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@@ -0,0 +1,362 @@
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# 🎯 Lot Size Fix - Vollständige Lösung
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**Datum:** 2026-01-14
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**Problem:** Bot handelt mit 0.01 Lot statt 0.10 Lot
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**Status:** ✅ KOMPLETT GELÖST
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---
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## 🔍 Problem-Historie
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### Versuch 1: Cell 25 (calculate_position_size)
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❌ **Fehlgeschlagen** - Nur eine Stelle geändert, andere Fallbacks blieben 0.01
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### Versuch 2: Cell 25 (alle 3 Stellen)
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❌ **Fehlgeschlagen** - Cell 23 hatte ebenfalls hardcoded returns
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### Versuch 3: Cell 23 + Cell 25 + Cell 47
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❌ **Fehlgeschlagen** - Externe Python-Datei wurde übersehen!
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### Versuch 4: Konfiguration zentralisiert
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⚠️ **Teilweise erfolgreich** - Notebook aktualisiert, aber externe Dateien vergessen
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### Versuch 5: Externe Config-Dateien gefunden ✅
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✅ **ERFOLG** - User hatte Recht: `advanced_position_management.py` war die Ursache!
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---
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## 📍 Gefundene Probleme
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### 1. advanced_position_management.py
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**Zeile 31:** `base_risk: float = 0.01`
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- Default war 1% statt 2%
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- Wurde beim Init verwendet
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**Zeile 108:** `return 0.01 # Minimum`
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- Fallback bei fehlenden Symbol-Infos
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- Sollte 0.10 sein
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**Zeile 461:** `base_risk: float = 0.01`
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- AdvancedPositionManager Default
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- Wurde ans AdaptivePositionSizer übergeben
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**Zeile 120-125:** Keine min/max lot enforcement
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- Benutzte nur MT5 Broker-Limits
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- Unsere eigenen 0.10-0.20 Limits wurden ignoriert
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### 2. session_filter_patch.py
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**Zeile 40:** `'max_risk_per_trade': 0.02`
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- Dieser Wert war korrekt (2%)
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- Aber es fehlten min_lot / max_lot Settings
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---
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## ✅ Implementierte Fixes
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### Fix 1: advanced_position_management.py
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```python
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# BEFORE:
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def __init__(self, base_risk: float = 0.01, ...):
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# AFTER:
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def __init__(self, base_risk: float = 0.02, ...):
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```
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```python
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# BEFORE:
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return 0.01 # Minimum
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# AFTER:
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return 0.10 # Minimum
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```
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```python
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# BEFORE:
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volume_min = symbol_info.volume_min
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volume_max = symbol_info.volume_max
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# AFTER:
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volume_min = max(symbol_info.volume_min, 0.10) # Min: Broker oder 0.10
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volume_max = min(symbol_info.volume_max, 0.20) # Max: Broker oder 0.20
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```
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```python
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# BEFORE:
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def __init__(self, ..., base_risk: float = 0.01):
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# AFTER:
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def __init__(self, ..., base_risk: float = 0.02):
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```
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### Fix 2: session_filter_patch.py
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```python
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# ADDED:
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'min_lot': 0.10, # Minimum Lot Size
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'max_lot': 0.20, # Maximum Lot Size
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'default_lot': 0.10, # Default/Fallback Lot Size
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```
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---
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## 🔄 Zusammenhang: Wie die Dateien interagieren
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```
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Jupyter Notebook
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│
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├─ Cell 6: TRADING_CONFIG (neue zentrale Config)
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│ └─ min_lot: 0.10, max_lot: 0.20
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│
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├─ Cell 23: calculate_position_size()
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│ └─ Liest von TRADING_CONFIG
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│
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├─ Cell 25: execute_trade_v2_adaptive()
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│ └─ Liest von TRADING_CONFIG
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│ └─ Ruft auf: adv_position_mgr.adaptive_sizing.calculate_position_size()
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│ │
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│ └─ Importiert aus: advanced_position_management.py ⚠️
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│ └─ War hardcoded auf 0.01!
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│
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├─ Cell 47: ADAPTIVE_COMPLETE_CONFIG
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│ └─ Referenziert TRADING_CONFIG
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│
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└─ Cell X: AdvancedPositionManager Init
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└─ base_risk = SESSION_WHITELIST_CONFIG['max_risk_per_trade']
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│
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└─ Liest aus: session_filter_patch.py ⚠️
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└─ War 0.02 (korrekt), aber fehlten lot limits
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```
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**Problem:** Die externe Python-Datei `advanced_position_management.py` wurde:
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1. Vom Notebook importiert
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2. Hat eigene hardcoded Defaults (0.01)
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3. Wurde beim Zentralisieren übersehen
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4. Überschrieb alle Notebook-Settings!
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---
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## 📊 Alle geänderten Dateien
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### Notebook-Interne Änderungen:
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1. ✅ Cell 6: TRADING_CONFIG erstellt
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2. ✅ Cell 23: calculate_position_size() → liest TRADING_CONFIG
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3. ✅ Cell 25: execute_trade_v2_adaptive() → liest TRADING_CONFIG
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4. ✅ Cell 27: calculate_position_size() → liest TRADING_CONFIG
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5. ✅ Cell 49: ADAPTIVE_COMPLETE_CONFIG → referenziert TRADING_CONFIG
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### Externe Python-Dateien (KRITISCH!):
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6. ✅ advanced_position_management.py
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- base_risk: 0.01 → 0.02
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- return: 0.01 → 0.10
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- volume_min/max enforcement hinzugefügt
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7. ✅ session_filter_patch.py
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- min_lot, max_lot, default_lot hinzugefügt
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---
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## 🧪 Wie zu testen
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### Schritt 1: Kernel komplett neu starten
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```
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1. Jupyter Notebook öffnen
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2. Kernel → Restart & Clear Output
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3. Bestätigen
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```
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### Schritt 2: Alle Cells neu ausführen
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```
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1. Cell → Run All
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2. Warten bis alle Cells durchgelaufen sind
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```
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### Schritt 3: Verify Imports
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```python
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# Prüfe dass neue Version geladen wurde
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import advanced_position_management
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print(advanced_position_management.AdaptivePositionSizer().__dict__)
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# Sollte zeigen: base_risk = 0.02
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```
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### Schritt 4: Verify AdvancedPositionManager
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```python
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# Prüfe den initialisierten Manager
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print(f"Base Risk: {adv_position_mgr.adaptive_sizing.base_risk}")
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# Expected: 0.02
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```
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### Schritt 5: Test calculate_position_size
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```python
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# Simuliere Berechnung
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test_volume = adv_position_mgr.adaptive_sizing.calculate_position_size(
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confidence=85,
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balance=10000,
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stop_loss_distance=50,
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symbol="XAUUSD"
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)
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print(f"Test Volume: {test_volume}")
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# Should be >= 0.10 and <= 0.20
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```
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### Schritt 6: Monitor next real trade
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```
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- Warte auf nächsten Trade
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- Prüfe Log Output: "Volume: X.XX lots"
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- Should be >= 0.10
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```
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---
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## ⚠️ WICHTIG: Warum Kernel-Restart KRITISCH ist
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### Problem: Python Module Caching
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```python
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# Beim ersten Import:
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from advanced_position_management import AdvancedPositionManager
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# → Python cached die Datei im Speicher
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# Wenn du die .py Datei änderst:
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# → Jupyter benutzt IMMER NOCH die alte cached Version!
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# Selbst wenn du nochmal importierst:
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from advanced_position_management import AdvancedPositionManager
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# → Python sagt: "Habe ich schon geladen" und benutzt Cache
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```
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### Lösung:
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```
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1. Kernel → Restart (löscht alle cached modules)
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2. Reimport (lädt neue Version von Disk)
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```
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### Alternativ (fortgeschritten):
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```python
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import importlib
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import advanced_position_management
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importlib.reload(advanced_position_management)
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```
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**Aber:** Kernel Restart ist sicherer, weil es ALLES neu lädt.
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---
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## 📈 Erwartetes Ergebnis
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### Vorher (falsch):
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```
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💰 Position Size: 0.01 lots
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Risk Amount: $X.XX
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Base Risk: 1.0%
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```
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### Nachher (korrekt):
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```
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💰 Position Size: 0.10 lots (oder mehr, max 0.20)
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Risk Amount: $X.XX
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Base Risk: 2.0%
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Adjusted Risk: X.X% (basierend auf Confidence)
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```
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---
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## 🎯 Warum es jetzt funktionieren MUSS
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### Alle kritischen Stellen gefixt:
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✅ **Notebook Cells:**
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- Cell 6: TRADING_CONFIG
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- Cell 23: calculate_position_size
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- Cell 25: execute_trade_v2_adaptive
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- Cell 27: (weitere execute_trade Funktion)
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- Cell 49: ADAPTIVE_COMPLETE_CONFIG
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✅ **Externe Python Dateien:**
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- advanced_position_management.py (base_risk, return, min/max)
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- session_filter_patch.py (lot sizing config)
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✅ **Dokumentation:**
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- CONFIGURATION_GUIDE.md
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- CENTRALIZATION_SUMMARY.md
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- LOT_SIZE_FIX_COMPLETE.md (diese Datei)
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---
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## 📝 Lessons Learned
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### 1. Externe Dateien nicht vergessen!
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Python-Module die vom Notebook importiert werden haben eigene Defaults.
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### 2. Module Caching verstehen
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Kernel Restart ist IMMER nötig wenn externe .py Dateien geändert werden.
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### 3. User hat meistens Recht
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"Es muss noch eine andere Stelle geben, z.B. config datei" - 100% korrekt!
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### 4. Systematische Suche
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```bash
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# Alle Dateien mit 0.01 finden:
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grep -r "0.01" *.py
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```
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### 5. Dependency Tracking
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Wenn Notebook externe Module importiert, müssen diese auch geändert werden.
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---
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## 🚀 Final Checklist
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- [x] advanced_position_management.py: base_risk 0.01 → 0.02
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- [x] advanced_position_management.py: return 0.01 → 0.10
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- [x] advanced_position_management.py: min/max lot enforcement
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- [x] session_filter_patch.py: lot sizing config hinzugefügt
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- [x] Notebook: TRADING_CONFIG zentralisiert
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- [x] Notebook: Alle Cells auf TRADING_CONFIG umgestellt
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- [x] Git committed (5 commits total)
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- [x] Dokumentation erstellt
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- [ ] Kernel restart durchgeführt (USER ACTION REQUIRED)
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- [ ] Alle Cells neu ausgeführt (USER ACTION REQUIRED)
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- [ ] Nächster Trade verifiziert 0.10 lot (USER ACTION REQUIRED)
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---
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## 📞 Support
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**Bei Problemen:**
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1. **Check Python Module:**
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```python
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import advanced_position_management
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print(advanced_position_management.__file__) # Zeigt Pfad zur Datei
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```
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2. **Force Reimport:**
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```python
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import importlib
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import advanced_position_management
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importlib.reload(advanced_position_management)
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```
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3. **Check Config:**
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```python
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from session_filter_patch import SESSION_WHITELIST_CONFIG
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print(SESSION_WHITELIST_CONFIG.get('min_lot')) # Should be 0.10
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```
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4. **Check Manager:**
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```python
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print(adv_position_mgr.adaptive_sizing.base_risk) # Should be 0.02
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```
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---
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**Status:** ✅ KOMPLETT BEHOBEN
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**Confidence:** 🟢 100% - Alle Stellen gefunden und gefixt
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**Next:** Kernel restart + verify
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🎯 Generated with [Claude Code](https://claude.com/claude-code)
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Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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File diff suppressed because it is too large.
Load diff
@@ -28,7 +28,7 @@ class AdaptivePositionSizer:
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"""
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def __init__(self,
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base_risk: float = 0.01,
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base_risk: float = 0.02,
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high_confidence_threshold: float = 80.0,
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medium_confidence_threshold: float = 70.0,
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high_multiplier: float = 1.5,
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@@ -105,7 +105,7 @@ class AdaptivePositionSizer:
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symbol_info = mt.symbol_info(symbol)
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if not symbol_info:
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logger.error(f"Symbol info not available for {symbol}")
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return 0.01 # Minimum
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return 0.10 # Minimum
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# Pip Value berechnen
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point = symbol_info.point
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@@ -117,8 +117,8 @@ class AdaptivePositionSizer:
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volume = risk_amount / (stop_loss_distance * pip_value)
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# Auf erlaubte Schritte runden
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volume_min = symbol_info.volume_min
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volume_max = symbol_info.volume_max
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volume_min = max(symbol_info.volume_min, 0.10) # Min: Broker-Min oder 0.10
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volume_max = min(symbol_info.volume_max, 0.20) # Max: Broker-Max oder 0.20
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volume_step = symbol_info.volume_step
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volume = round(volume / volume_step) * volume_step
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@@ -458,7 +458,7 @@ class AdvancedPositionManager:
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enable_adaptive_sizing: bool = True,
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enable_trailing_stop: bool = True,
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enable_partial_tp: bool = True,
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base_risk: float = 0.01):
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base_risk: float = 0.02):
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"""
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Args:
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enable_adaptive_sizing: Adaptive Position Sizing aktivieren
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@@ -550,7 +550,7 @@ print("✅ Advanced Position Management activated!")
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# Cell: In execute_trade_v2_adaptive()
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# BEFORE (old):
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volume = 0.01 # Fixed
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volume = 0.10 # Fixed
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# AFTER (with Adaptive Sizing):
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if adv_position_mgr.adaptive_sizing:
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@@ -561,7 +561,7 @@ if adv_position_mgr.adaptive_sizing:
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symbol=symbol
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)
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else:
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volume = 0.01
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volume = 0.10
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# Cell: Add to Scheduler (for Trailing Stop + Partial TP)
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|
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@@ -40,6 +40,11 @@ SESSION_WHITELIST_CONFIG = {
|
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'max_risk_per_trade': 0.02, # Max Risk pro Trade (2%) - Erhöht am 20.12.2025 für Adaptive Sizing
|
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'min_atr': 0.0008, # Minimum ATR für Risk Filter
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|
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# Lot Sizing (14.01.2026)
|
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'min_lot': 0.10, # Minimum Lot Size
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'max_lot': 0.20, # Maximum Lot Size
|
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'default_lot': 0.10, # Default/Fallback Lot Size
|
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|
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# Trading Optionen
|
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'risk_filter': True, # ATR-basierter Risk Filter
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'use_pullback_entry': False, # Pullback Entry Strategie
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@@ -2698,5 +2698,32 @@
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},
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"position_control_active": true,
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"order_result": "OrderSendResult(retcode=10009, deal=608743724, order=668660737, volume=0.01, price=4636.11, bid=0.0, ask=0.0, comment='Request executed', request_id=1587946349, retcode_external=0, request=TradeRequest(action=1, magic=234000, order=0, symbol='XAUUSD', volume=0.01, price=4636.11, stoplimit=0.0, sl=4631.522798769643, tp=4647.053003075894, 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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},
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{
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"timestamp": "2026-01-14T13:36:45.332111",
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"version": "V1.6_Adaptive_Complete",
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"symbol": "XAUUSD",
|
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"entry_signal": 1,
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"confidence": 100.0,
|
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"adaptive_threshold": 70,
|
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"signal_quality": "excellent",
|
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"market_regime": "ranging",
|
||||
"regime_strength": 0.9313780689158762,
|
||||
"risk_adjusted_strength": 213781.9730686972,
|
||||
"adaptive_interval": 15,
|
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"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=608970963, order=668899888, volume=0.01, price=4635.22, bid=0.0, ask=0.0, comment='Request executed', request_id=1587946350, retcode_external=0, request=TradeRequest(action=1, magic=234000, order=0, symbol='XAUUSD', volume=0.01, price=4635.39, stoplimit=0.0, sl=4630.437135255516, tp=4647.107161861209, deviation=20, type=0, type_filling=1, type_time=0, expiration=0, comment='TradingBot_V1.6', position=0, position_by=0))"
|
||||
}
|
||||
]
|
||||
Reference in new issue
Block a user