanced_scoring.py b/activate_enhanced_scoring.py deleted file mode 100644 index ade4fd6..0000000 --- a/activate_enhanced_scoring.py +++ /dev/null @@ -1,353 +0,0 @@ -#!/usr/bin/env python3 -""" -Script to activate Enhanced Signal Scoring in Trading Logic -Adds a new cell that wraps the trading check with enhanced scoring -""" - -import nbformat -from pathlib import Path -import sys - -def activate_enhanced_scoring(notebook_path): - """Add enhanced scoring activation cell to notebook""" - - # Read notebook - with open(notebook_path, 'r', encoding='utf-8') as f: - nb = nbformat.read(f, as_version=4) - - print(f"📖 Loaded notebook: {Path(notebook_path).name}") - print(f" Current cells: {len(nb.cells)}") - - # Define new cells - new_cells = [] - - # ========================================== - # Cell 1: Markdown Header - # ========================================== - new_cells.append(nbformat.v4.new_markdown_cell("""# 🎯 ENHANCED SIGNAL SCORING ACTIVATION (V1.10) - -**Aktiviert Multi-Faktor-Analyse für Trading Signals** - -Erweitert das Trend-System um: -- 📊 **Volume Analysis** (20%) - Hohes Volume = stärkerer Move -- 📈 **Momentum Indicators** (20%) - RSI + MACD Confirmation -- 🎯 **Support/Resistance** (15%) - Nähe zu Key Levels -- 📐 **Fibonacci Levels** (15%) - Bounce-Zones -- 📉 **Trend Alignment** (30%) - Bestehendes System - -**Status:** ✅ READY TO ACTIVATE -""")) - - # ========================================== - # Cell 2: Enhanced Trading Check Wrapper - # ========================================== - new_cells.append(nbformat.v4.new_code_cell("""# ========================================== -# ENHANCED TRADING CHECK WITH SIGNAL SCORING -# ========================================== - -def enhanced_trading_check_wrapper(symbol="XAUUSD", debug=False): - \"\"\" - Enhanced wrapper around execute_trade_v2_adaptive - Adds multi-factor signal scoring before execution - \"\"\" - - try: - # SCHRITT 1: Position Check (wie vorher) - max_positions = TRADING_CONFIG['risk']['max_positions'] - has_position, position_info = check_existing_positions(symbol) - - if position_info['count'] >= max_positions: - if debug: - print(f"🛑 TRADE BLOCKIERT: {position_info['count']}/{max_positions} Positionen aktiv") - for pos in position_info['details']: - profit_emoji = "🟢" if pos['profit'] >= 0 else "🔴" - print(f" {pos['type']} @ {pos['price_open']} | {profit_emoji} {pos['profit']:.2f}") - return None - - print(f"✅ Position-Check OK: {position_info['count']}/{max_positions}") - - # SCHRITT 1.5: EQUITY CURVE CHECK - ec_allowed, ec_reason, lot_multiplier = equity_curve_manager.should_trade() - print(f"📈 Equity Curve: {ec_reason}") - - if not ec_allowed: - print(f"⛔ TRADE BLOCKIERT durch Equity Curve Filter") - return None - - # SCHRITT 2: Signal Analysis (wie vorher) - signal_info = extended_top_down_v2_adaptive(symbol) - if signal_info is None: - print("❌ Signal-Analyse fehlgeschlagen") - return None - - entry_signal = signal_info["entry_signal"] - base_confidence = signal_info["confidence"] - adaptive_threshold = signal_info["adaptive_threshold"] - - print(f"\\n📊 Base Signal Analysis:") - print(f" Direction: {entry_signal}") - print(f" Base Confidence: {base_confidence:.1f}%") - print(f" Adaptive Threshold: {adaptive_threshold:.1f}%") - - # ⭐ SCHRITT 3: ENHANCED SIGNAL SCORING (NEU!) - print(f"\\n🎯 Calculating Enhanced Signal Score...") - - try: - enhanced = signal_scorer.calculate_enhanced_score( - symbol=symbol, - base_confidence=base_confidence, - trend_direction=entry_signal, - current_price=signal_info['trend_info']['M5']['price'] - ) - - # HYBRID APPROACH: 60% Base Confidence + 40% Enhanced Score - # Das bewährte Trend-System behält Hauptgewicht - enhanced_score = enhanced.total_score - final_confidence = (base_confidence * 0.6) + (enhanced_score * 0.4) - - print(f"\\n✅ Enhanced Signal Scoring (HYBRID 60/40):") - print(f" Trend Score: {enhanced.trend_score:.1f}/100") - print(f" Volume Score: {enhanced.volume_score:.1f}/100") - print(f" Momentum Score: {enhanced.momentum_score:.1f}/100") - print(f" S/R Score: {enhanced.support_resistance_score:.1f}/100") - print(f" Fibonacci Score: {enhanced.fibonacci_score:.1f}/100") - print(f" ─────────────────────────────────────") - print(f" 📊 Base Confidence: {base_confidence:.1f}%") - print(f" 📈 Enhanced Score: {enhanced_score:.1f}%") - print(f" 🔀 HYBRID (60/40): {final_confidence:.1f}%") - print(f" 📈 Signal Quality: {enhanced.signal_quality}") - - # Show reasoning - if enhanced.reason: - print(f"\\n💡 Analysis: {enhanced.reason}") - - except Exception as e: - print(f"⚠️ Enhanced scoring failed: {e}") - print(" Falling back to base confidence") - final_confidence = base_confidence - - # SCHRITT 4: Threshold Check - if entry_signal in [1, -1]: # 1=LONG, -1=SHORT - if final_confidence >= adaptive_threshold: - print(f"\\n🎯 Signal qualified! {final_confidence:.1f}% >= {adaptive_threshold:.1f}%") - - # Execute trade with pre-calculated signal_info and enhanced confidence - result = execute_trade_v2_adaptive( - symbol=symbol, - signal_info_override=signal_info, - confidence_override=final_confidence, # ← Use hybrid score! - lot_multiplier=lot_multiplier # ← Equity Curve adjustment - ) - - # Update Equity Curve nach Trade - if result is not None: - equity_curve_manager.update_equity() - print(f"📈 Equity Curve updated") - - return result - else: - print(f"\\n❌ Signal below threshold: {final_confidence:.1f}% < {adaptive_threshold:.1f}%") - print(f" Base would have been: {base_confidence:.1f}%") - - if final_confidence < base_confidence: - print(f" ⚠️ Enhanced scoring filtered out weak setup!") - - return None - else: - print(f"\\n⏸️ No clear signal: {entry_signal}") - return None - - except Exception as e: - print(f"❌ Enhanced trading check error: {e}") - import traceback - traceback.print_exc() - return None - -print("✅ Enhanced trading check wrapper created!") -print(" This will use multi-factor analysis for all trades") -""")) - - # ========================================== - # Cell 3: Replace Scheduler Job - # ========================================== - new_cells.append(nbformat.v4.new_code_cell("""# ========================================== -# UPDATE SCHEDULER WITH ENHANCED VERSION -# ========================================== - -print("🔄 Updating scheduler with enhanced trading check...") - -# Remove old job -try: - scheduler.remove_job('adaptive_trading_check') - print(" Removed old adaptive_trading_check job") -except: - pass - -# Add enhanced version -scheduler.add_job( - func=lambda: enhanced_trading_check_wrapper("XAUUSD", debug=True), - trigger='interval', - minutes=1, - id='adaptive_trading_check', - name='Enhanced Adaptive Trading Check', - replace_existing=True, - max_instances=1 -) - -print("\\n✅ Enhanced Trading Check activated!") -print(" Scheduler updated with multi-factor signal scoring") - -# Show active jobs -print("\\n📋 Active Scheduler Jobs:") -for job in scheduler.get_jobs(): - print(f" • {job.id}: {job.trigger}") - -print("\\n" + "=" * 70) -print("🎯 ENHANCED SIGNAL SCORING NOW ACTIVE!") -print("=" * 70) -print("\\nBot will now use 5-factor analysis for all trading signals:") -print(" ✅ Trend Alignment (30%)") -print(" ✅ Volume Analysis (20%)") -print(" ✅ Momentum (RSI/MACD) (20%)") -print(" ✅ Support/Resistance (15%)") -print(" ✅ Fibonacci Levels (15%)") -print("\\n💡 Expected improvement: +5-10% Win Rate") -print("=" * 70) -""")) - - # ========================================== - # Cell 4: Test Enhanced Scoring - # ========================================== - new_cells.append(nbformat.v4.new_markdown_cell("""## 🧪 Test Enhanced Signal Scoring - -Run the cell below to test enhanced scoring on current market conditions. -This will show you the difference between base confidence and enhanced score. -""")) - - new_cells.append(nbformat.v4.new_code_cell("""# ========================================== -# TEST ENHANCED SIGNAL SCORING -# ========================================== - -print("🧪 Testing Enhanced Signal Scoring...") -print("=" * 70) - -# Get current signal -signal_info = extended_top_down_v2_adaptive("XAUUSD") - -if signal_info: - base_confidence = signal_info["confidence"] - entry_signal = signal_info["entry_signal"] - - print(f"\\n📊 Base Signal:") - print(f" Direction: {entry_signal}") - print(f" Confidence: {base_confidence:.1f}%") - - # Calculate enhanced score - enhanced = signal_scorer.calculate_enhanced_score( - symbol="XAUUSD", - base_confidence=base_confidence, - trend_direction=entry_signal, - current_price=signal_info['trend_info']['M5']['price'] - ) - - print(f"\\n🎯 Enhanced Analysis:") - print(f" Trend: {enhanced.trend_score:.1f}/100 (30%)") - print(f" Volume: {enhanced.volume_score:.1f}/100 (20%)") - print(f" Momentum: {enhanced.momentum_score:.1f}/100 (20%)") - print(f" S/R: {enhanced.support_resistance_score:.1f}/100 (15%)") - print(f" Fibonacci: {enhanced.fibonacci_score:.1f}/100 (15%)") - print(f" ─────────────────────────────────────") - print(f" Total Score: {enhanced.total_score:.1f}%") - print(f" Quality: {enhanced.signal_quality}") - - # Compare - diff = enhanced.total_score - base_confidence - if diff > 0: - print(f"\\n✅ Enhanced score HIGHER by {diff:.1f}%") - print(f" Setup has strong confirmation factors") - elif diff < 0: - print(f"\\n⚠️ Enhanced score LOWER by {abs(diff):.1f}%") - print(f" Setup has weak confirmation factors") - else: - print(f"\\n⚪ Enhanced score same as base") - - # Show reasoning - if enhanced.reason: - print(f"\\n💡 {enhanced.reason}") - -else: - print("❌ No signal data available") - -print("\\n" + "=" * 70) -print("✅ Test complete!") -""")) - - # ========================================== - # Add cells to notebook at position 83 - # ========================================== - insert_position = 83 # After Option E cells (76-82) - - print(f"\\n📝 Adding {len(new_cells)} new cells at position {insert_position}...") - - for i, cell in enumerate(new_cells, start=insert_position): - nb.cells.insert(i, cell) - cell_type = "Markdown" if cell.cell_type == "markdown" else "Code" - print(f" ✅ Cell {i}: {cell_type}") - - # Save notebook - with open(notebook_path, 'w', encoding='utf-8') as f: - nbformat.write(nb, f) - - print(f"\\n✅ Integration complete!") - print(f" Total cells now: {len(nb.cells)}") - print(f" New cells: {insert_position} - {insert_position + len(new_cells) - 1}") - - return { - 'success': True, - 'notebook': notebook_path, - 'cells_added': len(new_cells), - 'total_cells': len(nb.cells), - 'new_cell_range': f"{insert_position}-{insert_position + len(new_cells) - 1}" - } - - -if __name__ == "__main__": - notebook_path = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - - if not Path(notebook_path).exists(): - print(f"❌ Error: Notebook not found: {notebook_path}") - sys.exit(1) - - print("=" * 80) - print("🎯 ENHANCED SIGNAL SCORING ACTIVATION") - print("=" * 80) - print(f"\\nNotebook: {notebook_path}") - print("Adding: 5 new cells for enhanced signal scoring") - - result = activate_enhanced_scoring(notebook_path) - - if result['success']: - print("\\n" + "=" * 80) - print("🎉 SUCCESS!") - print("=" * 80) - print(f"\\n✅ Added {result['cells_added']} cells to notebook") - print(f" Total cells: {result['total_cells']}") - print(f" New cells: {result['new_cell_range']}") - - print("\\n📋 Next Steps:") - print(" 1. Restart Kernel (Kernel → Restart & Clear Output)") - print(" 2. Run All Cells (Cell → Run All)") - print(" 3. Verify Cell 83-87 outputs") - print(" 4. Test enhanced scoring (Cell 87)") - print(" 5. Monitor first trades with enhanced scoring") - - print("\\n💡 What's different now:") - print(" • Bot uses 5-factor analysis (not just trend)") - print(" • Filters weak setups automatically") - print(" • Expected +5-10% Win Rate improvement") - print(" • All trades shown in logs with component breakdown") - - print("\\n" + "=" * 80) - else: - print(f"\\n❌ Activation failed!") - sys.exit(1) diff --git a/activate_news_filter.py b/activate_news_filter.py deleted file mode 100644 index e8dff96..0000000 --- a/activate_news_filter.py +++ /dev/null @@ -1,112 +0,0 @@ -#!/usr/bin/env python3 -""" -Script to add News Filter cell to notebook -""" - -import json -import sys - -notebook_path = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -print(f"📖 Loading notebook: {notebook_path}") -with open(notebook_path, 'r', encoding='utf-8') as f: - notebook = json.load(f) - -# Create News Filter Info Cell (Markdown) -news_filter_info_cell = { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 📰 News Filter - High-Impact Event Protection\n", - "\n", - "**Status:** ACTIVE - Blockiert Trading 30min vor/nach High-Impact News\n", - "\n", - "### 🛡️ Schutz vor:\n", - "- **NFP (Non-Farm Payrolls)** - 1. Freitag/Monat, 13:30 UTC\n", - "- **CPI (Consumer Price Index)** - Mitte Monat, 13:30 UTC\n", - "- **FOMC (Fed Interest Rate)** - 8x/Jahr, 19:00 UTC\n", - "- **Retail Sales, PMI, etc.**\n", - "\n", - "### ✅ Features:\n", - "- 30min Buffer vor/nach Event\n", - "- Manuelle Event-Liste (keine API nötig)\n", - "- Einfach zu warten\n", - "- Offline-fähig\n", - "\n", - "### 📝 Event Management:\n", - "- Events konfigurieren: `news_events_manual.json`\n", - "- Wöchentlich Updates: Checke ForexFactory Calendar\n", - "\n", - "### 💰 Erwarteter Impact:\n", - "- Verhindert $400-600/Monat News-Losses\n", - "- Trading-Zeit reduziert: ~0.4% (minimal)\n", - "- ROI: EXTREM HOCH ✅\n" - ] -} - -# Create News Filter Integration Cell (Code) -news_filter_integration_cell = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# NEWS FILTER INTEGRATION\n", - "# ==========================================\n", - "\n", - "from news_filter_integration import create_news_filter_wrapper\n", - "\n", - "# Backup original function (if not already backed up)\n", - "if '_original_execute_trade_before_news' not in dir():\n", - " _original_execute_trade_before_news = execute_trade_v2_adaptive\n", - " print(\"✅ Original execute_trade_v2_adaptive saved\")\n", - "\n", - "# Wrap with news filter\n", - "execute_trade_v2_adaptive = create_news_filter_wrapper(\n", - " _original_execute_trade_before_news\n", - ")\n", - "\n", - "print(\"✅ NEWS FILTER ACTIVATED\")\n", - "print(\"-\" * 60)\n", - "print(\"Protection: Trading blocked 30min before/after HIGH-IMPACT news\")\n", - "print(\"Events monitored:\")\n", - "print(\" • NFP (Non-Farm Payrolls)\")\n", - "print(\" • CPI (Consumer Price Index)\")\n", - "print(\" • FOMC (Fed Interest Rate Decision)\")\n", - "print(\" • Retail Sales, PMI, GDP\")\n", - "print(\" • Other high-impact USD/EUR/GBP events\")\n", - "print(\"-\" * 60)\n", - "print(\"\\n📝 To add events: Edit news_events_manual.json\")\n", - "print(\"💡 Recommended: Weekly check ForexFactory calendar\")\n" - ] -} - -# Find position to insert (after Cell 30 - execute_trade integration) -# We want to insert after the telegram integration cells -insert_position = 31 # After Cell 30 - -print(f"\n📝 Inserting News Filter cells at position {insert_position}...") -notebook['cells'].insert(insert_position, news_filter_info_cell) -notebook['cells'].insert(insert_position + 1, news_filter_integration_cell) - -# Update cell count -new_total = len(notebook['cells']) -print(f"✅ New total cells: {new_total}") - -# Save notebook -print(f"\n💾 Saving notebook...") -with open(notebook_path, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - -print("✅ Notebook updated successfully!") -print(f"\n📋 Added cells:") -print(f" Cell {insert_position}: News Filter Info (Markdown)") -print(f" Cell {insert_position + 1}: News Filter Integration (Code)") -print(f"\n🎯 News Filter is now at positions {insert_position}-{insert_position + 1}") -print(f" (Total cells: {new_total})") -print("\n📝 NEXT STEPS:") -print(" 1. Open notebook") -print(f" 2. Run Cell {insert_position + 1} (News Filter Integration)") -print(" 3. Add upcoming events to news_events_manual.json") -print(" 4. Done! Bot is protected from news events!") diff --git a/add_ranging_filter_cells.py b/add_ranging_filter_cells.py deleted file mode 100644 index 7772bc9..0000000 --- a/add_ranging_filter_cells.py +++ /dev/null @@ -1,235 +0,0 @@ -#!/usr/bin/env python3 -""" -🔥 Add Ranging Filter + Position Monitor Fix as NEW cells -Einfacherer Ansatz: Fügt neue Cells hinzu statt bestehende zu modifizieren -""" - -import json -import sys -from datetime import datetime - -NOTEBOOK_PATH = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -def add_filter_cells(): - """Fügt neue Cells für Fixes hinzu""" - - print("=" * 70) - print("🔥 Adding Ranging Filter + Position Monitor Fixes") - print("=" * 70) - - # 1. Load - print(f"\n1️⃣ Loading: {NOTEBOOK_PATH}") - with open(NOTEBOOK_PATH, 'r', encoding='utf-8') as f: - nb = json.load(f) - print(f"✅ Loaded {len(nb['cells'])} cells") - - # 2. Backup - backup_path = NOTEBOOK_PATH.replace('.ipynb', f'_backup_{datetime.now().strftime("%Y%m%d_%H%M%S")}.ipynb') - print(f"\n2️⃣ Backup: {backup_path}") - with open(backup_path, 'w', encoding='utf-8') as f: - json.dump(nb, f, indent=1, ensure_ascii=False) - print("✅ Backup created") - - # 3. Find execute_trade cell - execute_idx = None - for i, cell in enumerate(nb['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell['source']) - if 'def execute_trade_v2_adaptive' in source: - execute_idx = i - break - - if not execute_idx: - print("❌ Could not find execute_trade cell") - return False - - print(f"\n3️⃣ Found execute_trade at cell {execute_idx}") - - # 4. Create NEW cell with ranging filter wrapper - print("\n4️⃣ Creating Ranging Filter wrapper...") - - ranging_filter_code = """# ========================================== -# 🔥 FIX #1: RANGING FILTER WRAPPER (09.12.2025) -# ========================================== - -# Original function wird wrapped -_original_execute_trade_v2_adaptive = execute_trade_v2_adaptive - -def execute_trade_v2_adaptive_with_ranging_filter( - symbol="XAUUSD", - atr_mult=1.5, - base_confidence=60, - max_risk_per_trade=0.01, - risk_filter=True, - min_atr=0.0008, - use_pullback_entry=False, - max_positions=1, - strategy_name="TradingBot_V1.6", - debug=True): - \"\"\" - Wrapper für execute_trade_v2_adaptive mit Ranging Filter - Blocks trading in ranging markets - they cause 100% of losses! - \"\"\" - - # Quick check: Get signal info first - signal_info = extended_top_down_v2_adaptive(symbol) - if signal_info is None: - return None - - market_regime = signal_info.get("market_regime", {}) - regime = market_regime.get('regime', 'unknown') - adx = market_regime.get('adx', 0) - - # 🛑 RANGING FILTER - Block ALL ranging market trades - if regime == 'ranging': - if debug: - print(f"\\n🛑 TRADE BLOCKIERT: Ranging Market!") - print(f" ADX: {adx:.1f} (< 25 = Ranging)") - print(f" 📊 Ranging Performance: 0% Win Rate, 20 consecutive losses") - print(f" ✅ Filter is protecting you from losses!") - return None - - # Additional safety: Even in trending, ADX must be > 25 - if regime == 'trending' and adx < 25: - if debug: - print(f"\\n🛑 TRADE BLOCKIERT: Weak Trend!") - print(f" ADX: {adx:.1f} (< 25 = too weak)") - return None - - # ✅ Regime check passed - execute original function - if debug: - print(f"✅ REGIME CHECK PASSED: {regime.upper()} (ADX {adx:.1f})") - - return _original_execute_trade_v2_adaptive( - symbol=symbol, - atr_mult=atr_mult, - base_confidence=base_confidence, - max_risk_per_trade=max_risk_per_trade, - risk_filter=risk_filter, - min_atr=min_atr, - use_pullback_entry=use_pullback_entry, - max_positions=max_positions, - strategy_name=strategy_name, - debug=debug - ) - -# Replace original with wrapped version -execute_trade_v2_adaptive = execute_trade_v2_adaptive_with_ranging_filter - -print("✅ Ranging Filter activated!") -print(" 🛑 Blocks ALL ranging market trades") -print(" ✅ Only allows trending markets with ADX > 25") -""" - - new_cell = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": ranging_filter_code.split('\n') - } - - # Insert AFTER execute_trade cell - nb['cells'].insert(execute_idx + 1, new_cell) - print(f"✅ Ranging Filter cell inserted at position {execute_idx + 1}") - - # 5. Create Position Monitor Fix cell - print("\n5️⃣ Creating Position Monitor DB Fix...") - - position_monitor_fix = """# ========================================== -# 🔥 FIX #2: POSITION MONITOR DB LOGGING (09.12.2025) -# ========================================== - -# Wrap check_open_positions to add DB logging -if 'check_open_positions' in globals(): - _original_check_open_positions = check_open_positions - - def check_open_positions_with_db_logging(): - \"\"\" - Enhanced position monitor that writes exits to database - \"\"\" - from datetime import datetime - - # Get current open positions from MT5 - positions = mt.positions_get(symbol=symbol) - - if not positions or len(positions) == 0: - # Check if we have positions in DB that should be closed - if 'db' in globals(): - try: - open_trades_in_db = db.get_open_trades() - - for trade in open_trades_in_db: - ticket = trade['ticket'] - - # Check if this position is in MT5 history (closed) - deals = mt.history_deals_get(ticket=ticket) - if deals and len(deals) > 0: - # Position was closed - log to DB - last_deal = deals[-1] - - db.close_trade( - ticket=ticket, - exit_price=last_deal.price, - exit_time=datetime.fromtimestamp(last_deal.time), - profit=last_deal.profit, - status='closed', - exit_reason='mt5_detected', - commission=last_deal.commission, - swap=last_deal.swap - ) - - logger.info(f"💾 Position #{ticket} exit logged to DB (profit: ${last_deal.profit:.2f})") - - except Exception as e: - logger.error(f"⚠️ DB logging error: {e}") - - # Call original function - return _original_check_open_positions() - - # Replace - check_open_positions = check_open_positions_with_db_logging - print("✅ Position Monitor DB logging activated!") - print(" 💾 Exits will be written to SQLite database") - print(" 📊 Drawdown Protection will work correctly") -else: - print("⚠️ check_open_positions not found - skipping Position Monitor fix") -""" - - new_cell_2 = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": position_monitor_fix.split('\n') - } - - # Insert after ranging filter cell - nb['cells'].insert(execute_idx + 2, new_cell_2) - print(f"✅ Position Monitor Fix cell inserted at position {execute_idx + 2}") - - # 6. Save - print(f"\n6️⃣ Saving patched notebook...") - with open(NOTEBOOK_PATH, 'w', encoding='utf-8') as f: - json.dump(nb, f, indent=1, ensure_ascii=False) - print("✅ Notebook saved!") - - print("\n" + "=" * 70) - print("✅ FIXES ADDED AS NEW CELLS!") - print("=" * 70) - print(f"\n📍 New cells added at positions {execute_idx + 1} and {execute_idx + 2}") - print("\n🔥 FIXES:") - print(" 1. ✅ Ranging Filter - Wrapper around execute_trade") - print(" 2. ✅ Position Monitor - DB logging for exits") - print("\n⏰ NEXT STEPS:") - print(" 1. Open Jupyter Notebook") - print(" 2. Kernel → Restart & Run All") - print(" 3. Verify: \"✅ Ranging Filter activated!\"") - print(" 4. Verify: \"✅ Position Monitor DB logging activated!\"") - print(f"\n💾 Backup: {backup_path}") - - return True - -if __name__ == "__main__": - success = add_filter_cells() - sys.exit(0 if success else 1) diff --git a/add_regime_indicator.py b/add_regime_indicator.py deleted file mode 100644 index 5a1d6f9..0000000 --- a/add_regime_indicator.py +++ /dev/null @@ -1,161 +0,0 @@ -#!/usr/bin/env python3 -""" -🎨 Add Market Regime Indicator Cell to Notebook -Shows live regime status with visual indicator -""" - -import json -from datetime import datetime - -NOTEBOOK_PATH = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -def add_regime_indicator(): - """Add regime indicator cell""" - - print("=" * 70) - print("🎨 Adding Market Regime Indicator") - print("=" * 70) - - # Load notebook - with open(NOTEBOOK_PATH, 'r', encoding='utf-8') as f: - nb = json.load(f) - - # Create regime indicator cell - regime_indicator_code = """# ========================================== -# 📊 MARKET REGIME INDICATOR (Live Status) -# ========================================== - -def show_current_regime(symbol="XAUUSD"): - \"\"\"Display current market regime with visual indicator\"\"\" - - from datetime import datetime - - print("\\n" + "=" * 70) - print(f"📊 MARKET REGIME STATUS - {symbol}") - print("=" * 70) - - # Get signal - try: - signal_info = extended_top_down_v2_adaptive(symbol) - - if signal_info is None: - print("❌ Could not get signal info") - return None - - # Extract data - market_regime = signal_info.get("market_regime", {}) - regime = market_regime.get('regime', 'unknown') - adx = market_regime.get('adx', 0) - - # Get current price - tick = mt.symbol_info_tick(symbol) - current_price = tick.bid if tick else 0 - - # Display - print(f"\\n⏰ Time: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}") - print(f"💹 Price: ${current_price:.2f}") - print(f"\\n📈 REGIME:") - - # Visual indicator - if regime == 'ranging': - print(" 🔴 RANGING MARKET") - print(f" ADX: {adx:.1f} (< 25)") - print(" Status: ❌ Trading BLOCKED") - print(" Reason: No clear trend") - bar_color = "🔴" - can_trade = False - elif regime == 'trending' and adx >= 25: - print(" 🟢 TRENDING MARKET") - print(f" ADX: {adx:.1f} (≥ 25)") - print(" Status: ✅ Trading ALLOWED") - print(" Reason: Strong trend detected") - bar_color = "🟢" - can_trade = True - else: - print(" 🟡 WEAK TREND") - print(f" ADX: {adx:.1f} (< 25)") - print(" Status: ⚠️ Trading BLOCKED") - print(" Reason: Trend too weak") - bar_color = "🟡" - can_trade = False - - # ADX bar - bar_length = min(int(adx / 2), 50) - print(f"\\n📊 ADX Scale:") - print(f" {bar_color} {'█' * bar_length} {adx:.1f}") - print(" ├─────┼─────┼─────┼─────┼─────┤") - print(" 0 10 20 25 40 50+") - print(" ↑ ↑") - print(" Ranging Trending") - - # Signal info - if 'direction' in signal_info: - direction = signal_info['direction'] - confidence = signal_info.get('confidence', 0) - print(f"\\n📍 Signal:") - print(f" Direction: {direction}") - print(f" Confidence: {confidence:.1f}%") - - print("\\n" + "=" * 70 + "\\n") - - return { - 'regime': regime, - 'adx': adx, - 'can_trade': can_trade, - 'price': current_price - } - - except Exception as e: - print(f"❌ Error: {e}") - import traceback - traceback.print_exc() - return None - -# Run indicator -print("\\n🎯 To check regime anytime, run: show_current_regime()") -print("\\n📊 Running initial check...") -result = show_current_regime("XAUUSD") -""" - - new_cell = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": regime_indicator_code.split('\n') - } - - # Find good position (after execute_trade cells) - insert_pos = len(nb['cells']) - 1 # Before last cell - - # Insert - nb['cells'].insert(insert_pos, new_cell) - - # Backup - backup_path = NOTEBOOK_PATH.replace('.ipynb', f'_backup_regime_indicator_{datetime.now().strftime("%Y%m%d_%H%M%S")}.ipynb') - with open(backup_path, 'w', encoding='utf-8') as f: - json.dump(nb, f, indent=1, ensure_ascii=False) - - # Save - with open(NOTEBOOK_PATH, 'w', encoding='utf-8') as f: - json.dump(nb, f, indent=1, ensure_ascii=False) - - print(f"✅ Regime Indicator cell added at position {insert_pos}") - print(f"💾 Backup: {backup_path}") - - print("\n" + "=" * 70) - print("✅ REGIME INDICATOR ADDED!") - print("=" * 70) - print("\n⏰ NEXT STEPS:") - print(" 1. Open Jupyter Notebook") - print(" 2. Run the new Regime Indicator cell") - print(" 3. Call show_current_regime() anytime to check!") - print("\n💡 USAGE:") - print(" show_current_regime() # Check current regime") - - return True - -if __name__ == "__main__": - import sys - success = add_regime_indicator() - sys.exit(0 if success else 1) diff --git a/add_telegram_cells.py b/add_telegram_cells.py deleted file mode 100644 index 18e4300..0000000 --- a/add_telegram_cells.py +++ /dev/null @@ -1,161 +0,0 @@ -#!/usr/bin/env python3 -""" -Fügt Telegram Bot Command Cells ins Notebook hinzu -""" - -import json -import sys - -# Load notebook -notebook_path = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -print(f"📖 Loading notebook: {notebook_path}") -with open(notebook_path, 'r', encoding='utf-8') as f: - notebook = json.load(f) - -# Count cells -total_cells = len(notebook['cells']) -print(f"📊 Current cells: {total_cells}") - -# Find position to insert (after session confidence filter cells, which should be around cell 26) -# We want to insert after cell 26 (the session confidence filter) -insert_position = 27 # After cell 26 (0-indexed: position 27) - -# Create Cell 1: Telegram Bot Starter (Markdown Info) -telegram_info_cell = { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 🤖 Telegram Bot Commands - Remote Control\n", - "\n", - "**Status:** ACTIVE - Bot läuft im Hintergrund\n", - "\n", - "### 📱 Verfügbare Commands:\n", - "\n", - "**Bot Control:**\n", - "- `/status` - Bot Status, offene Positionen, Balance\n", - "- `/pause` - Trading pausieren (keine neuen Trades)\n", - "- `/resume` - Trading fortsetzen\n", - "- `/close confirm` - ALLE Positionen schließen (Emergency)\n", - "\n", - "**Information:**\n", - "- `/balance` - Aktueller Kontostand + Equity\n", - "- `/stats` - Performance Statistiken\n", - "- `/help` - Hilfe anzeigen\n", - "\n", - "### ✅ Features:\n", - "- Remote Control vom Handy\n", - "- Emergency Stop von überall\n", - "- Trading Pause/Resume\n", - "- Live Status & Balance Check\n", - "\n", - "### 🔒 Sicherheit:\n", - "- Nur deine Chat ID kann Commands senden\n", - "- `/close` requires confirmation\n", - "- `/pause` ist instant\n" - ] -} - -# Create Cell 2: Telegram Bot Commander Code -telegram_bot_cell = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# TELEGRAM BOT COMMANDS - Background Service\n", - "# ==========================================\n", - "\n", - "from telegram_bot_commands import TelegramBotCommander, get_bot_controller\n", - "import threading\n", - "\n", - "# Start Telegram Bot in background\n", - "try:\n", - " print(\"🚀 Starting Telegram Bot Commander...\")\n", - " \n", - " bot_commander = TelegramBotCommander()\n", - " bot_thread = bot_commander.start_background()\n", - " \n", - " # Get controller for integration with execute_trade\n", - " bot_controller = get_bot_controller()\n", - " \n", - " print(\"✅ Telegram Bot is running in background!\")\n", - " print(\"📱 Available Commands:\")\n", - " print(\" /status - Bot status & positions\")\n", - " print(\" /pause - Pause trading\")\n", - " print(\" /resume - Resume trading\")\n", - " print(\" /close - Close all positions (requires confirm)\")\n", - " print(\" /balance - Account balance\")\n", - " print(\" /stats - Performance stats\")\n", - " print(\" /help - Show help\")\n", - " \n", - "except Exception as e:\n", - " print(f\"❌ Failed to start Telegram Bot: {e}\")\n", - " bot_controller = None\n" - ] -} - -# Create Cell 3: Integration with execute_trade -telegram_integration_cell = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INTEGRATION: Bot Controller mit execute_trade\n", - "# ==========================================\n", - "\n", - "# Original execute_trade_v2_adaptive function wrappen\n", - "if 'bot_controller' in dir() and bot_controller is not None:\n", - " \n", - " # Original Funktion sichern\n", - " if '_original_execute_trade_before_telegram' not in dir():\n", - " _original_execute_trade_before_telegram = execute_trade_v2_adaptive\n", - " \n", - " def execute_trade_with_telegram_control(*args, **kwargs):\n", - " \"\"\"\n", - " Wrapper der bot_controller.is_paused prüft\n", - " \"\"\"\n", - " # Check if trading is paused\n", - " if bot_controller.is_paused:\n", - " print(\"⏸️ Trading PAUSED via Telegram\")\n", - " print(f\" Reason: {bot_controller.pause_reason}\")\n", - " return\n", - " \n", - " # Execute original function\n", - " return _original_execute_trade_before_telegram(*args, **kwargs)\n", - " \n", - " # Replace execute_trade\n", - " execute_trade_v2_adaptive = execute_trade_with_telegram_control\n", - " \n", - " print(\"✅ execute_trade_v2_adaptive wrapped with Telegram control\")\n", - " print(\" Trading can now be paused/resumed via /pause and /resume\")\n", - "else:\n", - " print(\"⚠️ bot_controller not available, skipping integration\")\n" - ] -} - -# Insert cells -print(f"\n📝 Inserting 3 new cells at position {insert_position}...") -notebook['cells'].insert(insert_position, telegram_info_cell) -notebook['cells'].insert(insert_position + 1, telegram_bot_cell) -notebook['cells'].insert(insert_position + 2, telegram_integration_cell) - -# Update cell count -new_total = len(notebook['cells']) -print(f"✅ New total cells: {new_total} (was {total_cells})") - -# Save notebook -print(f"\n💾 Saving notebook...") -with open(notebook_path, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - -print("✅ Notebook updated successfully!") -print(f"\n📋 Added cells:") -print(f" Cell {insert_position}: Telegram Bot Info (Markdown)") -print(f" Cell {insert_position + 1}: Telegram Bot Commander (Code)") -print(f" Cell {insert_position + 2}: execute_trade Integration (Code)") -print(f"\n🎯 Cells are now at positions {insert_position}-{insert_position + 2}") -print(f" (Previously the notebook had {total_cells} cells, now it has {new_total})") diff --git a/centralize_config.py b/centralize_config.py deleted file mode 100644 index 0cf13df..0000000 --- a/centralize_config.py +++ /dev/null @@ -1,175 +0,0 @@ -#!/usr/bin/env python3 -""" -Centralize Trading Bot Configuration -Creates a centralized configuration cell and updates all references -""" - -import json - -notebook_path = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -print("=" * 70) -print("🔧 CENTRALIZING TRADING BOT CONFIGURATION") -print("=" * 70) -print() - -# Load notebook -with open(notebook_path, 'r', encoding='utf-8') as f: - notebook = json.load(f) - -print(f"Loaded notebook with {len(notebook['cells'])} cells") -print() - -# Create centralized config cell -config_cell_markdown = { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 📋 CENTRALIZED TRADING CONFIGURATION\n", - "\n", - "**All trading parameters in one place for easy management**" - ] -} - -config_cell_code = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": [ - "# ============================================================================\n", - "# CENTRALIZED TRADING CONFIGURATION\n", - "# ============================================================================\n", - "# All trading parameters should be configured here and referenced throughout\n", - "# the notebook to avoid scattered settings\n", - "\n", - "TRADING_CONFIG = {\n", - " # ========================================================================\n", - " # LOT SIZING & POSITION MANAGEMENT\n", - " # ========================================================================\n", - " 'lot_sizing': {\n", - " 'min_lot': 0.10, # Minimum lot size\n", - " 'max_lot': 0.20, # Maximum lot size\n", - " 'default_lot': 0.10, # Fallback lot size\n", - " 'use_adaptive': True, # Use adaptive position sizing\n", - " },\n", - " \n", - " # ========================================================================\n", - " # RISK MANAGEMENT\n", - " # ========================================================================\n", - " 'risk': {\n", - " 'max_risk_per_trade': 0.02, # 2% max risk per trade\n", - " 'max_positions': 1, # Maximum concurrent positions\n", - " 'max_daily_loss': 0.05, # 5% max daily loss\n", - " },\n", - " \n", - " # ========================================================================\n", - " # CONFIDENCE THRESHOLDS\n", - " # ========================================================================\n", - " 'confidence': {\n", - " 'base_threshold': 70, # Base confidence threshold (all sessions)\n", - " 'ny_threshold': 70, # NY session threshold (was 97, reduced for more trades)\n", - " 'asian_threshold': 70, # Asian session threshold\n", - " 'london_threshold': 70, # London session threshold\n", - " },\n", - " \n", - " # ========================================================================\n", - " # ATR & STOP LOSS\n", - " # ========================================================================\n", - " 'atr': {\n", - " 'base_multiplier': 1.5, # Base ATR multiplier for SL/TP\n", - " 'period': 14, # ATR calculation period\n", - " },\n", - " \n", - " # ========================================================================\n", - " # NEWS FILTER\n", - " # ========================================================================\n", - " 'news_filter': {\n", - " 'enabled': True, # Enable/disable news filter\n", - " 'minutes_before': 30, # Minutes before event to block\n", - " 'minutes_after': 30, # Minutes after event to block\n", - " },\n", - " \n", - " # ========================================================================\n", - " # SESSION SETTINGS\n", - " # ========================================================================\n", - " 'sessions': {\n", - " 'asian_enabled': True,\n", - " 'london_enabled': False, # Currently disabled\n", - " 'ny_enabled': True,\n", - " 'overlap_enabled': False, # Currently disabled\n", - " },\n", - " \n", - " # ========================================================================\n", - " # TRADING SYMBOLS\n", - " # ========================================================================\n", - " 'symbols': {\n", - " 'primary': 'XAUUSD', # Primary trading symbol (Gold)\n", - " 'alternative': [], # Alternative symbols (if needed)\n", - " },\n", - "}\n", - "\n", - "# ============================================================================\n", - "# HELPER FUNCTIONS\n", - "# ============================================================================\n", - "\n", - "def get_config(section, key=None):\n", - " \"\"\"Get configuration value\"\"\"\n", - " if key is None:\n", - " return TRADING_CONFIG.get(section, {})\n", - " return TRADING_CONFIG.get(section, {}).get(key)\n", - "\n", - "def update_config(section, key, value):\n", - " \"\"\"Update configuration value (runtime only, doesn't save to notebook)\"\"\"\n", - " if section not in TRADING_CONFIG:\n", - " TRADING_CONFIG[section] = {}\n", - " TRADING_CONFIG[section][key] = value\n", - " print(f\"✅ Updated: {section}.{key} = {value}\")\n", - "\n", - "# Print current configuration\n", - "print(\"✅ TRADING CONFIGURATION LOADED\")\n", - "print()\n", - "print(f\"📊 Lot Sizing: {TRADING_CONFIG['lot_sizing']['min_lot']} - {TRADING_CONFIG['lot_sizing']['max_lot']} lots\")\n", - "print(f\"⚠️ Max Risk: {TRADING_CONFIG['risk']['max_risk_per_trade']*100}% per trade\")\n", - "print(f\"🎯 Confidence Threshold: {TRADING_CONFIG['confidence']['base_threshold']}%\")\n", - "print(f\"🛡️ News Filter: {'ENABLED' if TRADING_CONFIG['news_filter']['enabled'] else 'DISABLED'}\")\n", - "print(f\"🌍 Primary Symbol: {TRADING_CONFIG['symbols']['primary']}\")" - ] -} - -# Find a good insertion point (after imports, before main logic) -# Let's insert after the first few setup cells (position 5) -insert_position = 5 - -print(f"Inserting centralized config at position {insert_position}") -print() - -# Insert the markdown and code cells -notebook['cells'].insert(insert_position, config_cell_markdown) -notebook['cells'].insert(insert_position + 1, config_cell_code) - -print(f"✅ Added 2 new cells (markdown + config)") -print(f" Total cells now: {len(notebook['cells'])}") -print() - -# Save the modified notebook -with open(notebook_path, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - -print("✅ Notebook updated successfully!") -print() -print("=" * 70) -print("📋 NEXT STEPS:") -print("=" * 70) -print() -print("1. Open Jupyter Notebook") -print("2. Locate the new cells (should be around cell 5-6)") -print("3. Run the configuration cell to load TRADING_CONFIG") -print("4. Update Cells 23, 25, 47 to reference TRADING_CONFIG") -print(" instead of hardcoded values") -print() -print("Example usage in code:") -print(" volume = TRADING_CONFIG['lot_sizing']['default_lot']") -print(" max_risk = TRADING_CONFIG['risk']['max_risk_per_trade']") -print() -print("=" * 70) diff --git a/debug_telegram_bot.md b/debug_telegram_bot.md deleted file mode 100644 index 5480c74..0000000 --- a/debug_telegram_bot.md +++ /dev/null @@ -1,204 +0,0 @@ -# 🔍 TELEGRAM BOT DEBUG GUIDE - -**Problem:** Bot antwortet nicht auf `/help` in Telegram - ---- - -## ✅ CHECKS - -### **Check 1: Ist der Bot wirklich gestartet?** - -Im Notebook, in der Cell wo du den Bot gestartet hast, solltest du sehen: - -``` -✅ Telegram Bot Commander initialized -📱 Bot Token: 7783303065:AAHVVvwW... -👤 Chat ID: 8039713369 -✅ Command handlers registered -🚀 Starting Telegram Bot... -✅ Telegram Bot running in background -``` - -**Siehst du das?** ✅ JA / ❌ NEIN - ---- - -### **Check 2: Richtiger Bot Name?** - -Der Bot heißt: **@Xausd_digger_bot** - -Im Telegram: -1. Suche nach `@Xausd_digger_bot` -2. Öffne den Chat -3. Sende `/help` - -**Hast du den richtigen Bot geöffnet?** ✅ JA / ❌ NEIN - ---- - -### **Check 3: Deine Chat ID** - -Deine konfigurierte Chat ID ist: `8039713369` - -**Check deine eigene Chat ID:** -1. Öffne Telegram -2. Suche nach `@userinfobot` -3. Sende `/start` -4. Du bekommst deine User ID - -**Ist es `8039713369`?** ✅ JA / ❌ NEIN - -Wenn NEIN, dann **antwortet der Bot dir nicht**, weil er nur auf Chat ID `8039713369` reagiert! - ---- - -### **Check 4: Bot läuft wirklich im Background?** - -Im Notebook, führe aus: - -```python -# Check ob bot_thread läuft -print(f"Bot Thread alive: {bot_thread.is_alive()}") -print(f"Bot Controller exists: {bot_controller is not None}") -``` - -**Output sollte sein:** -``` -Bot Thread alive: True -Bot Controller exists: True -``` - -**Ist das so?** ✅ JA / ❌ NEIN - ---- - -### **Check 5: Telegram API erreichbar?** - -Test ob Telegram grundsätzlich funktioniert: - -```python -import requests - -bot_token = "7783303065:AAHVVvwWGqmhJ2BVq8LqkLRSsicKy1CUsD8" - -# Test API -response = requests.get(f"https://api.telegram.org/bot{bot_token}/getMe") -print(response.json()) - -# Test send message -test_msg = requests.post( - f"https://api.telegram.org/bot{bot_token}/sendMessage", - json={'chat_id': '8039713369', 'text': '🧪 Direct API Test'} -) -print(test_msg.json()) -``` - -**Bekommst du eine Test-Message in Telegram?** ✅ JA / ❌ NEIN - ---- - -## 🔧 LÖSUNGEN - -### **Lösung 1: Chat ID falsch** - -Wenn deine Chat ID NICHT `8039713369` ist: - -1. Öffne `telegram_config.json` -2. Ändere `"chat_id": "8039713369"` zu deiner echten Chat ID -3. Bot neu starten - ---- - -### **Lösung 2: Bot läuft nicht** - -Wenn `bot_thread.is_alive()` = False: - -**Neu starten:** -1. Gehe zu der Cell wo du den Bot gestartet hast -2. Führe sie erneut aus -3. Du solltest sehen: `✅ Telegram Bot running in background` - ---- - -### **Lösung 3: Falscher Bot** - -Stelle sicher dass du wirklich mit `@Xausd_digger_bot` chattest! - -Im Telegram: -- Tippe `@Xausd_digger_bot` in die Suche -- Öffne den Bot -- Sende `/start` - -Wenn der Bot **nicht antwortet**, dann läuft er nicht richtig. - ---- - -### **Lösung 4: Error im Bot** - -Checke ob Errors im Notebook stehen: - -Scroll zu der Cell wo du den Bot gestartet hast - siehst du Fehler oder Exceptions? - -Wenn JA: Kopiere den Fehler und wir fixen ihn. - ---- - -## 🧪 QUICK TEST - -**Führe das im Notebook aus:** - -```python -# Quick Bot Test -import requests - -bot_token = "7783303065:AAHVVvwWGqmhJ2BVq8LqkLRSsicKy1CUsD8" -chat_id = "8039713369" - -# Sende Test-Message direkt via API -response = requests.post( - f"https://api.telegram.org/bot{bot_token}/sendMessage", - json={ - 'chat_id': chat_id, - 'text': '🧪 **QUICK TEST**\n\nWenn du das siehst, funktioniert die API!\n\nJetzt teste `/help`', - 'parse_mode': 'Markdown' - } -) - -if response.status_code == 200: - print("✅ Test-Message sent successfully!") - print("📱 Check your Telegram - you should see the message") -else: - print(f"❌ Failed: {response.status_code}") - print(response.json()) -``` - -**Bekommst du die Message?** - -- ✅ **JA** → API funktioniert, aber Bot Commands nicht → Bot läuft vermutlich nicht richtig -- ❌ **NEIN** → API Problem oder falsche Chat ID - ---- - -## 📋 NEXT STEPS - -**Wenn Test-Message FUNKTIONIERT aber `/help` NICHT:** - -→ Der Bot läuft nicht richtig im Background - -**Fix:** -1. Suche die Cell wo du `bot_commander.start_background()` ausgeführt hast -2. Führe sie erneut aus -3. Checke ob Output zeigt: `✅ Bot is running` - -**Wenn Test-Message NICHT FUNKTIONIERT:** - -→ Chat ID oder Bot Token falsch - -**Fix:** -1. Check deine Chat ID mit `@userinfobot` -2. Update `telegram_config.json` mit richtiger Chat ID -3. Bot neu starten - ---- - -**Mach den Quick Test und sag mir was passiert!** 🔍 diff --git a/demo_test_stats.json b/demo_test_stats.json deleted file mode 100644 index 0667a2d..0000000 --- a/demo_test_stats.json +++ /dev/null @@ -1,8061 +0,0 @@ -{ - "start_date": "2026-01-28T09:59:20.002050", - "last_updated": "2026-01-29T09:04:15.696893", - "trades": [ - { - "ticket": 641628738, - "symbol": "XAUUSD", - "direction": "LONG", - "entry_price": 4400.63, - "exit_price": 4412.37, - "volume": 0.01, - "profit": 11.74, - "profit_pips": 117.39999999999782, - "entry_time": "2026-01-05T05:45:00", - "exit_time": "2026-01-05T06:05:13", - "duration_minutes": 20.216666666666665, - "session": "asian", - "base_confidence": 0, - "enhanced_score": 0, - "hybrid_score": 0, - "signal_quality": "unknown", - "equity_curve_multiplier": 1.0, - "is_win": true, - "stop_loss": 0.0, - "take_profit": 0.0, - "close_reason": "manual" - }, - { - "ticket": 641700832, - "symbol": "XAUUSD", - "direction": "LONG", - "entry_price": 4410.85, - "exit_price": 4402.41, - "volume": 0.01, - "profit": -8.44, - "profit_pips": -84.4000000000051, - "entry_time": "2026-01-05T06:15:00", - "exit_time": "2026-01-05T06:58:36", - "duration_minutes": 43.6, - "session": "asian", - "base_confidence": 0, - "enhanced_score": 0, - "hybrid_score": 0, - "signal_quality": "unknown", - "equity_curve_multiplier": 1.0, - "is_win": false, - "stop_loss": 0.0, - "take_profit": 0.0, - "close_reason": "stop_loss" - }, - { - "ticket": 641784321, - "symbol": "XAUUSD", - "direction": "LONG", - "entry_price": 4399.99, - "exit_price": 4408.38, - "volume": 0.01, - "profit": 8.39, - "profit_pips": 83.90000000000327, - "entry_time": "2026-01-05T07:00:00", - "exit_time": "2026-01-05T08:17:12", - "duration_minutes": 77.2, - "session": "asian", - "base_confidence": 0, - "enhanced_score": 0, - "hybrid_score": 0, - "signal_quality": "unknown", - "equity_curve_multiplier": 1.0, - "is_win": true, - "stop_loss": 0.0, - "take_profit": 0.0, - "close_reason": "manual" - }, - { - "ticket": 641950979, - "symbol": "XAUUSD", - "direction": "LONG", - "entry_price": 4412.72, - "exit_price": 4407.73, - "volume": 0.01, - "profit": -4.99, - "profit_pips": -49.90000000000691, - "entry_time": "2026-01-05T08:30:00", - "exit_time": "2026-01-05T08:42:57", - "duration_minutes": 12.95, - "session": "london", - "base_confidence": 0, - "enhanced_score": 0, - "hybrid_score": 0, - "signal_quality": "unknown", - "equity_curve_multiplier": 1.0, - "is_win": false, - "stop_loss": 0.0, - "take_profit": 0.0, - "close_reason": "stop_loss" - }, - { - "ticket": 642005938, - "symbol": "XAUUSD", - "direction": "LONG", - "entry_price": 4401.95, - "exit_price": 4408.87, - "volume": 0.01, - "profit": 6.92, - "profit_pips": 69.20000000000073, - "entry_time": "2026-01-05T08:45:00", - "exit_time": "2026-01-05T08:53:12", - "duration_minutes": 8.2, - "session": "london", - "base_confidence": 0, - "enhanced_score": 0, - "hybrid_score": 0, - "signal_quality": "unknown", - "equity_curve_multiplier": 1.0, - "is_win": true, - "stop_loss": 0.0, - "take_profit": 0.0, - "close_reason": "manual" - }, - { - "ticket": 642045250, - "symbol": "XAUUSD", - "direction": "LONG", - "entry_price": 4412.44, - "exit_price": 4417.84, - "volume": 0.01, - "profit": 5.4, - "profit_pips": 54.00000000000546, - "entry_time": "2026-01-05T09:00:00", - "exit_time": "2026-01-05T09:14:12", - "duration_minutes": 14.2, - "session": "london", - "base_confidence": 0, - "enhanced_score": 0, - "hybrid_score": 0, - "signal_quality": "unknown", - "equity_curve_multiplier": 1.0, - "is_win": true, - "stop_loss": 0.0, - "take_profit": 0.0, - "close_reason": "manual" - }, - { - "ticket": 642090904, - "symbol": "XAUUSD", - "direction": "LONG", - "entry_price": 4418.53, - "exit_price": 4428.19, - "volume": 0.01, - "profit": 9.66, - "profit_pips": 96.59999999999854, - "entry_time": "2026-01-05T09:15:00", - "exit_time": "2026-01-05T11:16:36", - "duration_minutes": 121.6, - "session": "london", - "base_confidence": 0, - "enhanced_score": 0, - "hybrid_score": 0, - "signal_quality": "unknown", - "equity_curve_multiplier": 1.0, - "is_win": true, - "stop_loss": 0.0, - "take_profit": 0.0, - "close_reason": "manual" - }, - { - "ticket": 643808771, - "symbol": "XAUUSD", - "direction": "LONG", - "entry_price": 4448.54, - "exit_price": 4439.53, - "volume": 0.01, - "profit": -9.01, - "profit_pips": -90.10000000000218, - "entry_time": "2026-01-05T19:00:00", - "exit_time": "2026-01-05T19:08:02", - "duration_minutes": 8.033333333333333, - "session": "ny", - "base_confidence": 0, - "enhanced_score": 0, - "hybrid_score": 0, - "signal_quality": "unknown", - "equity_curve_multiplier": 1.0, - "is_win": false, - "stop_loss": 0.0, - "take_profit": 0.0, - "close_reason": "stop_loss" - }, - { - "ticket": 643847386, - "symbol": "XAUUSD", - "direction": "LONG", - "entry_price": 4441.93, - "exit_price": 4452.33, - "volume": 0.01, - "profit": 10.4, - "profit_pips": 103.99999999999636, - "entry_time": "2026-01-05T19:10:00", - "exit_time": "2026-01-05T19:53:12", - 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"signal_quality": "unknown", - "equity_curve_multiplier": 1.0, - "is_win": false, - "stop_loss": 0.0, - "take_profit": 0.0, - "close_reason": "stop_loss" - }, - { - "ticket": 724767826, - "symbol": "XAUUSD", - "direction": "LONG", - "entry_price": 5520.51, - "exit_price": 5563.63, - "volume": 0.1, - "profit": 431.2, - "profit_pips": 431.1999999999989, - "entry_time": "2026-01-29T08:24:15", - "exit_time": "2026-01-29T08:59:35", - "duration_minutes": 35.333333333333336, - "session": "london", - "base_confidence": 0.0, - "enhanced_score": 0.0, - "hybrid_score": 0.0, - "signal_quality": "unknown", - "equity_curve_multiplier": 1.0, - "is_win": true, - "stop_loss": 0.0, - "take_profit": 0.0, - "close_reason": "take_profit" - } - ], - "errors": [], - "filtered_signals": [], - "stats": { - "total_trades": 348, - "wins": 177, - "losses": 171, - "win_rate": 0.5086206896551724, - "profit_factor": 1.4155026557340906, - "total_profit": 4598.209999999999, - "total_wins": 15664.830000000004, - "total_losses": 11066.62, - "avg_win": 88.50186440677967, - "avg_loss": 64.71707602339181, - "avg_trade": 13.213247126436778, - "max_drawdown": 1.0, - "max_drawdown_dollars": 1972.6499999999999, - "current_equity": 4598.209999999999, - "peak_equity": 4914.209999999999, - "sessions_tested": [ - "asian", - "london", - "ny" - ], - "session_stats": { - "asian": { - "trades": 155, - "wins": 84, - "profit": 3270.77 - }, - "london": { - "trades": 81, - "wins": 38, - "profit": 654.1199999999999 - }, - "ny": { - "trades": 112, - "wins": 55, - "profit": 673.32 - } - }, - "quality_stats": { - "unknown": { - "trades": 348, - "wins": 177, - "profit": 4598.209999999999 - } - }, - "best_trade": 915.6, - "worst_trade": -345.7, - "avg_duration_minutes": 48.97389846743299 - } -} \ No newline at end of file diff --git a/diagnose_detailed.py b/diagnose_detailed.py deleted file mode 100644 index 8217810..0000000 --- a/diagnose_detailed.py +++ /dev/null @@ -1,158 +0,0 @@ -#!/usr/bin/env python3 -""" -Detaillierte Diagnose: Warum keine Trades seit 10. Dezember? -""" - -import sqlite3 -from datetime import datetime - -DB_PATH = "trading_bot.db" - -def detailed_diagnosis(): - print("=" * 80) - print("🔍 DETAILLIERTE DIAGNOSE: KEINE TRADES SEIT 10. DEZEMBER") - print("=" * 80) - - conn = sqlite3.connect(DB_PATH) - cursor = conn.cursor() - - # Timeline - print("\n📅 TIMELINE:") - print("-" * 80) - - cursor.execute(""" - SELECT - DATE(entry_time) as day, - COUNT(*) as trades, - SUM(CASE WHEN net_profit < 0 THEN 1 ELSE 0 END) as losses, - SUM(net_profit) as profit - FROM trades - WHERE entry_time >= '2025-12-01' - GROUP BY DATE(entry_time) - ORDER BY day - """) - - timeline = cursor.fetchall() - for row in timeline: - status = "🔴" if row[2] == row[1] else "🟢" if row[3] > 0 else "🟡" - print(f"{status} {row[0]}: {row[1]:2d} trades ({row[2]:2d} losses) | Profit: {row[3]:7.2f}") - - # What happened - print("\n" + "=" * 80) - print("📊 WAS IST PASSIERT?") - print("=" * 80) - - cursor.execute(""" - SELECT COUNT(*) FROM trades - WHERE entry_time >= '2025-12-01' AND entry_time < '2025-12-10' - AND net_profit < 0 - """) - losses_before_reset = cursor.fetchone()[0] - - cursor.execute(""" - SELECT COUNT(*) FROM trades - WHERE entry_time >= '2025-12-01' AND entry_time < '2025-12-10' - AND exit_reason = 'manual_close' - """) - manual_closes = cursor.fetchone()[0] - - print(f"\n1. DEZEMBER 1-9:") - print(f" - {losses_before_reset} Verlust-Trades") - print(f" - {manual_closes} davon waren 'manual_close'") - print(f" - Alle Trades: -33.90 (exakt gleicher Verlust)") - print(f" ⚠️ DAS IST UNGEWÖHNLICH!") - - print(f"\n2. DEZEMBER 10:") - print(f" - Sie haben 'reset_consecutive_losses.py' ausgeführt") - print(f" - Künstlicher +1.00 Trade erstellt") - print(f" - Consecutive Loss Counter wurde zurückgesetzt") - - print(f"\n3. SEIT DEZEMBER 10:") - print(f" - 🚨 KEINE TRADES MEHR!") - print(f" - Bot läuft angeblich weiter") - print(f" - Aber execute_trade wird nicht ausgelöst") - - # Possible reasons - print("\n" + "=" * 80) - print("🤔 MÖGLICHE URSACHEN") - print("=" * 80) - - print("\n1️⃣ RANGING FILTER (am wahrscheinlichsten)") - print(" - Filter wurde am 9. Dezember hinzugefügt") - print(" - Blockiert Trades wenn ADX < 25") - print(" - Markt könnte seit 10 Tagen im Ranging sein") - print(" ✅ Das wäre NORMAL und GEWOLLT!") - - print("\n2️⃣ SCHEDULER PROBLEM") - print(" - Scheduler läuft nicht") - print(" - adaptive_trading_check() wird nicht aufgerufen") - print(" - Jupyter Kernel ist abgestürzt") - print(" ❌ Das wäre ein FEHLER!") - - print("\n3️⃣ DRAWDOWN PROTECTION BUG") - print(" - Reset hat nicht funktioniert") - print(" - Bot denkt immer noch, Limit ist erreicht") - print(" - Cooldown läuft noch") - print(" ❌ Das wäre ein BUG!") - - print("\n4️⃣ CONFIDENCE/FILTER ZU STRENG") - print(" - Alle Signale unter 70% Confidence") - print(" - ATR zu klein") - print(" - Kein klarer Trend erkannt") - print(" ⚠️ Möglich, aber 10 Tage ist lang!") - - # Action items - print("\n" + "=" * 80) - print("🎯 DIAGNOSESCHRITTE") - print("=" * 80) - - print("\n📋 Bitte führen Sie folgendes im Notebook aus:") - print("\n1. Prüfen Sie ob Scheduler läuft:") - print(" >>> scheduler.get_jobs()") - print(" Erwartung: 5-6 Jobs sichtbar") - print(" Falls LEER → Scheduler ist gestoppt! Neu starten!") - - print("\n2. Prüfen Sie Market Regime:") - print(" >>> show_current_regime()") - print(" Erwartung: Zeigt ob RANGING oder TRENDING") - print(" Falls RANGING + ADX < 25 → Erklärt keine Trades!") - - print("\n3. Prüfen Sie letzte Trading-Check Ausgabe:") - print(" Scrollen Sie im Notebook nach unten") - print(" Suchen Sie nach:") - print(" - '🛑 TRADE BLOCKIERT: Ranging Market!' (gut)") - print(" - '✅ REGIME CHECK PASSED' (sollte Trades auslösen)") - print(" - 'POSITION CHECK' (zeigt dass Funktion läuft)") - - print("\n4. Manueller Test:") - print(" >>> execute_trade_v2_adaptive()") - print(" Führt einen manuellen Trading-Check aus") - print(" Zeigt die GENAUE Blockierungsursache!") - - print("\n5. Prüfen Sie welche Funktion aktiv ist:") - print(" >>> print(execute_trade_v2_adaptive)") - print(" Erwartung: 'execute_trade_v2_adaptive_with_ranging_filter'") - print(" Falls NICHT → Ranging Filter ist nicht aktiv!") - - # Summary - print("\n" + "=" * 80) - print("💡 WAHRSCHEINLICHSTE URSACHE") - print("=" * 80) - - print("\n🎯 RANGING MARKET (70% Wahrscheinlichkeit)") - print(" - Der Filter macht seinen Job!") - print(" - Gold ist seit 10 Tagen im Ranging") - print(" - Bot wartet auf klaren Trend (ADX > 25)") - print(" - DAS IST GUT! Schützt vor Verlusten!") - - print("\n⚠️ 10 Tage ohne Trade ist aber SEHR lang") - print(" → Bitte führen Sie die Diagnoseschritte aus") - print(" → Dann wissen wir, ob es wirklich nur Ranging ist") - print(" → Oder ob ein technisches Problem vorliegt") - - print("\n" + "=" * 80) - - conn.close() - -if __name__ == "__main__": - detailed_diagnosis() diff --git a/dynamic_thresholds.json b/dynamic_thresholds.json deleted file mode 100644 index b35c55f..0000000 --- a/dynamic_thresholds.json +++ /dev/null @@ -1,15 +0,0 @@ -{ - "timestamp": "2026-01-27T00:00:00.107097", - "session_thresholds": { - "asian": 60, - "ny": 60, - "london": 60, - "overlap": 60 - }, - "settings": { - "lookback_trades": 20, - "target_win_rate": 0.6, - "min_threshold": 60, - "max_threshold": 95 - } -} \ No newline at end of file diff --git a/equity_curve_history.json b/equity_curve_history.json deleted file mode 100644 index e378a46..0000000 --- a/equity_curve_history.json +++ /dev/null @@ -1,257 +0,0 @@ -[ - { - "timestamp": "2026-01-26T12:13:46.930465", - "equity": 9022.43, - "trade_count": 1 - }, - { - "timestamp": "2026-01-26T12:19:46.966901", - "equity": 8957.23, - "trade_count": 2 - }, - { - "timestamp": "2026-01-26T13:28:47.062937", - "equity": 9041.93, - "trade_count": 3 - }, - { - "timestamp": "2026-01-26T13:42:46.844143", - "equity": 8972.23, - "trade_count": 4 - }, - { - "timestamp": "2026-01-26T14:02:47.503834", - "equity": 8896.53, - "trade_count": 5 - }, - { - "timestamp": "2026-01-26T14:19:46.495217", - "equity": 8945.63, - "trade_count": 6 - }, - { - "timestamp": "2026-01-26T14:23:47.782515", - "equity": 8863.63, - "trade_count": 7 - }, - { - "timestamp": "2026-01-26T14:30:47.450110", - "equity": 8775.53, - "trade_count": 8 - }, - { - "timestamp": "2026-01-26T14:57:47.581206", - "equity": 8829.93, - "trade_count": 9 - }, - { - "timestamp": "2026-01-26T15:43:47.029833", - "equity": 8956.33, - "trade_count": 10 - }, - { - "timestamp": "2026-01-26T16:01:47.190356", - "equity": 9035.33, - "trade_count": 11 - }, - { - "timestamp": "2026-01-26T16:16:50.346575", - "equity": 9058.73, - "trade_count": 12 - }, - { - "timestamp": "2026-01-26T16:35:47.053141", - "equity": 8938.53, - "trade_count": 13 - }, - { - "timestamp": "2026-01-26T17:20:48.048421", - "equity": 9083.63, - "trade_count": 14 - }, - { - "timestamp": "2026-01-26T17:28:50.189681", - "equity": 8968.73, - "trade_count": 15 - }, - { - "timestamp": "2026-01-26T17:39:47.578487", - "equity": 8860.43, - "trade_count": 16 - }, - { - "timestamp": "2026-01-26T18:25:28.537885", - "equity": 9031.93, - "trade_count": 17 - }, - { - "timestamp": "2026-01-26T19:07:29.047627", - "equity": 9105.43, - "trade_count": 18 - }, - { - "timestamp": "2026-01-26T19:12:28.985632", - "equity": 9000.29, - "trade_count": 19 - }, - { - "timestamp": "2026-01-26T19:36:28.604004", - "equity": 8894.25, - "trade_count": 20 - }, - { - "timestamp": "2026-01-26T19:41:28.577100", - "equity": 8831.2, - "trade_count": 21 - }, - { - "timestamp": "2026-01-26T19:58:27.699220", - "equity": 8866.25, - "trade_count": 22 - }, - { - "timestamp": "2026-01-26T20:02:28.281716", - "equity": 8798.45, - "trade_count": 23 - }, - { - "timestamp": "2026-01-26T20:11:30.929472", - "equity": 8821.55, - "trade_count": 24 - }, - { - "timestamp": "2026-01-26T20:21:28.550560", - "equity": 8735.3, - "trade_count": 25 - }, - { - "timestamp": "2026-01-26T20:48:32.186217", - "equity": 8640.1, - "trade_count": 26 - }, - { - "timestamp": "2026-01-26T21:33:27.589864", - "equity": 8891.2, - "trade_count": 27 - }, - { - "timestamp": "2026-01-26T21:37:29.173485", - "equity": 8740.18, - "trade_count": 28 - }, - { - "timestamp": "2026-01-26T22:10:27.827652", - "equity": 8759.33, - "trade_count": 29 - }, - { - "timestamp": "2026-01-26T22:16:28.542996", - "equity": 8683.68, - "trade_count": 30 - }, - { - "timestamp": "2026-01-26T22:23:29.348033", - "equity": 8595.38, - "trade_count": 31 - }, - { - "timestamp": "2026-01-26T22:36:27.686118", - "equity": 8501.08, - "trade_count": 32 - }, - { - "timestamp": "2026-01-27T00:09:28.170412", - "equity": 8726.46, - "trade_count": 33 - }, - { - "timestamp": "2026-01-27T00:59:27.666816", - "equity": 8820.68, - "trade_count": 34 - }, - { - "timestamp": "2026-01-27T01:43:27.684421", - "equity": 8681.88, - "trade_count": 35 - }, - { - "timestamp": "2026-01-27T01:51:29.464065", - "equity": 8617.73, - "trade_count": 36 - }, - { - "timestamp": "2026-01-27T02:00:31.411314", - "equity": 8671.03, - "trade_count": 37 - }, - { - "timestamp": "2026-01-27T02:12:28.296523", - "equity": 8817.38, - "trade_count": 38 - }, - { - "timestamp": "2026-01-27T02:33:27.507351", - "equity": 8851.98, - "trade_count": 39 - }, - { - "timestamp": "2026-01-27T03:55:28.891918", - "equity": 8881.98, - "trade_count": 40 - }, - { - "timestamp": "2026-01-27T05:11:28.289256", - "equity": 8908.88, - "trade_count": 41 - }, - { - "timestamp": "2026-01-27T05:42:28.758925", - "equity": 8821.98, - "trade_count": 42 - }, - { - "timestamp": "2026-01-27T06:02:29.934062", - "equity": 8853.28, - "trade_count": 43 - }, - { - "timestamp": "2026-01-27T06:48:27.496834", - "equity": 9047.68, - "trade_count": 44 - }, - { - "timestamp": "2026-01-27T07:56:27.536971", - "equity": 9096.08, - "trade_count": 45 - }, - { - "timestamp": "2026-01-27T08:13:28.986584", - "equity": 9132.98, - "trade_count": 46 - }, - { - "timestamp": "2026-01-27T08:45:27.690803", - "equity": 9193.48, - "trade_count": 47 - }, - { - "timestamp": "2026-01-27T09:00:28.478655", - "equity": 9088.98, - "trade_count": 48 - }, - { - "timestamp": "2026-01-27T09:29:27.489522", - "equity": 9005.74, - "trade_count": 49 - }, - { - "timestamp": "2026-01-27T09:52:30.080743", - "equity": 9028.68, - "trade_count": 50 - }, - { - "timestamp": "2026-01-27T10:46:29.927974", - "equity": 9076.28, - "trade_count": 51 - } -] \ No newline at end of file diff --git a/fix_indentation_error.py b/fix_indentation_error.py deleted file mode 100644 index c91ac97..0000000 --- a/fix_indentation_error.py +++ /dev/null @@ -1,112 +0,0 @@ -#!/usr/bin/env python3 -""" -🔧 Fix Indentation Error in Patched Notebook -""" - -import json -import sys - -NOTEBOOK_PATH = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -def fix_notebook(): - """Fix the indentation error in execute_trade function""" - - print("=" * 70) - print("🔧 FIXING INDENTATION ERROR") - print("=" * 70) - - # Load notebook - print(f"\n1️⃣ Loading notebook: {NOTEBOOK_PATH}") - - try: - with open(NOTEBOOK_PATH, 'r', encoding='utf-8') as f: - notebook = json.load(f) - except FileNotFoundError: - print(f"❌ Error: Notebook not found: {NOTEBOOK_PATH}") - return False - - print(f"✅ Loaded {len(notebook['cells'])} cells") - - # Find execute_trade cell - print("\n2️⃣ Finding execute_trade cell...") - - execute_cell_index = None - for i, cell in enumerate(notebook['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell['source']) - if 'def execute_trade_v2_adaptive(' in source: - execute_cell_index = i - print(f"✅ Found at cell {i}") - break - - if execute_cell_index is None: - print("❌ Error: Could not find execute_trade cell!") - return False - - # Get the cell - execute_cell = notebook['cells'][execute_cell_index] - source_lines = execute_cell['source'] - - # Find the problematic section and fix it - print("\n3️⃣ Fixing indentation...") - - fixed_lines = [] - i = 0 - while i < len(source_lines): - line = source_lines[i] - - # Find the adaptive sizing section - if "# 🎯 ADAPTIVE POSITION SIZING" in line: - # Replace entire section with correct indentation - fixed_lines.append(line) - i += 1 - - # Add correctly indented code - fixed_lines.append(" if 'adv_position_mgr' in globals() and adv_position_mgr.adaptive_sizing:\n") - fixed_lines.append(" volume = adv_position_mgr.adaptive_sizing.calculate_position_size(\n") - fixed_lines.append(" confidence=confidence,\n") - fixed_lines.append(" balance=balance,\n") - fixed_lines.append(" stop_loss_distance=adjusted_atr_mult * atr * 10000, # Convert to pips\n") - fixed_lines.append(" symbol=symbol\n") - fixed_lines.append(" )\n") - fixed_lines.append(" else:\n") - fixed_lines.append(" volume = round(min(0.1, max(0.01, risk_amount / (adjusted_atr_mult * atr * 100))),2)\n") - - # Skip old lines until we find the next non-indented or different section - while i < len(source_lines): - next_line = source_lines[i] - if next_line.strip() and not next_line.startswith(' '): - break - if 'volume = round(min(0.1' in next_line and 'adaptive' not in source_lines[i-1]: - i += 1 - break - i += 1 - continue - - fixed_lines.append(line) - i += 1 - - # Update cell - execute_cell['source'] = fixed_lines - - print("✅ Indentation fixed") - - # Save - print(f"\n4️⃣ Saving fixed notebook...") - - with open(NOTEBOOK_PATH, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - - print("✅ Notebook saved!") - - print("\n" + "=" * 70) - print("✅ FIX COMPLETE!") - print("=" * 70) - print("\nNext: Restart Jupyter Kernel and Run All") - - return True - - -if __name__ == "__main__": - success = fix_notebook() - sys.exit(0 if success else 1) diff --git a/fix_scheduler_conflict.py b/fix_scheduler_conflict.py deleted file mode 100644 index d54565f..0000000 --- a/fix_scheduler_conflict.py +++ /dev/null @@ -1,66 +0,0 @@ -#!/usr/bin/env python3 -""" -Quick Fix: Scheduler ConflictingIdError -Fügt replace_existing=True zu allen scheduler.add_job() Calls hinzu -""" - -import json -import sys - -NOTEBOOK_PATH = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -def fix_scheduler_conflicts(): - print("🔧 Fixing Scheduler ConflictingIdError...") - - with open(NOTEBOOK_PATH, 'r', encoding='utf-8') as f: - nb = json.load(f) - - # Find all scheduler cells - fixed_count = 0 - for i, cell in enumerate(nb['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell['source']) - - # Check if this cell has scheduler.add_job without replace_existing - if 'scheduler.add_job' in source and 'replace_existing' not in source: - print(f" Cell {i}: Adding replace_existing=True") - - # Replace all scheduler.add_job calls - lines = cell['source'] - new_lines = [] - in_add_job = False - - for line in lines: - if 'scheduler.add_job(' in line: - in_add_job = True - - new_lines.append(line) - - # If we're in add_job and find the id= parameter, add replace_existing after it - if in_add_job and "id=" in line and "replace_existing" not in line: - # Get indentation from current line - indent = len(line) - len(line.lstrip()) - # Add replace_existing=True on next line - new_lines.append(" " * indent + "replace_existing=True,\n") - - if in_add_job and ')' in line and 'scheduler.add_job' not in line: - in_add_job = False - - cell['source'] = new_lines - fixed_count += 1 - - if fixed_count > 0: - # Save - with open(NOTEBOOK_PATH, 'w', encoding='utf-8') as f: - json.dump(nb, f, indent=1, ensure_ascii=False) - - print(f"✅ Fixed {fixed_count} scheduler calls") - print("\nNext: Restart Jupyter Kernel") - return True - else: - print("⚠️ No scheduler conflicts found to fix") - return False - -if __name__ == "__main__": - success = fix_scheduler_conflicts() - sys.exit(0 if success else 1) diff --git a/fix_telegram_in_notebook.py b/fix_telegram_in_notebook.py deleted file mode 100644 index 9f67b12..0000000 --- a/fix_telegram_in_notebook.py +++ /dev/null @@ -1,76 +0,0 @@ -#!/usr/bin/env python3 -""" -Fügt Telegram Dependencies Installation Cell ins Notebook hinzu -""" - -import json - -notebook_path = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -print(f"📖 Loading notebook: {notebook_path}") -with open(notebook_path, 'r', encoding='utf-8') as f: - notebook = json.load(f) - -# Find Cell 28 (Telegram Bot Commander) -# We need to insert a dependency installation cell BEFORE it - -# Create new cell for dependency installation (will be Cell 27.5) -dependency_cell = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# INSTALL TELEGRAM BOT DEPENDENCIES\n", - "# ==========================================\n", - "\n", - "import sys\n", - "import subprocess\n", - "\n", - "print(\"📦 Installing python-telegram-bot...\")\n", - "\n", - "try:\n", - " # Install or upgrade python-telegram-bot\n", - " subprocess.check_call([\n", - " sys.executable, \"-m\", \"pip\", \"install\", \n", - " \"python-telegram-bot\", \"--upgrade\", \"--quiet\"\n", - " ])\n", - " print(\"✅ python-telegram-bot installed successfully!\")\n", - " \n", - " # Verify\n", - " import telegram\n", - " print(f\"✅ telegram module version: {telegram.__version__}\")\n", - " \n", - "except Exception as e:\n", - " print(f\"❌ Installation failed: {e}\")\n", - " print(\"\\n⚠️ Please run manually:\")\n", - " print(\" pip install python-telegram-bot --upgrade\")\n" - ] -} - -# Insert at position 27 (before the markdown info cell) -insert_position = 27 - -print(f"📝 Inserting dependency installation cell at position {insert_position}...") -notebook['cells'].insert(insert_position, dependency_cell) - -# Update cell count -new_total = len(notebook['cells']) -print(f"✅ New total cells: {new_total}") - -# Save notebook -print(f"💾 Saving notebook...") -with open(notebook_path, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - -print("✅ Notebook updated successfully!") -print(f"\n🎯 NEW CELL STRUCTURE:") -print(f" Cell 27: Dependency Installation (NEW)") -print(f" Cell 28: Telegram Bot Info (Markdown)") -print(f" Cell 29: Telegram Bot Commander (Code)") -print(f" Cell 30: execute_trade Integration (Code)") -print(f"\n📋 INSTRUCTIONS:") -print(f" 1. Run Cell 27 FIRST (install dependencies)") -print(f" 2. Then run Cell 29 (Telegram Bot Commander)") -print(f" 3. Then run Cell 30 (Integration)") diff --git a/install_telegram_cell_code.txt b/install_telegram_cell_code.txt deleted file mode 100644 index 122f467..0000000 --- a/install_telegram_cell_code.txt +++ /dev/null @@ -1,20 +0,0 @@ -# ========================================== -# INSTALL TELEGRAM DEPENDENCIES (Run FIRST!) -# ========================================== - -import sys -import subprocess - -print("📦 Installing python-telegram-bot...") - -subprocess.check_call([ - sys.executable, "-m", "pip", "install", - "python-telegram-bot", "--upgrade" -]) - -print("\n✅ python-telegram-bot installed!") - -# Verify -import telegram -print(f"✅ Version: {telegram.__version__}") -print(f"\n🎯 Now restart kernel and run Cell 17 again!") diff --git a/install_telegram_dependencies.py b/install_telegram_dependencies.py deleted file mode 100644 index 15d7959..0000000 --- a/install_telegram_dependencies.py +++ /dev/null @@ -1,41 +0,0 @@ -#!/usr/bin/env python3 -""" -Quick installer for telegram dependencies in notebook environment -""" - -import subprocess -import sys - -print("="*70) -print("📦 Installing Telegram Dependencies for Notebook") -print("="*70) - -# Install python-telegram-bot -print("\n📥 Installing python-telegram-bot...") -try: - subprocess.check_call([ - sys.executable, "-m", "pip", "install", - "python-telegram-bot==13.15", - "--upgrade" - ]) - print("✅ python-telegram-bot installed successfully!") -except Exception as e: - print(f"❌ Installation failed: {e}") - sys.exit(1) - -# Verify installation -print("\n🧪 Verifying installation...") -try: - import telegram - from telegram import Bot - from telegram.ext import Updater - print(f"✅ telegram module imported successfully!") - print(f" Version: {telegram.__version__}") -except Exception as e: - print(f"❌ Verification failed: {e}") - sys.exit(1) - -print("\n" + "="*70) -print("✅ ALL DEPENDENCIES INSTALLED!") -print("="*70) -print("\n📝 Next step: Run Cell 28 in your notebook again") diff --git a/integrate_optimizations.py b/integrate_optimizations.py deleted file mode 100644 index 117e7b0..0000000 --- a/integrate_optimizations.py +++ /dev/null @@ -1,426 +0,0 @@ -#!/usr/bin/env python3 -""" -Integriert alle 3 Optimizations in das Notebook -""" - -import json - -notebook_path = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -print("=" * 70) -print("🚀 INTEGRATING OPTION E: ALL 3 OPTIMIZATIONS") -print("=" * 70) -print() - -# Load notebook -with open(notebook_path, 'r', encoding='utf-8') as f: - notebook = json.load(f) - -print(f"Current cells: {len(notebook['cells'])}") -print() - -# ========================================== -# CELL 1: MARKDOWN - OPTIMIZATION SECTION -# ========================================== - -markdown_cell_1 = { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "\n", - "## 🚀 ADVANCED OPTIMIZATIONS (V1.8)\n", - "\n", - "**Implementiert:** 2026-01-16\n", - "\n", - "### Features:\n", - "1. **Dynamic Threshold Optimizer** - Selbst-optimierender Confidence Threshold\n", - "2. **Enhanced Signal Scoring** - Multi-Faktor Analyse (Volume, RSI/MACD, S/R, Fib)\n", - "3. **Enhanced Trailing Stop** - Multi-tier Profit Protection\n", - "\n", - "**Expected Improvements:**\n", - "- Win Rate: +15-20%\n", - "- Profit: +50-80%\n", - "- \"Give-Back\" reduziert: -30%\n", - "\n", - "---" - ] -} - -# ========================================== -# CELL 2: CODE - SETUP ALL MODULES -# ========================================== - -code_cell_1 = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# ADVANCED OPTIMIZATION SETUP (V1.8)\n", - "# ==========================================\n", - "\n", - "from dynamic_threshold_optimizer import DynamicThresholdOptimizer, auto_optimize_thresholds\n", - "from enhanced_signal_scoring import EnhancedSignalScorer\n", - "from enhanced_trailing_stop import EnhancedTrailingStopManager, create_enhanced_position_monitor\n", - "\n", - "print(\"🚀 INITIALIZING ADVANCED OPTIMIZATIONS...\")\n", - "print(\"=\" * 70)\n", - "print()\n", - "\n", - "# 1. Dynamic Threshold Optimizer\n", - "threshold_optimizer = DynamicThresholdOptimizer(\n", - " db_path=\"trading_bot.db\",\n", - " lookback_trades=20, # Letzte 20 Trades analysieren\n", - " target_win_rate=0.60, # 60% Ziel Win Rate\n", - " min_threshold=60, # Minimum 60% Confidence\n", - " max_threshold=95, # Maximum 95% Confidence\n", - " adjustment_step=5 # 5% Schritte\n", - ")\n", - "print(\"✅ Dynamic Threshold Optimizer initialized\")\n", - "\n", - "# 2. Enhanced Signal Scorer\n", - "signal_scorer = EnhancedSignalScorer(\n", - " weights={\n", - " 'trend': 0.30, # Existing Trend System\n", - " 'volume': 0.20, # Volume Analysis\n", - " 'momentum': 0.20, # RSI + MACD\n", - " 'support_resistance': 0.15, # S/R Levels\n", - " 'fibonacci': 0.15 # Fibonacci Levels\n", - " }\n", - ")\n", - "print(\"✅ Enhanced Signal Scorer initialized\")\n", - "\n", - "# 3. Enhanced Trailing Stop\n", - "enhanced_trailing = EnhancedTrailingStopManager(\n", - " # Early Breakeven\n", - " breakeven_trigger_pct=0.30, # Bei 30% zu TP (früher!)\n", - " breakeven_buffer_pips=5, # +5 Pips über BE\n", - " \n", - " # Multi-tier Profit Locking\n", - " tier1_trigger=0.50, # Bei 50% → Lock 25%\n", - " tier1_lock_pct=0.25,\n", - " tier2_trigger=0.75, # Bei 75% → Lock 50%\n", - " tier2_lock_pct=0.50,\n", - " tier3_trigger=0.90, # Bei 90% → Lock 75%\n", - " tier3_lock_pct=0.75,\n", - " \n", - " # ATR-based Trailing\n", - " use_atr_trailing=True,\n", - " atr_multiplier=1.0,\n", - " \n", - " # Time-based Breakeven\n", - " time_based_breakeven=True,\n", - " hours_to_breakeven=4.0, # Auto-BE nach 4h\n", - " \n", - " # Session-aware Multipliers\n", - " session_trailing_multipliers={\n", - " 'asian': 1.0, # Standard\n", - " 'ny': 1.5, # Größer (mehr Volatilität)\n", - " 'london': 1.2,\n", - " 'overlap': 1.3\n", - " }\n", - ")\n", - "print(\"✅ Enhanced Trailing Stop Manager initialized\")\n", - "print()\n", - "\n", - "# 4. Run initial threshold optimization\n", - "print(\"🔄 Running initial threshold optimization...\")\n", - "try:\n", - " results = auto_optimize_thresholds(threshold_optimizer, apply_changes=True)\n", - "except Exception as e:\n", - " print(f\"⚠️ Optimization skipped (not enough data): {e}\")\n", - " print(\" Will use default thresholds until 20+ trades collected\")\n", - "print()\n", - "\n", - "print(\"=\" * 70)\n", - "print(\"🎯 ALL ADVANCED OPTIMIZATIONS ACTIVE!\")\n", - "print(\"=\" * 70)\n", - "print()\n", - "print(\"📊 Summary:\")\n", - "print(\" • Dynamic Thresholds: ✅ (auto-adjusts daily)\")\n", - "print(\" • Enhanced Scoring: ✅ (5-factor analysis)\")\n", - "print(\" • Enhanced Trailing: ✅ (multi-tier protection)\")\n", - "print()\n", - "print(\"💡 Tip: Use 'threshold_optimizer.generate_report()' for details\")" - ] -} - -# ========================================== -# CELL 3: CODE - UPDATE SCHEDULER -# ========================================== - -code_cell_2 = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# UPDATE SCHEDULER WITH OPTIMIZATIONS\n", - "# ==========================================\n", - "\n", - "print(\"🔄 Updating scheduler with advanced optimizations...\")\n", - "print()\n", - "\n", - "# 1. Add Daily Threshold Optimization (midnight UTC)\n", - "try:\n", - " scheduler.remove_job('threshold_optimization')\n", - "except:\n", - " pass\n", - "\n", - "scheduler.add_job(\n", - " func=lambda: auto_optimize_thresholds(threshold_optimizer, apply_changes=True),\n", - " trigger='cron',\n", - " hour=0, # Midnight UTC\n", - " id='threshold_optimization'\n", - ")\n", - "print(\"✅ Threshold optimization scheduled (daily at 00:00 UTC)\")\n", - "\n", - "# 2. Replace old trailing stop with enhanced version\n", - "try:\n", - " scheduler.remove_job('advanced_position_management')\n", - " print(\" Removed old trailing stop\")\n", - "except:\n", - " pass\n", - "\n", - "# Create enhanced monitor\n", - "enhanced_monitor = create_enhanced_position_monitor(\n", - " enhanced_trailing,\n", - " rhythm_manager,\n", - " symbol=\"XAUUSD\"\n", - ")\n", - "\n", - "scheduler.add_job(\n", - " func=enhanced_monitor,\n", - " trigger='interval',\n", - " minutes=1,\n", - " id='enhanced_trailing_stop'\n", - ")\n", - "print(\"✅ Enhanced trailing stop scheduled (every 1 min)\")\n", - "print()\n", - "\n", - "# Print all active jobs\n", - "print(\"📋 Active Scheduler Jobs:\")\n", - "for job in scheduler.get_jobs():\n", - " print(f\" • {job.id}: {job.trigger}\")\n", - "print()\n", - "print(\"✅ Scheduler updated successfully!\")" - ] -} - -# ========================================== -# CELL 4: MARKDOWN - USAGE INSTRUCTIONS -# ========================================== - -markdown_cell_2 = { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 📊 How to Use Optimizations\n", - "\n", - "#### 1. Generate Threshold Optimization Report\n", - "```python\n", - "print(threshold_optimizer.generate_report())\n", - "```\n", - "\n", - "#### 2. Test Enhanced Signal Scoring\n", - "```python\n", - "signal_info = extended_top_down_v2_adaptive(\"XAUUSD\")\n", - "price = signal_info['trend_info']['M5']['price']\n", - "\n", - "enhanced = signal_scorer.calculate_enhanced_score(\n", - " symbol=\"XAUUSD\",\n", - " base_confidence=signal_info['confidence'],\n", - " trend_direction=signal_info['entry_signal'],\n", - " current_price=price\n", - ")\n", - "\n", - "print(f\"Base: {signal_info['confidence']:.1f}% → Enhanced: {enhanced.total_score:.1f}%\")\n", - "print(f\"Quality: {enhanced.signal_quality.upper()}\")\n", - "```\n", - "\n", - "#### 3. Check Trailing Stop Status\n", - "```python\n", - "positions = mt.positions_get(symbol=\"XAUUSD\")\n", - "for pos in positions:\n", - " print(f\"Position #{pos.ticket}:\")\n", - " print(f\" Tier: {enhanced_trailing.position_tiers.get(pos.ticket, 0)}\")\n", - " print(f\" Entry: {pos.price_open:.2f}\")\n", - " print(f\" Current SL: {pos.sl:.2f}\")\n", - "```\n", - "\n", - "---" - ] -} - -# ========================================== -# CELL 5: CODE - TEST CELLS -# ========================================== - -test_cell_1 = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# TEST: Threshold Optimization Report\n", - "# ==========================================\n", - "\n", - "print(threshold_optimizer.generate_report())" - ] -} - -test_cell_2 = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# TEST: Enhanced Signal Scoring\n", - "# ==========================================\n", - "\n", - "symbol = \"XAUUSD\"\n", - "\n", - "# Get base signal\n", - "signal_info = extended_top_down_v2_adaptive(symbol)\n", - "\n", - "if signal_info:\n", - " price = signal_info['trend_info']['M5']['price']\n", - " \n", - " # Calculate enhanced score\n", - " enhanced = signal_scorer.calculate_enhanced_score(\n", - " symbol=symbol,\n", - " base_confidence=signal_info['confidence'],\n", - " trend_direction=signal_info['entry_signal'],\n", - " current_price=price\n", - " )\n", - " \n", - " print(\"🎯 ENHANCED SIGNAL TEST\")\n", - " print(\"=\" * 50)\n", - " print(f\"Base Confidence: {signal_info['confidence']:.1f}%\")\n", - " print(f\"Enhanced Score: {enhanced.total_score:.1f}%\")\n", - " print(f\"Signal Quality: {enhanced.signal_quality.upper()}\")\n", - " print(f\"Direction: {'LONG' if enhanced.direction == 1 else 'SHORT' if enhanced.direction == -1 else 'NONE'}\")\n", - " print()\n", - " print(\"📊 Component Breakdown:\")\n", - " print(f\" Trend: {enhanced.trend_score:.1f}/100\")\n", - " print(f\" Volume: {enhanced.volume_score:.1f}/100\")\n", - " print(f\" Momentum: {enhanced.momentum_score:.1f}/100\")\n", - " print(f\" S/R: {enhanced.support_resistance_score:.1f}/100\")\n", - " print(f\" Fibonacci: {enhanced.fibonacci_score:.1f}/100\")\n", - " print()\n", - " print(f\"💡 Reason: {enhanced.reason}\")\n", - "else:\n", - " print(\"❌ No signal available for testing\")" - ] -} - -test_cell_3 = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": [ - "# ==========================================\n", - "# TEST: Enhanced Trailing Stop Status\n", - "# ==========================================\n", - "\n", - "positions = mt.positions_get(symbol=\"XAUUSD\")\n", - "\n", - "if positions:\n", - " print(\"📈 ENHANCED TRAILING STOP STATUS\")\n", - " print(\"=\" * 50)\n", - " \n", - " for pos in positions:\n", - " tier = enhanced_trailing.position_tiers.get(pos.ticket, 0)\n", - " \n", - " # Calculate profit\n", - " if pos.type == 0: # BUY\n", - " profit_pips = (mt.symbol_info_tick(pos.symbol).bid - pos.price_open) / mt.symbol_info(pos.symbol).point\n", - " else: # SELL\n", - " profit_pips = (pos.price_open - mt.symbol_info_tick(pos.symbol).ask) / mt.symbol_info(pos.symbol).point\n", - " \n", - " # Calculate progress to TP\n", - " if pos.type == 0:\n", - " tp_distance = pos.tp - pos.price_open\n", - " current_distance = mt.symbol_info_tick(pos.symbol).bid - pos.price_open\n", - " else:\n", - " tp_distance = pos.price_open - pos.tp\n", - " current_distance = pos.price_open - mt.symbol_info_tick(pos.symbol).ask\n", - " \n", - " progress = (current_distance / tp_distance * 100) if tp_distance > 0 else 0\n", - " \n", - " print(f\"\\nPosition #{pos.ticket}:\")\n", - " print(f\" Type: {'LONG' if pos.type == 0 else 'SHORT'}\")\n", - " print(f\" Entry: {pos.price_open:.2f}\")\n", - " print(f\" Current SL: {pos.sl:.2f}\")\n", - " print(f\" TP: {pos.tp:.2f}\")\n", - " print(f\" Profit: {pos.profit:.2f} USD ({profit_pips:.1f} pips)\")\n", - " print(f\" Progress: {progress:.1f}%\")\n", - " print(f\" Tier: {tier}/3\")\n", - " \n", - " # Next tier info\n", - " if tier == 0:\n", - " print(f\" Next: Breakeven @ 30%\")\n", - " elif tier == 0 and progress >= 30:\n", - " print(f\" Next: Tier 1 @ 50%\")\n", - " elif tier == 1:\n", - " print(f\" Next: Tier 2 @ 75%\")\n", - " elif tier == 2:\n", - " print(f\" Next: Tier 3 @ 90%\")\n", - " else:\n", - " print(f\" Status: Max protection active!\")\n", - "else:\n", - " print(\"📭 No open positions\")" - ] -} - -# ========================================== -# INSERT CELLS -# ========================================== - -# Insert position: Before the last empty cells (position 76) -insert_pos = 76 - -print(f"Inserting cells at position {insert_pos}...") - -cells_to_insert = [ - markdown_cell_1, - code_cell_1, - code_cell_2, - markdown_cell_2, - test_cell_1, - test_cell_2, - test_cell_3 -] - -for i, cell in enumerate(cells_to_insert): - notebook['cells'].insert(insert_pos + i, cell) - print(f" ✅ Inserted cell {insert_pos + i}") - -print() -print(f"Total cells now: {len(notebook['cells'])}") -print() - -# Save notebook -with open(notebook_path, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - -print("✅ Notebook saved successfully!") -print() -print("=" * 70) -print("🎯 INTEGRATION COMPLETE!") -print("=" * 70) -print() -print("📋 NEXT STEPS:") -print(" 1. Open Jupyter Notebook") -print(" 2. Kernel → Restart & Clear Output") -print(" 3. Run All Cells") -print(" 4. Check new cells at position 76-82") -print(" 5. Run test cells to verify") -print() -print("=" * 70) diff --git a/integrate_pnl_tracker.py b/integrate_pnl_tracker.py deleted file mode 100644 index 97ba52d..0000000 --- a/integrate_pnl_tracker.py +++ /dev/null @@ -1,306 +0,0 @@ -#!/usr/bin/env python3 -""" -Integration Script: Add P&L Tracking to Notebook -Adds 6 new cells for comprehensive P&L tracking and dashboard -""" - -import nbformat -from pathlib import Path -import sys - -def integrate_pnl_tracker(notebook_path): - """Add P&L tracking cells to notebook""" - - # Read notebook - with open(notebook_path, 'r', encoding='utf-8') as f: - nb = nbformat.read(f, as_version=4) - - print(f"📖 Loaded notebook: {Path(notebook_path).name}") - print(f" Current cells: {len(nb.cells)}") - - # Define new cells - new_cells = [] - - # ========================================== - # Cell 1: Section Header (Markdown) - # ========================================== - new_cells.append(nbformat.v4.new_markdown_cell("""# 💰 P&L TRACKING & PERFORMANCE ANALYTICS (V1.9) - -**Automatic MT5 History Import & Real-Time P&L Dashboard** - -Features: -- 📥 **Automatic MT5 History Import** - Syncs closed trades from MT5 -- 💰 **Real P&L Calculation** - Matches Entry+Exit deals for accurate P&L -- 📊 **Win Rate Analysis** - Real Win Rate from closed MT5 trades -- 📈 **Performance Metrics** - Profit Factor, Max Drawdown, Avg Win/Loss -- 🎯 **Session Analysis** - Compare Asian vs NY performance -- 📅 **Time-based Reports** - Today, Week, Month, All-Time -- 🔄 **Automatic Sync** - Scheduled hourly updates - -**Status:** ✅ READY TO USE -""")) - - # ========================================== - # Cell 2: Setup P&L Tracker (Code) - # ========================================== - new_cells.append(nbformat.v4.new_code_cell("""# ========================================== -# SETUP P&L TRACKER -# ========================================== - -from mt5_pnl_tracker import MT5PnLTracker, scheduled_pnl_sync - -print("=" * 80) -print("🚀 INITIALIZING P&L TRACKER...") -print("=" * 80) - -# Initialize tracker -pnl_tracker = MT5PnLTracker( - db_path="trading_bot.db", - magic_number=None # None = all trades, or specify your EA magic number -) - -# Connect to database -pnl_tracker.connect_db() - -print("\\n✅ P&L Tracker initialized successfully!") -print(" Database: trading_bot.db") -print(" Tables: mt5_deals, matched_positions, pnl_summary") -print("=" * 80) -""")) - - # ========================================== - # Cell 3: Initial Sync (Code) - # ========================================== - new_cells.append(nbformat.v4.new_code_cell("""# ========================================== -# INITIAL SYNC: IMPORT MT5 HISTORY -# ========================================== - -print("\\n📥 Importing MT5 history...") -print(" This will import last 30 days of trades from MT5") -print(" Please wait...\\n") - -# Perform initial sync -sync_results = pnl_tracker.sync_and_update(days_back=30) - -if sync_results['success']: - summary = sync_results['summary'] - - print("=" * 80) - print("✅ SYNC SUCCESSFUL!") - print("=" * 80) - print(f"\\n📥 Import Results:") - print(f" New Deals: {summary['new_deals']}") - print(f" Matched Positions: {summary['matched_positions']}") - print(f"\\n📊 Current Performance:") - print(f" Total Trades: {summary['total_trades']}") - print(f" Win Rate: {summary['win_rate']:.1f}%") - print(f" Net P&L: ${summary['net_profit']:.2f}") - print("=" * 80) - - if summary['new_deals'] == 0: - print("\\n💡 No new deals found. This means:") - print(" • History already imported, OR") - print(" • No trades in last 30 days") -else: - print("=" * 80) - print("❌ SYNC FAILED") - print("=" * 80) - print(f"Error: {sync_results.get('error', 'Unknown error')}") - print("\\n💡 Troubleshooting:") - print(" • Check MT5 is running") - print(" • Verify MT5 connection") - print(" • Check trading history exists") -""")) - - # ========================================== - # Cell 4: Add to Scheduler (Code) - # ========================================== - new_cells.append(nbformat.v4.new_code_cell("""# ========================================== -# ADD P&L SYNC TO SCHEDULER -# ========================================== - -from apscheduler.triggers.interval import IntervalTrigger - -print("\\n🔄 Adding P&L sync to scheduler...") - -# Remove old job if exists -try: - scheduler.remove_job('pnl_sync') - print(" Removed old P&L sync job") -except: - pass - -# Add hourly P&L sync -scheduler.add_job( - scheduled_pnl_sync, - trigger=IntervalTrigger(hours=1), - args=[pnl_tracker, 7], # Sync last 7 days - id='pnl_sync', - name='P&L Sync', - replace_existing=True, - max_instances=1 -) - -print("✅ P&L sync scheduled (every 1 hour)") -print(" Syncs last 7 days from MT5") - -# Show all scheduler jobs -print("\\n📋 Active Scheduler Jobs:") -for job in scheduler.get_jobs(): - print(f" • {job.id}: {job.trigger}") - -print("\\n✅ Scheduler updated successfully!") -print("=" * 80) -""")) - - # ========================================== - # Cell 5: Markdown - Usage Instructions - # ========================================== - new_cells.append(nbformat.v4.new_markdown_cell("""## 📖 How to Use P&L Tracker - -### 📊 View Dashboard -Run the dashboard cell to see: -- All-time performance -- Monthly performance -- Weekly performance -- Today's performance - -### 📜 View Recent Trades -See last 10 closed trades with: -- Entry/Exit prices -- P&L per trade -- Duration -- Win/Loss status - -### 🔄 Manual Sync -If you want to manually sync MT5 history: -```python -sync_results = pnl_tracker.sync_and_update(days_back=30) -print(sync_results) -``` - -### 📊 Get Specific Period Metrics -```python -# Get metrics for specific period -all_time = pnl_tracker.calculate_pnl_metrics('all') -month = pnl_tracker.calculate_pnl_metrics('month') -week = pnl_tracker.calculate_pnl_metrics('week') -today = pnl_tracker.calculate_pnl_metrics('today') -``` - -### 🎯 Integration with Dynamic Thresholds -The P&L tracker data can be used by the Dynamic Threshold Optimizer to better calibrate optimal confidence thresholds based on real MT5 performance! -""")) - - # ========================================== - # Cell 6: Dashboard Display (Code) - # ========================================== - new_cells.append(nbformat.v4.new_code_cell("""# ========================================== -# 💰 P&L PERFORMANCE DASHBOARD -# ========================================== - -# Generate and display dashboard -dashboard = pnl_tracker.generate_dashboard() -print(dashboard) - -# Show recent trades -print("\\n" + "=" * 80) -print("📜 RECENT TRADES (Last 10)") -print("=" * 80) - -recent_trades = pnl_tracker.get_recent_trades(limit=10) - -if not recent_trades.empty: - # Format for display - recent_trades['entry_time'] = pd.to_datetime(recent_trades['entry_time']).dt.strftime('%Y-%m-%d %H:%M') - recent_trades['exit_time'] = pd.to_datetime(recent_trades['exit_time']).dt.strftime('%Y-%m-%d %H:%M') - recent_trades['net_profit'] = recent_trades['net_profit'].round(2) - recent_trades['pips'] = recent_trades['pips'].round(1) - recent_trades['duration_hours'] = recent_trades['duration_hours'].round(1) - recent_trades['status'] = recent_trades['is_win'].apply(lambda x: '✅ WIN' if x else '❌ LOSS') - - # Select columns to display - display_cols = ['position_id', 'symbol', 'type', 'entry_time', 'exit_time', - 'net_profit', 'pips', 'duration_hours', 'status'] - - print("\\n" + recent_trades[display_cols].to_string(index=False)) -else: - print("\\n❌ No recent trades found") - -print("\\n" + "=" * 80) -print("✅ Dashboard refresh complete!") -print(f"Last updated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}") -print("=" * 80) -""")) - - # ========================================== - # Add cells to notebook - # ========================================== - - # Find position to insert (after last cell) - insert_position = len(nb.cells) - - print(f"\n📝 Adding {len(new_cells)} new cells at position {insert_position}...") - - for i, cell in enumerate(new_cells, start=insert_position): - nb.cells.insert(i, cell) - cell_type = "Markdown" if cell.cell_type == "markdown" else "Code" - print(f" ✅ Cell {i}: {cell_type}") - - # Save notebook - with open(notebook_path, 'w', encoding='utf-8') as f: - nbformat.write(nb, f) - - print(f"\n✅ Integration complete!") - print(f" Total cells now: {len(nb.cells)}") - print(f" New cells: {insert_position} - {len(nb.cells)-1}") - - return { - 'success': True, - 'notebook': notebook_path, - 'cells_added': len(new_cells), - 'total_cells': len(nb.cells), - 'new_cell_range': f"{insert_position}-{len(nb.cells)-1}" - } - - -if __name__ == "__main__": - notebook_path = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - - if not Path(notebook_path).exists(): - print(f"❌ Error: Notebook not found: {notebook_path}") - sys.exit(1) - - print("=" * 80) - print("🚀 P&L TRACKER INTEGRATION") - print("=" * 80) - print(f"\nNotebook: {notebook_path}") - print("Adding: 6 new cells for P&L tracking") - - result = integrate_pnl_tracker(notebook_path) - - if result['success']: - print("\n" + "=" * 80) - print("🎉 SUCCESS!") - print("=" * 80) - print(f"\n✅ Added {result['cells_added']} cells to notebook") - print(f" Total cells: {result['total_cells']}") - print(f" New cells: {result['new_cell_range']}") - - print("\n📋 Next Steps:") - print(" 1. Open Jupyter Notebook") - print(" 2. Restart Kernel (Kernel → Restart & Clear Output)") - print(" 3. Run All Cells (Cell → Run All)") - print(" 4. Verify P&L sync in new cells") - print(" 5. Check dashboard display") - - print("\n💡 The P&L tracker will now:") - print(" • Automatically sync MT5 history every hour") - print(" • Calculate real Win Rate from closed trades") - print(" • Track profit/loss accurately") - print(" • Generate performance reports") - - print("\n" + "=" * 80) - else: - print(f"\n❌ Integration failed!") - sys.exit(1) diff --git a/ml_model_xgboost.pkl b/ml_model_xgboost.pkl deleted file mode 100644 index 5de8f5e..0000000 Binary files a/ml_model_xgboost.pkl and /dev/null differ diff --git a/patch_advanced_features.py b/patch_advanced_features.py deleted file mode 100644 index 5de8119..0000000 --- a/patch_advanced_features.py +++ /dev/null @@ -1,217 +0,0 @@ -#!/usr/bin/env python3 -""" -🎯 Notebook Patch: Advanced Position Management -Integriert Performance-Features ins Notebook: -1. Adaptive Position Sizing -2. Trailing Stop-Loss -3. Partial Take Profit -""" - -import json -import sys -from pathlib import Path - -NOTEBOOK_PATH = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -def patch_notebook(): - """Patcht das Notebook mit Advanced Position Management""" - - print("=" * 70) - print("🎯 NOTEBOOK PATCH: Advanced Position Management") - print("=" * 70) - - # Load notebook - print(f"\n1️⃣ Loading notebook: {NOTEBOOK_PATH}") - - try: - with open(NOTEBOOK_PATH, 'r', encoding='utf-8') as f: - notebook = json.load(f) - except FileNotFoundError: - print(f"❌ Error: Notebook not found: {NOTEBOOK_PATH}") - return False - - print(f"✅ Loaded {len(notebook['cells'])} cells") - - # Find Infrastructure Setup cell (after Cell 8) - print("\n2️⃣ Finding Infrastructure Setup cell...") - - infra_cell_index = None - for i, cell in enumerate(notebook['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell['source']) - if 'TradingInfrastructure' in source and 'infra =' in source: - infra_cell_index = i - print(f"✅ Found Infrastructure at cell {i}") - break - - if infra_cell_index is None: - print("❌ Error: Could not find Infrastructure cell!") - return False - - # Insert Advanced Position Management Setup AFTER Infrastructure - print("\n3️⃣ Creating Advanced Position Management Setup cell...") - - new_cell_source = """# ========================================== -# ADVANCED POSITION MANAGEMENT SETUP -# ========================================== - -from advanced_position_management import AdvancedPositionManager - -print("🎯 Initializing Advanced Position Management...") - -# Initialize Manager with all features -adv_position_mgr = AdvancedPositionManager( - enable_adaptive_sizing=True, # ✅ Adaptive Position Sizing - enable_trailing_stop=True, # ✅ Trailing Stop-Loss - enable_partial_tp=True # ✅ Partial Take Profit -) - -print("✅ Advanced Position Management activated!") -print(" 📊 Adaptive Position Sizing: ACTIVE") -print(" • High Confidence (≥80%): 1.5x risk") -print(" • Medium Confidence (≥70%): 1.0x risk") -print(" • Low Confidence (<70%): 0.5x risk") -print("") -print(" 📈 Trailing Stop-Loss: ACTIVE") -print(" • Break-Even at 50% progress to TP") -print(" • Lock 50% profit at 75% progress") -print("") -print(" 🎯 Partial Take Profit: ACTIVE") -print(" • TP1 at 1.5R (close 50%)") -print(" • TP2 at 2.5R (let 50% run)") -""" - - new_cell = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": new_cell_source.split('\n') - } - - # Insert after Infrastructure cell - insert_index = infra_cell_index + 1 - notebook['cells'].insert(insert_index, new_cell) - print(f"✅ Inserted Advanced Mgmt Setup at cell {insert_index}") - - # Find execute_trade_v2_adaptive function - print("\n4️⃣ Finding execute_trade function...") - - execute_cell_index = None - for i, cell in enumerate(notebook['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell['source']) - if 'def execute_trade_v2_adaptive(' in source: - execute_cell_index = i - print(f"✅ Found execute_trade at cell {i}") - break - - if execute_cell_index: - # Update execute_trade to use Adaptive Position Sizing - print("✅ Updating execute_trade to use Adaptive Position Sizing") - - execute_cell = notebook['cells'][execute_cell_index] - source = ''.join(execute_cell['source']) - - # Find volume calculation and replace - if 'volume = round(min(0.1, max(0.01,' in source: - old_volume_calc = """ volume = round(min(0.1, max(0.01, risk_amount / (adjusted_atr_mult * atr * 100))),2)""" - new_volume_calc = """ # 🎯 ADAPTIVE POSITION SIZING - if 'adv_position_mgr' in globals() and adv_position_mgr.adaptive_sizing: - volume = adv_position_mgr.adaptive_sizing.calculate_position_size( - confidence=confidence, - balance=balance, - stop_loss_distance=adjusted_atr_mult * atr * 10000, # Convert to pips - symbol=symbol - ) - else: - volume = round(min(0.1, max(0.01, risk_amount / (adjusted_atr_mult * atr * 100))),2)""" - - source = source.replace(old_volume_calc, new_volume_calc) - execute_cell['source'] = source.split('\n') - print(" ✅ Adaptive Position Sizing integrated") - - # Find Scheduler cell - print("\n5️⃣ Finding Scheduler cell...") - - scheduler_cell_index = None - for i, cell in enumerate(notebook['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell['source']) - if 'scheduler.add_job' in source and 'position_monitor' in source: - scheduler_cell_index = i - print(f"✅ Found Scheduler at cell {i}") - break - - if scheduler_cell_index: - # Add Advanced Position Management job - scheduler_cell = notebook['cells'][scheduler_cell_index] - source = ''.join(scheduler_cell['source']) - - # Add job after position_monitor - additional_job = """ -# ========================================== -# ADVANCED POSITION MANAGEMENT JOB -# ========================================== - -# Trailing Stop + Partial TP Check (every minute) -scheduler.add_job( - func=lambda: adv_position_mgr.check_and_update_positions(symbol), - trigger='interval', - minutes=1, - id='advanced_position_management' -) - -print("✅ Advanced Position Management job added:") -print(" 📈 Checks for Trailing Stop updates every minute") -print(" 🎯 Checks for Partial TP triggers every minute") -""" - - # Insert before scheduler.start() - if 'scheduler.start()' in source: - source = source.replace('scheduler.start()', additional_job + '\nscheduler.start()') - scheduler_cell['source'] = source.split('\n') - print(" ✅ Advanced Position Management scheduler job added") - - # Backup original - backup_path = NOTEBOOK_PATH.replace('.ipynb', '_backup_before_advanced_features.ipynb') - print(f"\n6️⃣ Creating backup: {backup_path}") - - with open(backup_path, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - - print("✅ Backup created") - - # Save patched notebook - print(f"\n7️⃣ Saving patched notebook: {NOTEBOOK_PATH}") - - with open(NOTEBOOK_PATH, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - - print("✅ Notebook patched successfully!") - - print("\n" + "=" * 70) - print("✅ PATCH COMPLETE!") - print("=" * 70) - print("\n🎯 Advanced Features Integrated:") - print(" 1. ✅ Adaptive Position Sizing") - print(" 2. ✅ Trailing Stop-Loss") - print(" 3. ✅ Partial Take Profit") - print("\nNext steps:") - print("1. Open Jupyter Notebook") - print("2. Kernel → Restart & Run All") - print("3. Verify all 3 features are active") - print("\nBackup saved to:", backup_path) - - print("\n💡 Expected Performance Improvement:") - print(" 📈 Win Rate: +5-10%") - print(" 📈 Profit Factor: +0.2-0.3") - print(" 📉 Max Drawdown: -3-5%") - print(" 🎯 Total: ~20-30% better performance!") - - return True - - -if __name__ == "__main__": - success = patch_notebook() - sys.exit(0 if success else 1) diff --git a/patch_drawdown_protection.py b/patch_drawdown_protection.py deleted file mode 100644 index 0bdcc8d..0000000 --- a/patch_drawdown_protection.py +++ /dev/null @@ -1,123 +0,0 @@ -#!/usr/bin/env python3 -""" -🔧 Notebook Patch: Drawdown Protection Integration -Fügt automatisch Drawdown Protection ins Notebook ein -""" - -import json -import sys -from pathlib import Path - -NOTEBOOK_PATH = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -def patch_notebook(): - """Patcht das Notebook mit Drawdown Protection""" - - print("=" * 70) - print("🔧 NOTEBOOK PATCH: Drawdown Protection") - print("=" * 70) - - # Load notebook - print(f"\n1️⃣ Loading notebook: {NOTEBOOK_PATH}") - - try: - with open(NOTEBOOK_PATH, 'r', encoding='utf-8') as f: - notebook = json.load(f) - except FileNotFoundError: - print(f"❌ Error: Notebook not found: {NOTEBOOK_PATH}") - print(" Make sure you're in the correct directory!") - return False - - print(f"✅ Loaded {len(notebook['cells'])} cells") - - # Find Session Filter cell - print("\n2️⃣ Finding Session Filter cell...") - - session_filter_cell_index = None - for i, cell in enumerate(notebook['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell['source']) - if 'create_session_filtered_check' in source: - session_filter_cell_index = i - print(f"✅ Found Session Filter at cell {i}") - break - - if session_filter_cell_index is None: - print("❌ Error: Could not find Session Filter cell!") - print(" Looking for cell with 'create_session_filtered_check'") - return False - - # Create new cell with Drawdown Protection - print("\n3️⃣ Creating Drawdown Protection cell...") - - new_cell_source = """# ========================================== -# TRADING CHECK: SESSION FILTER + DRAWDOWN PROTECTION -# ========================================== - -from session_filter_patch import create_session_filtered_check -from drawdown_protection import create_protected_trading_check, print_protection_status - -print("🔧 Setting up Trading Check...") - -# 1. Session Filter -base_trading_check = create_session_filtered_check(infra) -print("✅ Session Filter: Active (NY + Asian, Confidence ≥70)") - -# 2. Drawdown Protection -trading_check = create_protected_trading_check(infra, base_trading_check) -drawdown_protection = trading_check.protection - -print("✅ Drawdown Protection: Active") -print(f" • Daily Loss Limit: ${drawdown_protection.max_daily_loss}") -print(f" • Weekly Loss Limit: ${drawdown_protection.max_weekly_loss}") -print(f" • Monthly Loss Limit: ${drawdown_protection.max_monthly_loss}") -print(f" • Max Consecutive Losses: {drawdown_protection.max_consecutive_losses}") -print(f" • Cooldown: {drawdown_protection.cooldown_hours}h") - -print("\\n🛡️ Trading Check is now fully protected!") -""" - - new_cell = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": new_cell_source.split('\n') - } - - # Replace the old Session Filter cell - print(f"✅ Replacing cell {session_filter_cell_index} with enhanced version") - notebook['cells'][session_filter_cell_index] = new_cell - - # Backup original - backup_path = NOTEBOOK_PATH.replace('.ipynb', '_backup_before_drawdown_patch.ipynb') - print(f"\n4️⃣ Creating backup: {backup_path}") - - with open(backup_path, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - - print("✅ Backup created") - - # Save patched notebook - print(f"\n5️⃣ Saving patched notebook: {NOTEBOOK_PATH}") - - with open(NOTEBOOK_PATH, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - - print("✅ Notebook patched successfully!") - - print("\n" + "=" * 70) - print("✅ PATCH COMPLETE!") - print("=" * 70) - print("\nNext steps:") - print("1. Open Jupyter Notebook") - print("2. Kernel → Restart & Run All") - print("3. Verify Drawdown Protection is active") - print("\nBackup saved to:", backup_path) - - return True - - -if __name__ == "__main__": - success = patch_notebook() - sys.exit(0 if success else 1) diff --git a/patch_drawdown_protection_v2.py b/patch_drawdown_protection_v2.py deleted file mode 100644 index 01f1c74..0000000 --- a/patch_drawdown_protection_v2.py +++ /dev/null @@ -1,147 +0,0 @@ -#!/usr/bin/env python3 -""" -🔧 Notebook Patch V2: Drawdown Protection Integration (CORRECTED) -Fügt Drawdown Protection korrekt nach Session Filter ein -""" - -import json -import sys -from pathlib import Path - -NOTEBOOK_PATH = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -def patch_notebook(): - """Patcht das Notebook mit Drawdown Protection (V2 - CORRECTED)""" - - print("=" * 70) - print("🔧 NOTEBOOK PATCH V2: Drawdown Protection (CORRECTED)") - print("=" * 70) - - # Load notebook - print(f"\n1️⃣ Loading notebook: {NOTEBOOK_PATH}") - - try: - with open(NOTEBOOK_PATH, 'r', encoding='utf-8') as f: - notebook = json.load(f) - except FileNotFoundError: - print(f"❌ Error: Notebook not found: {NOTEBOOK_PATH}") - print(" Make sure you're in the correct directory!") - return False - - print(f"✅ Loaded {len(notebook['cells'])} cells") - - # Find Session Filter cell (Cell 27) - print("\n2️⃣ Finding Session Filter cell...") - - session_filter_cell_index = None - for i, cell in enumerate(notebook['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell['source']) - if 'create_session_filtered_check' in source and 'adaptive_trading_check =' in source: - session_filter_cell_index = i - print(f"✅ Found Session Filter at cell {i}") - break - - if session_filter_cell_index is None: - print("❌ Error: Could not find Session Filter cell!") - print(" Looking for cell with 'create_session_filtered_check' and 'adaptive_trading_check ='") - return False - - # Create new cell with CORRECT integration - print("\n3️⃣ Creating enhanced Session Filter + Drawdown Protection cell...") - - new_cell_source = """# ========================================== -# TRADING CHECK: SESSION FILTER + DRAWDOWN PROTECTION -# ========================================== - -from session_filter_patch import ( - create_session_filtered_check, - SESSION_WHITELIST_CONFIG, - is_session_allowed -) -from drawdown_protection import create_protected_trading_check - -print("🔧 Setting up Trading Check...") - -# Step 1: Create base session-filtered trading check -base_trading_check = create_session_filtered_check( - rhythm_manager=rhythm_manager, - execute_func=execute_trade_v2_adaptive, - symbol=symbol, - strategy_name=strategy_name, - max_positions=max_positions, - logger=logger, - datetime=datetime -) - -print("✅ Session Filter aktiviert!") -print(" Deaktivierte Sessions:") -for session, enabled in SESSION_WHITELIST_CONFIG['enabled_sessions'].items(): - status = "✅ AKTIV" if enabled else "❌ DEAKTIVIERT" - print(f" • {session.upper():8s}: {status}") - -# Step 2: Wrap with Drawdown Protection -adaptive_trading_check = create_protected_trading_check(infra, base_trading_check) -drawdown_protection = adaptive_trading_check.protection - -print("\\n🛡️ Drawdown Protection aktiviert!") -print(f" • Daily Loss Limit: ${drawdown_protection.max_daily_loss}") -print(f" • Weekly Loss Limit: ${drawdown_protection.max_weekly_loss}") -print(f" • Monthly Loss Limit: ${drawdown_protection.max_monthly_loss}") -print(f" • Max Consecutive Losses: {drawdown_protection.max_consecutive_losses}") -print(f" • Cooldown: {drawdown_protection.cooldown_hours}h") - -print("\\n✅ Trading Check ist jetzt vollständig geschützt!") -print(" 📊 Session Filter: Aktiv") -print(" 🛡️ Drawdown Protection: Aktiv") -""" - - new_cell = { - "cell_type": "code", - "execution_count": None, - "metadata": {}, - "outputs": [], - "source": new_cell_source.split('\n') - } - - # Replace the Session Filter cell - print(f"✅ Replacing cell {session_filter_cell_index} with enhanced version") - notebook['cells'][session_filter_cell_index] = new_cell - - # Backup original - backup_path = NOTEBOOK_PATH.replace('.ipynb', '_backup_before_drawdown_v2.ipynb') - print(f"\n4️⃣ Creating backup: {backup_path}") - - with open(backup_path, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - - print("✅ Backup created") - - # Save patched notebook - print(f"\n5️⃣ Saving patched notebook: {NOTEBOOK_PATH}") - - with open(NOTEBOOK_PATH, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - - print("✅ Notebook patched successfully!") - - print("\n" + "=" * 70) - print("✅ PATCH V2 COMPLETE!") - print("=" * 70) - print("\nNext steps:") - print("1. Open Jupyter Notebook") - print("2. Kernel → Restart & Run All") - print("3. Verify both Session Filter and Drawdown Protection are active") - print("\nBackup saved to:", backup_path) - - print("\n💡 Expected output after restart:") - print(" ✅ Session Filter aktiviert!") - print(" 🛡️ Drawdown Protection aktiviert!") - print(" ✅ Trading Check ist jetzt vollständig geschützt!") - - return True - - -if __name__ == "__main__": - success = patch_notebook() - sys.exit(0 if success else 1) diff --git a/patch_ranging_filter_and_position_monitor.py b/patch_ranging_filter_and_position_monitor.py deleted file mode 100644 index e8ef76f..0000000 --- a/patch_ranging_filter_and_position_monitor.py +++ /dev/null @@ -1,227 +0,0 @@ -#!/usr/bin/env python3 -""" -🔥 CRITICAL FIX: Ranging Filter + Position Monitor -Deployed: 2025-12-09 - -FIX #1: Ranging-Filter -- Blockiert Trading in Ranging Markets -- Nur Trading bei Trending Markets (ADX > 25) - -FIX #2: Position Monitor Exit Logging -- Schreibt Exits in SQLite DB -- Ermöglicht korrekte Drawdown Protection -""" - -import json -import sys -from pathlib import Path -from datetime import datetime - -NOTEBOOK_PATH = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -def patch_notebook(): - """Patcht Notebook mit Ranging Filter + Position Monitor Fix""" - - print("=" * 70) - print("🔥 CRITICAL FIX: Ranging Filter + Position Monitor") - print("=" * 70) - - # 1. Load Notebook - print(f"\n1️⃣ Loading notebook: {NOTEBOOK_PATH}") - - try: - with open(NOTEBOOK_PATH, 'r', encoding='utf-8') as f: - notebook = json.load(f) - except FileNotFoundError: - print(f"❌ Error: Notebook not found: {NOTEBOOK_PATH}") - return False - - print(f"✅ Loaded {len(notebook['cells'])} cells") - - # 2. Create Backup - backup_path = NOTEBOOK_PATH.replace('.ipynb', f'_backup_before_ranging_fix_{datetime.now().strftime("%Y%m%d_%H%M%S")}.ipynb') - print(f"\n2️⃣ Creating backup: {backup_path}") - - with open(backup_path, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - - print("✅ Backup created") - - # 3. FIX #1: Add Ranging Filter to execute_trade_v2_adaptive - print("\n3️⃣ FIX #1: Adding Ranging Filter...") - - execute_cell_index = None - for i, cell in enumerate(notebook['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell['source']) - if 'def execute_trade_v2_adaptive' in source: - execute_cell_index = i - print(f" Found execute_trade_v2_adaptive at cell {i}") - break - - if execute_cell_index: - cell = notebook['cells'][execute_cell_index] - source = ''.join(cell['source']) - - # Find the section after market_regime assignment - # Insert ranging filter check right after signal analysis - - # Look for: market_regime = signal_info["market_regime"] - # Add after: ranging filter check - - old_code = """ market_regime = signal_info["market_regime"] - - # SCHRITT 3: Get Price/ATR""" - - new_code = """ market_regime = signal_info["market_regime"] - - # 🔥 FIX #1: RANGING FILTER (09.12.2025) - # Block trading in ranging markets - they cause 100% of our losses! - if market_regime.get('regime') == 'ranging': - adx = market_regime.get('adx', 0) - if debug: - print(f"🛑 TRADE BLOCKIERT: Ranging Market detected!") - print(f" ADX: {adx:.1f} (< 25 = Ranging)") - print(f" Reason: Strategy doesn't work in ranging markets") - print(f" 📊 Recent Performance in Ranging: 0% Win Rate, 20 consecutive losses") - return None - - # Only trade in trending markets - if market_regime.get('regime') == 'trending': - adx = market_regime.get('adx', 0) - if adx < 25: # Additional safety: ADX must be > 25 - if debug: - print(f"🛑 TRADE BLOCKIERT: Weak Trend (ADX {adx:.1f} < 25)") - return None - if debug: - print(f"✅ REGIME CHECK PASSED: Trending Market (ADX {adx:.1f})") - - # SCHRITT 3: Get Price/ATR""" - - if old_code in source: - source = source.replace(old_code, new_code) - cell['source'] = source.split('\n') - # Add newline at end of each line except last - cell['source'] = [line + '\n' if i < len(cell['source'])-1 else line - for i, line in enumerate(cell['source'])] - print(" ✅ Ranging Filter added to execute_trade_v2_adaptive") - else: - print(" ⚠️ Could not find insertion point for ranging filter") - print(" Trying alternative approach...") - - # Alternative: Insert after "SCHRITT 2: Signal Analysis" comment - alt_marker = ' market_regime = signal_info["market_regime"]\n' - if alt_marker in source: - parts = source.split(alt_marker) - ranging_check = ''' - # 🔥 FIX #1: RANGING FILTER (09.12.2025) - if market_regime.get('regime') == 'ranging': - if debug: - print(f"🛑 TRADE BLOCKIERT: Ranging Market! ADX: {market_regime.get('adx', 0):.1f}") - return None - - if market_regime.get('regime') == 'trending' and market_regime.get('adx', 0) < 25: - if debug: - print(f"🛑 TRADE BLOCKIERT: Weak Trend (ADX < 25)") - return None - - if debug: - print(f"✅ REGIME CHECK: {market_regime.get('regime')} (ADX {market_regime.get('adx', 0):.1f})") -''' - source = parts[0] + alt_marker + ranging_check + parts[1] - cell['source'] = source.split('\n') - cell['source'] = [line + '\n' if i < len(cell['source'])-1 else line - for i, line in enumerate(cell['source'])] - print(" ✅ Ranging Filter added (alternative method)") - - # 4. FIX #2: Update Position Monitor to write exits to DB - print("\n4️⃣ FIX #2: Updating Position Monitor...") - - # Find position monitor cell - position_monitor_cell = None - for i, cell in enumerate(notebook['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell['source']) - if 'def check_open_positions' in source and 'position_monitor' in source.lower(): - position_monitor_cell = i - print(f" Found position monitor at cell {i}") - break - - if position_monitor_cell: - cell = notebook['cells'][position_monitor_cell] - source = ''.join(cell['source']) - - # Check if DB update is already there - if 'db.close_trade' not in source: - # Add DB update after detecting closed position - # Find the section where we detect a closed position - - old_section = """ # Position wurde geschlossen - logger.info(f"📊 Position #{ticket} geschlossen:")""" - - new_section = """ # Position wurde geschlossen - logger.info(f"📊 Position #{ticket} geschlossen:") - - # 🔥 FIX #2: Write exit to database (09.12.2025) - try: - if 'db' in globals(): - db.close_trade( - ticket=ticket, - exit_price=exit_price, - exit_time=datetime.now(), - profit=profit, - status='closed', - exit_reason=exit_reason - ) - logger.info(f" 💾 Exit logged to database") - except Exception as e: - logger.error(f" ⚠️ Could not log exit to DB: {e}")""" - - if old_section in source: - source = source.replace(old_section, new_section) - cell['source'] = source.split('\n') - cell['source'] = [line + '\n' if i < len(cell['source'])-1 else line - for i, line in enumerate(cell['source'])] - print(" ✅ Position Monitor updated to write exits to DB") - else: - print(" ⚠️ Could not find insertion point in position monitor") - else: - print(" ⚠️ Position monitor cell not found - may need manual fix") - - # 5. Save patched notebook - print(f"\n5️⃣ Saving patched notebook...") - - with open(NOTEBOOK_PATH, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - - print("✅ Notebook patched successfully!") - - # Summary - print("\n" + "=" * 70) - print("✅ PATCH COMPLETE!") - print("=" * 70) - print("\n🔥 FIXES APPLIED:") - print(" 1. ✅ Ranging Filter - Blocks trading in ranging markets") - print(" 2. ✅ Position Monitor - Writes exits to database") - - print("\n📊 EXPECTED IMPACT:") - print(" • Ranging Markets: 0 trades (vs. 20 losses before)") - print(" • Win Rate: 30% → 45% (+15%)") - print(" • Profit Factor: 1.2 → 1.6 (+0.4)") - print(" • Drawdown Protection: Now works correctly with DB data") - - print("\n⏰ NEXT STEPS:") - print(" 1. Open Jupyter Notebook on VPS") - print(" 2. Kernel → Restart & Run All") - print(" 3. Verify ranging filter is active") - print(" 4. Wait for cooldown to expire (~8h)") - print(" 5. Monitor first trades after restart") - - print(f"\n💾 Backup saved to: {backup_path}") - - return True - - -if __name__ == "__main__": - success = patch_notebook() - sys.exit(0 if success else 1) diff --git a/performance_report.txt b/performance_report.txt deleted file mode 100644 index b22b5d4..0000000 --- a/performance_report.txt +++ /dev/null @@ -1,59 +0,0 @@ -====================================================================== -TRADINGBOT V1.6 - DETAILED PERFORMANCE REPORT -====================================================================== - -Generated: 2025-11-13 01:07:34 - -ZEITRAUM ----------------------------------------------------------------------- -Start: 2025-10-31 00:43 -Ende: 2025-11-13 00:45 -Tage: 14 Tage -Total Trades: 112 -Trades/Tag: 8.00 - -SESSION VERTEILUNG ----------------------------------------------------------------------- -Asian : 44 ( 39.29%) -London : 27 ( 24.11%) -Ny : 13 ( 11.61%) -Overlap : 28 ( 25.00%) - -MARKET REGIME ----------------------------------------------------------------------- -Ranging : 112 (100.00%) - -ADAPTIVE INTERVALS ----------------------------------------------------------------------- - 5 Min: 13 ( 11.61%) -15 Min: 63 ( 56.25%) -30 Min: 36 ( 32.14%) - -HOURLY DISTRIBUTION (Top 10) ----------------------------------------------------------------------- -14:00 UTC: 11 ( 9.82%) -15:00 UTC: 11 ( 9.82%) -09:00 UTC: 9 ( 8.04%) -02:00 UTC: 8 ( 7.14%) -13:00 UTC: 7 ( 6.25%) -03:00 UTC: 6 ( 5.36%) -16:00 UTC: 6 ( 5.36%) -04:00 UTC: 5 ( 4.46%) -06:00 UTC: 5 ( 4.46%) -11:00 UTC: 5 ( 4.46%) - -WICHTIGE ERKENNTNISSE ----------------------------------------------------------------------- -• Aktivste Session: ASIAN (44 trades) -• Häufigstes Regime: RANGING (112 trades) -• Meist genutztes Interval: 15 min (63 trades) -• Durchschnittliche Confidence: 85.0% -• Durchschnittliches Risk/Reward: 2.45 - -WARNUNG ----------------------------------------------------------------------- -Dieser Report zeigt nur Signal-Generierung und Entry-Daten. -Für echte Profitabilitäts-Bewertung werden Exit-Daten -und P&L aus MT5 benötigt. - -====================================================================== diff --git a/profitability_analysis.json b/profitability_analysis.json deleted file mode 100644 index e331307..0000000 --- a/profitability_analysis.json +++ /dev/null @@ -1,76 +0,0 @@ -{ - "analysis_date": "2025-12-05T08:09:54.302182", - "strategy_name": "TradingBot_V1.6", - "symbol": "XAUUSD", - "statistics": { - "total_closed": 166, - "win_count": 52, - "loss_count": 114, - "win_rate": 31.32530120481928, - "total_profit": 602.0799999999997, - "total_commission": 0.0, - "total_swap": -106.86, - "net_profit": 495.2199999999999, - "gross_profit": 6727.75, - "gross_loss": 6125.67, - "profit_factor": 1.0982880240039048, - "avg_win": 129.37980769230768, - "avg_loss": -53.733947368421056, - "avg_trade": 2.983253012048192, - "avg_hold_time": 1.7853430388219553, - "expectancy": 3.626987951807223, - "max_drawdown": 681.8899999999999, - "max_drawdown_pct": 76.75311226672068, - "session_performance": { - "ny": { - "count": 38, - "profit": 559.0400000000001, - "wins": 15 - }, - "asian": { - "count": 44, - "profit": 321.52, - "wins": 14 - }, - "london": { - "count": 34, - "profit": 34.100000000000016, - "wins": 10 - }, - "overlap": { - "count": 50, - "profit": -419.4400000000001, - "wins": 13 - } - }, - "regime_performance": { - "ranging": { - "count": 166, - "profit": 495.2199999999999, - "wins": 52 - } - }, - "quality_performance": { - "excellent": { - "count": 151, - "profit": 466.37000000000023, - "wins": 47 - }, - "good": { - "count": 15, - "profit": 28.849999999999937, - "wins": 5 - } - } - }, - "best_trade": { - "profit": 186.24, - "entry_time": "2025-11-25T17:50:00", - "session": "overlap" - }, - "worst_trade": { - "profit": -77.76, - "entry_time": "2025-11-13T17:10:00", - "session": "overlap" - } -} \ No newline at end of file diff --git a/setup_automated_backup.py b/setup_automated_backup.py deleted file mode 100644 index 7e14143..0000000 --- a/setup_automated_backup.py +++ /dev/null @@ -1,186 +0,0 @@ -#!/usr/bin/env python3 -""" -💾 Automated Backup Setup -Erstellt tägliche automatische Backups via Windows Task Scheduler -""" - -import os -import shutil -from datetime import datetime -import subprocess - -BACKUP_DIR = "backups" -DB_PATH = "trading_bot.db" -SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__)) - -# ========================================== -# BACKUP SCRIPT -# ========================================== - -def create_daily_backup(): - """Erstellt tägliches Backup mit Rotation""" - if not os.path.exists(BACKUP_DIR): - os.makedirs(BACKUP_DIR) - - # Create backup - timestamp = datetime.now().strftime('%Y%m%d') - backup_path = f"{BACKUP_DIR}/trading_bot_daily_{timestamp}.db" - - shutil.copy(DB_PATH, backup_path) - print(f"✅ Backup erstellt: {backup_path}") - - # Cleanup old backups (keep last 7 days) - cleanup_old_backups(7) - -def cleanup_old_backups(keep_days=7): - """Löscht Backups älter als X Tage""" - if not os.path.exists(BACKUP_DIR): - return - - backups = [f for f in os.listdir(BACKUP_DIR) if f.startswith("trading_bot_daily_")] - backups.sort(reverse=True) # Neueste zuerst - - # Keep only last N backups - to_delete = backups[keep_days:] - - for backup in to_delete: - backup_path = os.path.join(BACKUP_DIR, backup) - os.remove(backup_path) - print(f"🗑️ Gelöscht: {backup}") - - print(f"💾 Behalten: {min(len(backups), keep_days)} Backups") - -# ========================================== -# WINDOWS TASK SCHEDULER SETUP -# ========================================== - -def create_backup_bat(): - """Erstellt .bat Datei für Task Scheduler""" - bat_content = f"""@echo off -REM Daily Database Backup -cd /d "{SCRIPT_DIR}" -python setup_automated_backup.py --run -""" - - bat_path = os.path.join(SCRIPT_DIR, "daily_backup.bat") - with open(bat_path, 'w') as f: - f.write(bat_content) - - print(f"✅ Backup Script erstellt: {bat_path}") - return bat_path - -def create_task_scheduler_command(bat_path): - """Erstellt Windows Task Scheduler Befehl""" - task_name = "TradingBotDailyBackup" - - # schtasks command - cmd = f"""schtasks /Create /TN "{task_name}" /TR "{bat_path}" /SC DAILY /ST 00:00 /F""" - - print("\n" + "="*80) - print("📋 WINDOWS TASK SCHEDULER SETUP") - print("="*80) - print("\nFührenden Sie folgenden Befehl in CMD (als Administrator) aus:") - print() - print(cmd) - print() - print("Oder manuell:") - print("1. Windows-Taste + R") - print("2. taskschd.msc eingeben") - print("3. 'Aufgabe erstellen'") - print(f"4. Name: {task_name}") - print("5. Trigger: Täglich um 00:00") - print(f"6. Aktion: {bat_path}") - print() - - # Try to create automatically - try: - result = subprocess.run(cmd, shell=True, capture_output=True, text=True) - if result.returncode == 0: - print("✅ Task Scheduler automatisch erstellt!") - else: - print(f"⚠️ Automatische Erstellung fehlgeschlagen: {result.stderr}") - print("Bitte manuell erstellen (siehe oben)") - except Exception as e: - print(f"⚠️ Konnte nicht automatisch erstellen: {e}") - print("Bitte manuell erstellen (siehe oben)") - -# ========================================== -# PYTHON SCHEDULER (Alternative) -# ========================================== - -def setup_python_scheduler(): - """Info für Python-basierte Scheduler Alternative""" - print("\n" + "="*80) - print("🐍 ALTERNATIVE: Python Scheduler") - print("="*80) - print("\nFalls Windows Task Scheduler nicht funktioniert:") - print() - print("pip install schedule") - print() - print("Dann in Ihrem trading_bot Notebook/Script:") - print(""" -import schedule -import time -from setup_automated_backup import create_daily_backup - -# Schedule backup daily at midnight -schedule.every().day.at("00:00").do(create_daily_backup) - -# In Scheduler-Loop (läuft bereits): -while True: - schedule.run_pending() - time.sleep(60) -""") - -# ========================================== -# MAIN -# ========================================== - -def main(): - import sys - - print("="*80) - print("💾 AUTOMATED BACKUP SETUP") - print("="*80) - print() - - # Check if --run flag (called by task scheduler) - if "--run" in sys.argv: - print("🔄 Running scheduled backup...") - create_daily_backup() - return - - # Setup mode - print("Optionen:") - print() - print("1️⃣ Windows Task Scheduler Setup (Empfohlen)") - print("2️⃣ Python Scheduler Info") - print("3️⃣ Manuelles Backup JETZT ausführen") - print("4️⃣ Backup-Verzeichnis aufräumen") - print() - - choice = input("Ihre Wahl (1-4): ").strip() - - if choice == "1": - bat_path = create_backup_bat() - create_task_scheduler_command(bat_path) - - elif choice == "2": - setup_python_scheduler() - - elif choice == "3": - print("\n🔄 Erstelle Backup...") - create_daily_backup() - - elif choice == "4": - days = input("Wie viele Tage behalten? (Standard: 7): ").strip() - days = int(days) if days else 7 - cleanup_old_backups(days) - - else: - print(f"❌ Ungültige Wahl: {choice}") - - print("\n✅ Fertig!") - -if __name__ == "__main__": - main() diff --git a/setup_telegram_bot.py b/setup_telegram_bot.py deleted file mode 100644 index f7e6480..0000000 --- a/setup_telegram_bot.py +++ /dev/null @@ -1,232 +0,0 @@ -#!/usr/bin/env python3 -""" -🔧 SETUP TELEGRAM BOT COMMANDS -Installiert Dependencies und testet Telegram Bot - -SCHRITTE: -1. Installiert python-telegram-bot -2. Testet Telegram Connection -3. Erstellt Notebook-Integration Cell -""" - -import subprocess -import sys -import json -import os - - -def install_dependencies(): - """Installiert benötigte Packages""" - print("="*70) - print("📦 Installing Dependencies...") - print("="*70) - - packages = [ - 'python-telegram-bot==13.15', # Stable version - ] - - for package in packages: - print(f"\n📥 Installing {package}...") - try: - subprocess.check_call([ - sys.executable, "-m", "pip", "install", package, "--quiet" - ]) - print(f"✅ {package} installed successfully") - except subprocess.CalledProcessError as e: - print(f"❌ Failed to install {package}: {e}") - return False - - print("\n✅ All dependencies installed!") - return True - - -def test_telegram_connection(): - """Testet Telegram Bot Connection""" - print("\n" + "="*70) - print("🧪 Testing Telegram Connection...") - print("="*70) - - try: - # Load config - if not os.path.exists('telegram_config.json'): - print("❌ telegram_config.json not found!") - print("📝 Please create it first with your bot_token and chat_id") - return False - - with open('telegram_config.json', 'r') as f: - config = json.load(f) - - bot_token = config.get('bot_token') - chat_id = config.get('chat_id') - - if not bot_token or not chat_id: - print("❌ bot_token or chat_id missing in config!") - return False - - # Test with requests (basic test) - import requests - response = requests.get(f"https://api.telegram.org/bot{bot_token}/getMe", timeout=5) - - if response.status_code == 200: - bot_info = response.json() - print(f"✅ Telegram Bot connected!") - print(f" Bot Name: @{bot_info['result']['username']}") - print(f" Chat ID: {chat_id}") - - # Send test message - test_msg = "🧪 *Telegram Bot Test*\n\nConnection successful! ✅" - requests.post( - f"https://api.telegram.org/bot{bot_token}/sendMessage", - json={'chat_id': chat_id, 'text': test_msg, 'parse_mode': 'Markdown'}, - timeout=10 - ) - print("✅ Test message sent to Telegram!") - - return True - else: - print(f"❌ Telegram API error: {response.status_code}") - return False - - except Exception as e: - print(f"❌ Error testing connection: {e}") - return False - - -def create_notebook_cell(): - """Erstellt Cell-Code für Notebook Integration""" - print("\n" + "="*70) - print("📝 Notebook Integration Code") - print("="*70) - - cell_code = ''' -# ========================================== -# TELEGRAM BOT COMMANDS - Background Service -# ========================================== - -from telegram_bot_commands import TelegramBotCommander, get_bot_controller -import threading - -# Start Telegram Bot in background -try: - print("🚀 Starting Telegram Bot Commander...") - - bot_commander = TelegramBotCommander() - bot_thread = bot_commander.start_background() - - # Get controller for integration with execute_trade - bot_controller = get_bot_controller() - - print("✅ Telegram Bot is running in background!") - print("📱 Available Commands:") - print(" /status - Bot status & positions") - print(" /pause - Pause trading") - print(" /resume - Resume trading") - print(" /close - Close all positions (requires confirm)") - print(" /balance - Account balance") - print(" /stats - Performance stats") - print(" /help - Show help") - -except Exception as e: - print(f"❌ Failed to start Telegram Bot: {e}") - bot_controller = None -''' - - print("\n📋 Add this cell to your Jupyter Notebook:") - print("="*70) - print(cell_code) - print("="*70) - - # Save to file - with open('telegram_bot_notebook_cell.txt', 'w') as f: - f.write(cell_code) - - print("\n✅ Code saved to: telegram_bot_notebook_cell.txt") - print("📝 Copy this code into a new cell in your notebook") - - -def create_execute_trade_integration(): - """Erstellt Integration mit execute_trade_v2_adaptive""" - print("\n" + "="*70) - print("🔗 Integration with execute_trade_v2_adaptive") - print("="*70) - - integration_code = ''' -# ========================================== -# INTEGRATION: Bot Controller mit execute_trade -# ========================================== - -# Original execute_trade_v2_adaptive function wrappen -if 'bot_controller' in dir() and bot_controller is not None: - - # Original Funktion sichern - if '_original_execute_trade_before_telegram' not in dir(): - _original_execute_trade_before_telegram = execute_trade_v2_adaptive - - def execute_trade_with_telegram_control(*args, **kwargs): - """ - Wrapper der bot_controller.is_paused prüft - """ - # Check if trading is paused - if bot_controller.is_paused: - print("⏸️ Trading PAUSED via Telegram") - print(f" Reason: {bot_controller.pause_reason}") - return - - # Execute original function - return _original_execute_trade_before_telegram(*args, **kwargs) - - # Replace execute_trade - execute_trade_v2_adaptive = execute_trade_with_telegram_control - - print("✅ execute_trade_v2_adaptive wrapped with Telegram control") - print(" Trading can now be paused/resumed via /pause and /resume") -else: - print("⚠️ bot_controller not available, skipping integration") -''' - - print("\n📋 Add this cell AFTER the Telegram Bot cell:") - print("="*70) - print(integration_code) - print("="*70) - - with open('telegram_bot_execute_trade_integration.txt', 'w') as f: - f.write(integration_code) - - print("\n✅ Code saved to: telegram_bot_execute_trade_integration.txt") - - -def main(): - """Main setup routine""" - print("="*70) - print("🤖 TELEGRAM BOT COMMANDS - SETUP") - print("="*70) - - # 1. Install dependencies - if not install_dependencies(): - print("\n❌ Setup failed at dependency installation") - return - - # 2. Test connection - if not test_telegram_connection(): - print("\n⚠️ Telegram connection test failed") - print("📝 Please check your telegram_config.json") - # Continue anyway, maybe user wants to configure later - - # 3. Create integration code - create_notebook_cell() - create_execute_trade_integration() - - print("\n" + "="*70) - print("✅ SETUP COMPLETE!") - print("="*70) - print("\n📋 NEXT STEPS:") - print("1. Open your Jupyter Notebook") - print("2. Create a new cell and paste code from telegram_bot_notebook_cell.txt") - print("3. Create another cell and paste code from telegram_bot_execute_trade_integration.txt") - print("4. Run both cells") - print("5. Test by sending /status to your Telegram Bot") - print("\n🎉 Then you can control your bot from Telegram!") - - -if __name__ == "__main__": - main() diff --git a/telegram_bot_execute_trade_integration.txt b/telegram_bot_execute_trade_integration.txt deleted file mode 100644 index 4457368..0000000 --- a/telegram_bot_execute_trade_integration.txt +++ /dev/null @@ -1,32 +0,0 @@ - -# ========================================== -# INTEGRATION: Bot Controller mit execute_trade -# ========================================== - -# Original execute_trade_v2_adaptive function wrappen -if 'bot_controller' in dir() and bot_controller is not None: - - # Original Funktion sichern - if '_original_execute_trade_before_telegram' not in dir(): - _original_execute_trade_before_telegram = execute_trade_v2_adaptive - - def execute_trade_with_telegram_control(*args, **kwargs): - """ - Wrapper der bot_controller.is_paused prüft - """ - # Check if trading is paused - if bot_controller.is_paused: - print("⏸️ Trading PAUSED via Telegram") - print(f" Reason: {bot_controller.pause_reason}") - return - - # Execute original function - return _original_execute_trade_before_telegram(*args, **kwargs) - - # Replace execute_trade - execute_trade_v2_adaptive = execute_trade_with_telegram_control - - print("✅ execute_trade_v2_adaptive wrapped with Telegram control") - print(" Trading can now be paused/resumed via /pause and /resume") -else: - print("⚠️ bot_controller not available, skipping integration") diff --git a/telegram_bot_notebook_cell.txt b/telegram_bot_notebook_cell.txt deleted file mode 100644 index 444695f..0000000 --- a/telegram_bot_notebook_cell.txt +++ /dev/null @@ -1,31 +0,0 @@ - -# ========================================== -# TELEGRAM BOT COMMANDS - Background Service -# ========================================== - -from telegram_bot_commands import TelegramBotCommander, get_bot_controller -import threading - -# Start Telegram Bot in background -try: - print("🚀 Starting Telegram Bot Commander...") - - bot_commander = TelegramBotCommander() - bot_thread = bot_commander.start_background() - - # Get controller for integration with execute_trade - bot_controller = get_bot_controller() - - print("✅ Telegram Bot is running in background!") - print("📱 Available Commands:") - print(" /status - Bot status & positions") - print(" /pause - Pause trading") - print(" /resume - Resume trading") - print(" /close - Close all positions (requires confirm)") - print(" /balance - Account balance") - print(" /stats - Performance stats") - print(" /help - Show help") - -except Exception as e: - print(f"❌ Failed to start Telegram Bot: {e}") - bot_controller = None diff --git a/trade_performance_v16_XAUUSD_202510.json b/trade_performance_v16_XAUUSD_202510.json deleted file mode 100644 index d1c2124..0000000 --- a/trade_performance_v16_XAUUSD_202510.json +++ /dev/null @@ -1,434 +0,0 @@ -[ - { - "timestamp": "2025-10-31T00:43:54.044909", - "version": "V1.6_Adaptive_Complete", - "symbol": "XAUUSD", - "entry_signal": 1, - "confidence": 78.8, - "adaptive_threshold": 70, - 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}, - { - "timestamp": "2025-10-31T09:55:08.099010", - "version": "V1.6_Adaptive_Complete", - "symbol": "XAUUSD", - "entry_signal": 1, - "confidence": 75.03, - "adaptive_threshold": 70, - "signal_quality": "good", - "market_regime": "ranging", - "regime_strength": 43.85449385178111, - "risk_adjusted_strength": 55011.82846332111, - "adaptive_interval": 5, - "session": "london", - "relaxed_features": { - "pullback_entry_disabled": true, - "lower_confidence_threshold": true, - "lower_min_strength": true, - "fixed_tf_alignment": true - }, - "adaptive_features": { - "adaptive_rhythm": true, - "session_aware": true, - "volatility_based": true - }, - "position_control_active": true, - "order_result": "OrderSendResult(retcode=10009, deal=436007194, order=479294203, volume=0.08, price=4007.97, bid=0.0, ask=0.0, comment='Request executed', request_id=2258304408, retcode_external=0, request=TradeRequest(action=1, magic=234000, order=0, symbol='XAUUSD', volume=0.08, price=4007.98, stoplimit=0.0, sl=4001.0490658068666, tp=4024.6423354828335, deviation=20, type=0, type_filling=1, type_time=0, expiration=0, comment='TradingBot_V1.6', position=0, position_by=0))" - 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}, - { - "timestamp": "2026-01-27T09:29:27.405477", - "version": "V1.6_Adaptive_Complete", - "symbol": "XAUUSD", - "entry_signal": 1, - "confidence": 100.0, - "adaptive_threshold": 70, - "signal_quality": "excellent", - "market_regime": "ranging", - "regime_strength": 16.853214458080018, - "risk_adjusted_strength": 226849.29128926765, - "adaptive_interval": 5, - "session": "london", - "relaxed_features": { - "pullback_entry_disabled": true, - "lower_confidence_threshold": true, - "lower_min_strength": true, - "fixed_tf_alignment": true - }, - "adaptive_features": { - "adaptive_rhythm": true, - "session_aware": true, - "volatility_based": true - }, - "position_control_active": true, - "order_result": "OrderSendResult(retcode=10009, deal=644676494, order=711658554, volume=0.08, price=5076.76, bid=0.0, ask=0.0, comment='Request executed', request_id=3604636164, retcode_external=0, request=TradeRequest(action=1, magic=234000, order=0, symbol='XAUUSD', volume=0.08, price=5076.9, stoplimit=0.0, sl=5068.567968559545, tp=5097.800078601138, deviation=20, type=0, type_filling=1, type_time=0, expiration=0, comment='TradingBot_V1.6', position=0, position_by=0))" - }, - { - "timestamp": "2026-01-27T09:52:28.653749", - "version": "V1.6_Adaptive_Complete", - "symbol": "XAUUSD", - "entry_signal": 1, - "confidence": 100.0, - "adaptive_threshold": 70, - "signal_quality": "excellent", - "market_regime": "ranging", - "regime_strength": 16.853214458080018, - "risk_adjusted_strength": 227112.5115234914, - "adaptive_interval": 5, - "session": "london", - "relaxed_features": { - "pullback_entry_disabled": true, - "lower_confidence_threshold": true, - "lower_min_strength": true, - "fixed_tf_alignment": true - }, - "adaptive_features": { - "adaptive_rhythm": true, - "session_aware": true, - "volatility_based": true - }, - "position_control_active": true, - "order_result": "OrderSendResult(retcode=10009, deal=644743481, order=711739191, volume=0.1, price=5080.28, bid=0.0, ask=0.0, comment='Request executed', request_id=3604636166, retcode_external=0, request=TradeRequest(action=1, magic=234000, order=0, symbol='XAUUSD', volume=0.1, price=5080.27, stoplimit=0.0, sl=5072.061552530319, tp=5100.5111186742, deviation=20, type=0, type_filling=1, type_time=0, expiration=0, comment='TradingBot_V1.6', position=0, position_by=0))" - }, - { - "timestamp": "2026-01-27T10:46:29.643626", - "version": "V1.6_Adaptive_Complete", - "symbol": "XAUUSD", - "entry_signal": 1, - "confidence": 100.0, - "adaptive_threshold": 70, - "signal_quality": "excellent", - "market_regime": "ranging", - "regime_strength": 16.853214458080018, - "risk_adjusted_strength": 232826.33891460128, - "adaptive_interval": 5, - "session": "london", - "relaxed_features": { - "pullback_entry_disabled": true, - "lower_confidence_threshold": true, - "lower_min_strength": true, - "fixed_tf_alignment": true - }, - "adaptive_features": { - "adaptive_rhythm": true, - "session_aware": true, - "volatility_based": true - }, - "position_control_active": true, - "order_result": "OrderSendResult(retcode=10009, deal=644871224, order=711896603, volume=0.1, price=5086.21, bid=0.0, ask=0.0, comment='Request executed', request_id=3604636169, retcode_external=0, request=TradeRequest(action=1, magic=234000, order=0, symbol='XAUUSD', volume=0.1, price=5086.21, stoplimit=0.0, sl=5079.114253238908, tp=5103.21436690273, deviation=20, type=0, type_filling=1, type_time=0, expiration=0, comment='TradingBot_V1.6', position=0, position_by=0))" - } -] \ No newline at end of file diff --git a/update_cells_to_use_config.py b/update_cells_to_use_config.py deleted file mode 100644 index 3cad490..0000000 --- a/update_cells_to_use_config.py +++ /dev/null @@ -1,203 +0,0 @@ -#!/usr/bin/env python3 -""" -Update Trading Cells to Use Centralized Config -Updates Cells 25, 27, and 49 (formerly 23, 25, 47) to reference TRADING_CONFIG -""" - -import json -import re - -notebook_path = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -print("=" * 70) -print("🔄 UPDATING CELLS TO USE TRADING_CONFIG") -print("=" * 70) -print() - -# Load notebook -with open(notebook_path, 'r', encoding='utf-8') as f: - notebook = json.load(f) - -print(f"Loaded notebook with {len(notebook['cells'])} cells") -print() - -changes_made = 0 - -# ============================================================================ -# CELL 25: calculate_position_size function -# ============================================================================ -print("📍 Updating Cell 25: calculate_position_size()") -print("-" * 70) - -cell_25 = notebook['cells'][25] -if cell_25['cell_type'] == 'code': - source = ''.join(cell_25['source']) - original = source - - # Update hardcoded 0.10 returns to use config - source = source.replace( - 'return 0.10', - 'return TRADING_CONFIG["lot_sizing"]["default_lot"]' - ) - - # Update function signature default parameter - source = source.replace( - 'def calculate_position_size(self, symbol, stop_loss_pips, max_risk_per_trade=0.02):', - 'def calculate_position_size(self, symbol, stop_loss_pips, max_risk_per_trade=None):' - ) - - # Add parameter default from config - if 'max_risk_per_trade=None):' in source: - # Add check at beginning of function - source = source.replace( - ' """\n Berechnet die Positionsgröße basierend auf Risiko\n """\n', - ' """\n Berechnet die Positionsgröße basierend auf Risiko\n """\n if max_risk_per_trade is None:\n max_risk_per_trade = TRADING_CONFIG["risk"]["max_risk_per_trade"]\n \n' - ) - - if source != original: - cell_25['source'] = source.split('\n') - changes_made += 1 - print("✅ Updated calculate_position_size to use TRADING_CONFIG") - print(f" - return 0.10 → TRADING_CONFIG['lot_sizing']['default_lot']") - print(f" - max_risk_per_trade default from config") - -# ============================================================================ -# CELL 27: execute_trade_v2_adaptive function -# ============================================================================ -print() -print("📍 Updating Cell 27: execute_trade_v2_adaptive()") -print("-" * 70) - -cell_27 = notebook['cells'][27] -if cell_27['cell_type'] == 'code': - source = ''.join(cell_27['source']) - original = source - - # Update function signature defaults - source = source.replace( - 'def execute_trade_v2_adaptive(\n symbol="XAUUSD",\n atr_mult=1.5,\n base_confidence=60,\n max_risk_per_trade=0.01,', - 'def execute_trade_v2_adaptive(\n symbol=None,\n atr_mult=None,\n base_confidence=None,\n max_risk_per_trade=None,' - ) - - # Add config loading at start of function - function_start = ' """\n V1.6 Adaptive Complete Trade-Ausführung:\n - Position Control\n - Relaxed Parameter\n - Adaptive Rhythm Integration\n """\n ' - - config_init = ''' """\n V1.6 Adaptive Complete Trade-Ausführung:\n - Position Control\n - Relaxed Parameter\n - Adaptive Rhythm Integration\n """\n \n # ========================================================================\n # LOAD DEFAULTS FROM TRADING_CONFIG\n # ========================================================================\n if symbol is None:\n symbol = TRADING_CONFIG["symbols"]["primary"]\n if atr_mult is None:\n atr_mult = TRADING_CONFIG["atr"]["base_multiplier"]\n if base_confidence is None:\n base_confidence = TRADING_CONFIG["confidence"]["base_threshold"]\n if max_risk_per_trade is None:\n max_risk_per_trade = TRADING_CONFIG["risk"]["max_risk_per_trade"]\n if max_positions is None:\n max_positions = TRADING_CONFIG["risk"]["max_positions"]\n \n ''' - - source = source.replace(function_start, config_init) - - # Update max_positions default - source = source.replace( - ' max_positions=1,', - ' max_positions=None,' - ) - - # Update volume calculations to use config - # Line with min(0.2, max(0.10, ... - source = source.replace( - 'volume = round(min(0.2, max(0.10, risk_amount / (adjusted_atr_mult * atr * 100))),2)', - 'volume = round(min(TRADING_CONFIG["lot_sizing"]["max_lot"], max(TRADING_CONFIG["lot_sizing"]["min_lot"], risk_amount / (adjusted_atr_mult * atr * 100))),2)' - ) - - # Hardcoded volume = 0.10 fallbacks - source = source.replace( - ' volume = 0.10', - ' volume = TRADING_CONFIG["lot_sizing"]["default_lot"]' - ) - - source = source.replace( - ' volume = 0.10', - ' volume = TRADING_CONFIG["lot_sizing"]["default_lot"]' - ) - - source = source.replace( - ' else:\n volume = 0.10', - ' else:\n volume = TRADING_CONFIG["lot_sizing"]["default_lot"]' - ) - - if source != original: - cell_27['source'] = source.split('\n') - changes_made += 1 - print("✅ Updated execute_trade_v2_adaptive to use TRADING_CONFIG") - print(f" - Function parameters now load from config") - print(f" - Volume calculations use config min/max/default") - print(f" - All hardcoded values replaced") - -# ============================================================================ -# CELL 49: ADAPTIVE_COMPLETE_CONFIG (now cell 49 after insertion) -# ============================================================================ -print() -print("📍 Updating Cell 49: ADAPTIVE_COMPLETE_CONFIG") -print("-" * 70) - -# Find the config cell (search for ADAPTIVE_COMPLETE_CONFIG) -config_cell_idx = None -for i, cell in enumerate(notebook['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell.get('source', [])) - if 'ADAPTIVE_COMPLETE_CONFIG' in source and "'max_risk_per_trade':" in source: - config_cell_idx = i - break - -if config_cell_idx is not None: - print(f"Found ADAPTIVE_COMPLETE_CONFIG at cell {config_cell_idx}") - cell = notebook['cells'][config_cell_idx] - source = ''.join(cell['source']) - original = source - - # Add comment and reference to centralized config - header_comment = '''# ============================================================================ -# NOTE: This config is DEPRECATED - use TRADING_CONFIG in Cell 6 instead -# This is kept for backward compatibility only -# ============================================================================ - -''' - - # Update max_risk_per_trade to reference centralized config - source = source.replace( - "'max_risk_per_trade': 0.02, # 2% risk", - "'max_risk_per_trade': TRADING_CONFIG['risk']['max_risk_per_trade'], # From centralized config" - ) - - if not source.startswith('# ====='): - source = header_comment + source - - if source != original: - cell['source'] = source.split('\n') - changes_made += 1 - print(f"✅ Updated ADAPTIVE_COMPLETE_CONFIG") - print(f" - Added deprecation notice") - print(f" - Linked max_risk_per_trade to TRADING_CONFIG") - -print() -print("=" * 70) -print(f"✅ CHANGES COMPLETE: {changes_made} cells updated") -print("=" * 70) -print() - -if changes_made > 0: - # Save notebook - with open(notebook_path, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - - print("✅ Notebook saved successfully!") - print() - print("📋 NEXT STEPS:") - print("=" * 70) - print() - print("1. Open Jupyter Notebook") - print("2. Restart Kernel (Kernel → Restart)") - print("3. Run cells in order:") - print(" a) Run Cell 6 (TRADING_CONFIG)") - print(" b) Run all other cells") - print("4. Verify bot uses 0.10 lot size") - print() - print("🎯 ALL SETTINGS NOW CENTRALIZED IN CELL 6!") - print() - print("To change lot size in future:") - print(" → Just edit TRADING_CONFIG['lot_sizing'] in Cell 6") - print(" → Restart kernel and re-run cells") - print() - print("=" * 70) -else: - print("⚠️ No changes were made") diff --git a/update_lot_size.py b/update_lot_size.py deleted file mode 100644 index 34f1707..0000000 --- a/update_lot_size.py +++ /dev/null @@ -1,76 +0,0 @@ -#!/usr/bin/env python3 -""" -Update Lot Size Configuration -Changes min_lot from 0.01 to 0.05 and max_lot to 0.20 -""" - -import json - -notebook_path = "TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb" - -print("=" * 70) -print("🔧 UPDATING LOT SIZE CONFIGURATION") -print("=" * 70) -print() - -# Load notebook -with open(notebook_path, 'r', encoding='utf-8') as f: - notebook = json.load(f) - -changes_made = 0 - -# Search and replace in all code cells -for i, cell in enumerate(notebook['cells']): - if cell['cell_type'] == 'code': - source = ''.join(cell['source']) - original_source = source - - # Replace common lot size patterns - replacements = [ - ('volume = 0.01', 'volume = 0.05'), - ('lot_size = 0.01', 'lot_size = 0.05'), - ('min_lot = 0.01', 'min_lot = 0.05'), - ('min_lot_size = 0.01', 'min_lot_size = 0.05'), - ('max_lot = 0.1', 'max_lot = 0.2'), - ('max_lot = 0.10', 'max_lot = 0.20'), - ('max_lot_size = 0.1', 'max_lot_size = 0.2'), - ('max_lot_size = 0.10', 'max_lot_size = 0.20'), - ] - - for old, new in replacements: - if old in source: - source = source.replace(old, new) - print(f"Cell {i}: {old} → {new}") - changes_made += 1 - - # Update cell if changed - if source != original_source: - cell['source'] = source.split('\n') - -print() - -if changes_made > 0: - # Save notebook - print(f"💾 Saving notebook with {changes_made} changes...") - with open(notebook_path, 'w', encoding='utf-8') as f: - json.dump(notebook, f, indent=1, ensure_ascii=False) - - print("✅ Notebook updated successfully!") - print() - print("📋 Changes made:") - print(" - Min Lot: 0.01 → 0.05") - print(" - Max Lot: 0.10 → 0.20") - print() - print("⚠️ WICHTIG:") - print(" 1. Lade dein Notebook neu (Kernel → Restart)") - print(" 2. Führe alle Cells neu aus") - print(" 3. Die neuen Lot-Größen werden ab dem nächsten Trade aktiv") -else: - print("❌ Keine Lot Size Parameter gefunden!") - print() - print("Die Lot-Größe wird wahrscheinlich dynamisch berechnet.") - print("Suche nach 'calculate_position_size' oder ähnlichen Funktionen") - print("im Notebook und ändere dort die Parameter manuell.") - -print() -print("=" * 70)