cbazza and Claude Sonnet 4.5
f9f4737b19
docs: Add bot analysis and performance report for January 2026
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Deploy to Windows VPS / deploy (push) Has been cancelled
Added comprehensive documentation:
- BOT_ANALYSIS_2026-01-10.md: Trading gap analysis (07-11 Jan)
- PERFORMANCE_REPORT_JAN_2026.md: Full performance metrics
- debug_bot_status.py: Debug script for bot status checks
Performance highlights:
- 74 trade signals over 5 days
- 92.90% average confidence
- 56.7% trades with ≥95% confidence
- News Filter successfully blocked NFP event
Analysis findings:
- Bot working correctly since 12.01
- Trading gap 08-11 Jan explained (NFP + weekend)
- Lot size increased to 0.10
Updated files:
- Notebook with latest trading state
- Performance JSON with new trades (12-13 Jan)
🤖 Generated with Claude Code
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com >
2026-01-14 12:10:07 +01:00
cbazza and Claude Sonnet 4.5
d3e54c6deb
fix: Correct lot size to 0.10 in all 3 locations
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Fixed all volume assignments in Cell 25:
- Line 106: min/max calculation (0.01→0.10, 0.1→0.2)
- Line 108: fallback volume (0.05→0.10)
- Line 110: default volume (0.05→0.10)
Previous commit only changed one location, bot kept using 0.01.
Now ALL volume settings use 0.10 as minimum.
Impact:
- 10x profit/loss per trade
- Pip value: $1.00 (was $0.10)
- Risk: ~2.9% per trade with 20 pip SL
🤖 Generated with Claude Code
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com >
2026-01-14 12:03:34 +01:00
cbazza and Claude Sonnet 4.5
9e0452ca8c
feat: Increase lot size from 0.01 to 0.05
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Changes:
- Min Lot: 0.01 → 0.05 (5x increase)
- Max Lot: 0.10 → 0.20 (2x increase)
Impact:
- Higher profit potential per trade
- More aggressive position sizing
- Risk still controlled by percentage
Cell 25 updated with new volume = 0.05
🤖 Generated with Claude Code
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com >
2026-01-13 09:30:11 +01:00
cbazza and Claude Sonnet 4.5
05b0d0b41b
update: Sync notebook changes
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Deploy to Windows VPS / deploy (push) Has been cancelled
- Notebook auto-updates during execution
- All changes synchronized
🤖 Generated with Claude Code
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com >
2026-01-08 17:56:29 +01:00
cbazza and Claude Sonnet 4.5
1af628cdc3
update: Notebook modifications after News Filter setup
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- Notebook updated after opening/execution
- News Filter cells 31-32 in place
- Ready for production use
🤖 Generated with Claude Code
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com >
2026-01-08 11:20:21 +01:00
cbazza and Claude Sonnet 4.5
af7a98d022
fix: Add News Filter cells 31-32 to notebook
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- Cell 31: News Filter Info (Markdown)
• Protection details
• Event schedule (NFP, CPI, FOMC)
• Expected impact ($400-600/month savings)
- Cell 32: News Filter Integration (Code)
• Wraps execute_trade_v2_adaptive
• Blocks trading 30min before/after high-impact news
• 5 events configured for January 2026
Notebook now has 74 total cells (was 72)
Status: Ready to activate - run Cell 32
🤖 Generated with Claude Code
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com >
2026-01-08 11:05:45 +01:00
cbazza and Claude Sonnet 4.5
773317f879
docs: Add News Filter activation status and checklist
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- Complete activation checklist
- Expected impact: $400-600/month savings
- Maintenance guide (5min/week)
- Next step: Run Cell 32 to activate
🤖 Generated with Claude Code
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com >
2026-01-08 10:21:23 +01:00
cbazza and Claude Sonnet 4.5
c5937b05ff
feat: Activate News Filter with January 2026 events
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- Added 5 high-impact USD news events for January 2026:
• NFP (Jan 9, 13:30 UTC)
• CPI (Jan 14, 13:30 UTC)
• Retail Sales (Jan 15, 13:30 UTC)
• FOMC Rate Decision (Jan 28, 19:00 UTC)
• FOMC Press Conference (Jan 28, 19:30 UTC)
- News Filter Cells 31-32 added to notebook
- activate_news_filter.py script created
- Filter blocks trading 30min before/after events
- Expected savings: $400-600/month from avoided news volatility
Status: News Filter READY TO ACTIVATE (run Cell 32)
🤖 Generated with Claude Code
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com >
2026-01-08 10:19:35 +01:00
cbazza
d15ec99918
Implement News Filter - High-Impact Event Protection
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Features:
- 3 versions: Simple (manual), Finnhub API, ForexFactory scraper
- 30min buffer before/after high-impact news
- Protects against volatile news losses (NFP, CPI, FOMC, etc.)
- Integration wrapper for execute_trade_v2_adaptive
Files:
- news_filter_simple.py - Manual event list (RECOMMENDED)
- news_filter_v2.py - Finnhub API version
- news_filter.py - ForexFactory scraper
- news_filter_integration.py - execute_trade wrapper
- NEWS_FILTER_GUIDE.md - Complete documentation
- news_events_manual.json - Event configuration template
- news_config.json - API configuration
Expected Impact:
- Prevents $400-600/month in news-related losses
- Blocks trading during NFP, CPI, FOMC events
- Minimal impact on trading time (~0.4%)
- High ROI for risk management
Status: Ready to activate
Recommendation: Add to notebook immediately
2026-01-08 09:57:54 +01:00
cbazza
d3a426edf4
Update notebook and add telegram debug tools
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Changes:
- Notebook updated with latest telegram bot integration
- Trade performance data updated
- Added debug_telegram_bot.md - troubleshooting guide
- Added test_telegram_bot.py - standalone test bot
Note: Telegram Bot now working with fixes applied
2025-12-26 21:42:28 +01:00
cbazza
d6ecc7605b
Fix Telegram Bot - disable job_queue and fix event loop
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Changes:
- Disable job_queue to avoid timezone/pytz error
- Fix event loop in background thread (use new_event_loop)
- Keep event loop running with run_forever()
- Add error handling in thread
Fixes: bot_thread was dying due to timezone error
Now: Thread stays alive and processes commands
2025-12-26 21:38:17 +01:00
cbazza
c061f234fa
Add immediate telegram installation instructions
2025-12-26 21:20:30 +01:00
cbazza
948211e711
Add telegram dependency installation cell to notebook
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Cell 27 now installs python-telegram-bot automatically
before the Telegram Bot Commander starts.
New cell structure:
- Cell 27: Dependency Installation (pip install)
- Cell 28: Telegram Bot Info (Markdown)
- Cell 29: Telegram Bot Commander (Start Bot)
- Cell 30: execute_trade Integration (Wrapper)
Instructions: Run Cell 27 first, then 29, then 30
2025-12-26 21:02:43 +01:00
cbazza
f537a16fd3
Add Telegram Bot Fix Guide and dependency installer
2025-12-26 20:14:36 +01:00
cbazza
9475730769
Update Telegram Bot to v22.x API (fix import error)
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Changes:
- Updated from python-telegram-bot 13.15 to 22.5
- Changed from sync API to async/await pattern
- Updated all command handlers to async
- Updated Application builder (new API)
- Fixed ModuleNotFoundError: No module named 'telegram'
Technical changes:
- Updater -> Application.builder()
- CommandHandler now uses async functions
- Context.DEFAULT_TYPE instead of CallbackContext
- await for all telegram API calls
Compatibility: python-telegram-bot 22.5 works with Python 3.12
2025-12-26 20:09:41 +01:00
cbazza
ac9a8ac969
Add Session Summary #2 - Telegram Bot Commands Implementation
2025-12-26 20:00:07 +01:00
cbazza
5a090d0346
Add Telegram Bot Quick Start Guide
2025-12-26 19:57:33 +01:00
cbazza
155ec1b524
Add Telegram Bot Commands - Remote Control Implementation
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Features:
- Remote control via Telegram commands
- /status - Bot status, positions, balance
- /pause - Pause trading (no new trades)
- /resume - Resume trading
- /close - Close all positions (emergency)
- /balance - Account balance & equity
- /stats - Performance statistics
- /help - Command help
Integration:
- Integrated into notebook (cells 27-29)
- Wrapped execute_trade_v2_adaptive with pause check
- Background service running parallel to bot
- MT5 integration for positions & balance
- Database integration for stats
Safety:
- Only authorized chat ID can send commands
- /close requires confirmation
- Instant pause/resume
Files:
- telegram_bot_commands.py - Main implementation
- setup_telegram_bot.py - Setup & installation
- TELEGRAM_BOT_COMMANDS_GUIDE.md - Complete documentation
- Notebook updated with 3 new cells (27-29)
Expected Impact: High - Full remote control from mobile phone
2025-12-26 19:50:12 +01:00
cbazza
95a112e238
Integrate session-specific confidence filter into notebook
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Added 2 new cells (25-26):
- Cell 25: Info markdown explaining the optimization
- Cell 26: Session confidence filter wrapper code
Changes:
- Wraps execute_trade_v2_adaptive with session-specific thresholds
- Asian: >=95% Confidence (unchanged, 97.8% WR)
- NY: >=97% Confidence (improves WR from 43.3% to 56.5%)
- Expected improvement: +$292/month, +3.2pp win-rate
Implementation:
- Auto-detects and wraps original function
- Preserves original in _original_execute_trade_v2_adaptive
- Clear console output showing active thresholds
- Ready to use immediately after kernel restart
Next step: Kernel -> Restart & Run All
2025-12-26 17:51:33 +01:00
cbazza
b5e596a96a
Add integration checklist for NY session fine-tuning
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Step-by-step guide to integrate session-specific confidence filter into notebook:
1. Add wrapper cell after execute_trade_v2_adaptive
2. Restart kernel
3. Verify thresholds
4. Monitor for 1 week
Includes:
- Exact code to add to notebook
- Expected output
- Verification steps
- Troubleshooting guide
- Success criteria
Ready for immediate deployment!
2025-12-26 17:48:50 +01:00
cbazza
ce197c06f4
Implement session-specific confidence thresholds (NY Fine-Tuning)
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FEATURE: Session-Specific Confidence Thresholds
- Asian: >=95% Confidence (unchanged, 97.8% WR)
- NY: >=97% Confidence (NEW, improves WR from 43.3% to 56.5%!)
- London/Overlap: Blocked (as before)
EXPECTED IMPACT:
- Eliminates 7 poor NY trades (all <97% confidence)
- NY Win-Rate: 43.3% → 56.5% (+13.2 pp)
- NY Profit: $1,418 → $1,655 (+$237)
- Total Profit: $8,306 → $8,598 (+$292)
- Overall Win-Rate: 67.8% → ~71%
IMPLEMENTATION:
1. session_filter_patch.py
- Added session_confidence_thresholds config
- New function: get_session_confidence_threshold()
- New function: is_confidence_sufficient()
2. session_confidence_filter.py (NEW)
- Wrapper for execute_trade_v2_adaptive
- Session-specific confidence checks
- Test suite (6/6 tests passed ✅ )
3. analyze_ny_session.py (NEW)
- Detailed NY session analysis
- Simulations for different thresholds
- Data shows 97-98% trades had 100% WR
TESTING:
All 6 test cases passed:
- Asian 96%: ALLOWED ✅
- Asian 94%: BLOCKED ✅
- NY 98%: ALLOWED ✅
- NY 96%: BLOCKED ✅
- London 99%: BLOCKED ✅
- Overlap 99%: BLOCKED ✅
NEXT STEPS:
1. Integrate wrapper into notebook
2. Restart kernel
3. Monitor for 1 week
4. Review performance improvement
FILES:
- session_filter_patch.py: Updated config + new functions
- session_confidence_filter.py: Wrapper implementation
- analyze_ny_session.py: Analysis tool
- NY_SESSION_FINETUNING.md: Complete documentation
2025-12-26 17:46:58 +01:00
cbazza
26d1802bb1
Add comprehensive performance analysis with key insights
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Performance Analysis Results (90 clean trades):
Overall Performance:
- Win Rate: 67.8% (61/90)
- Total Profit: $8,305.78
- Profit Factor: 4.19
- Avg Profit/Trade: $92.29
- Max Drawdown: -12.1%
KEY INSIGHT: Lot Size Reduction Success
- BEFORE (Nov 27 - Dec 4): 0.07-0.10 Lot → 0% WR, -$1,062 loss
- AFTER (Dec 10+): 0.01 Lot → 100% WR, +$9,368 profit
- Change was made Dec 4, results improved dramatically!
Session Performance:
- Asian: 97.8% WR, $150.93/trade (EXCELLENT!) 🌟
- NY: 46.4% WR, $53.16/trade (profitable but low WR)
- London: 12.5% WR (correctly blocked)
- Overlap: 14.3% WR (correctly blocked)
Confidence Analysis:
- 95-100%: 74.4% WR, 82 trades ✅
- 90-94%: 0% WR, 4 trades (all losses)
- 85-89%: 0% WR, 4 trades (all losses)
- Recommendation: Keep threshold at 95%+ (current excellent quality)
Monthly Trend:
- November: 6 trades, 0% WR, -$283 (testing phase)
- December: 84 trades, 72.6% WR, +$8,589 (optimized!)
Recommendations:
1. Keep current lot size (0.01) - working perfectly
2. Asian session is best performer (97.8% WR)
3. Current confidence threshold (95%+) is optimal
4. London/Overlap correctly blocked
5. System is well-optimized after December changes
2025-12-26 16:39:26 +01:00
cbazza
0a1086134c
Complete database cleanup and setup automated backups
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Phase 1: Historical Trades Cleanup ✅
- Deleted 240 historical trades with NULL profit
- Database now 100% clean: 90 valid trades only
- Backup created before deletion
- Result: 0 NULL profits, 0 unknown sessions
Phase 2: Automated Backup Setup ✅
- Created daily_backup.bat script
- Windows Task Scheduler configured
- Daily backups at 00:00 (midnight)
- 7-day backup rotation
- Next backup: 27.12.2025 00:00:00
Final Database Stats:
- Total Trades: 90 (all valid)
- Win Rate: 67.8% (61 wins / 29 losses)
- Total Profit: $8,305.78
- Profit Factor: 4.19
- Avg Win: $153.58
- Avg Loss: $-36.65
Backups created:
1. backups/trading_bot_before_cleanup_20251226_162438.db
2. backups/trading_bot_before_historical_cleanup_20251226_162934.db
3. backups/trading_bot_daily_20251226.db
All data quality issues resolved!
2025-12-26 16:31:35 +01:00
cbazza
23f0a4c800
Add database cleanup and backup automation
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Created comprehensive database maintenance tools:
1. database_cleanup.py (✅ EXECUTED)
- Fixed 102 unknown sessions → assigned to correct sessions
- Revealed true win rate: 67.8% (not 18.5%!)
- Created automatic backup before changes
2. cleanup_historical_trades.py
- Handles 240 'historical' trades with NULL profit
- 3 options: Delete / Mark / Set to breakeven
- Interactive selection with backup
3. setup_automated_backup.py
- Daily automated backups
- Windows Task Scheduler integration
- 7-day backup rotation
- Manual backup option
Results after cleanup:
- ✅ Unknown sessions: 0 (was 102)
- ✅ Session distribution: asian 132, ny 64, overlap 75, london 58
- ✅ Win rate: 67.8% (61 wins / 90 trades)
- ✅ Backup created: trading_bot_before_cleanup_20251226_162438.db
- ⏳ 240 historical trades pending decision (recommend delete)
Next steps:
1. Run cleanup_historical_trades.py (option 1: delete)
2. Setup automated backups via Task Scheduler
3. Re-analyze performance with correct session data
2025-12-26 16:28:07 +01:00
cbazza
a86f42b48c
Add comprehensive improvement status analysis for 2025
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Analysis of current system:
- ✅ Implemented features (Multi-TF Filter, Adaptive Sizing, etc.)
- 🚨 Problems found (all trades 98-100% confidence, database inconsistencies)
- 🎯 Recommended improvements (Confidence threshold, Telegram commands, News filter)
- 📊 Performance analysis (Asian session 7/trade, Total profit ,306)
Key findings:
- Adaptive Position Sizing not showing effect (all trades excellent quality)
- 240 trades missing win/loss status in database
- 102 trades with 'unknown' session
- Need to adjust confidence thresholds to enable medium-quality trades
Priority recommendations:
1. Adjust confidence thresholds (enable 75-97% trades)
2. Implement Telegram bot commands
3. Database cleanup & backup automation
4. News filter integration
2025-12-26 16:20:24 +01:00
cbazza
90ec9c5948
Add missing position sizing documentation and notebook session filter import
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- POSITION_SIZING_UPDATE.md: Documentation from earlier commit
- Notebook: Added SESSION_WHITELIST_CONFIG import in Cell 9 for base_risk parameter
2025-12-26 12:44:54 +01:00
cbazza
98e1c026df
Add activation status documentation and PowerShell autostart script
2025-12-24 16:45:04 +01:00
cbazza
d2c56a8636
Fix: Adaptive Position Sizing now uses base_risk from config
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PROBLEM:
- AdaptivePositionSizer was created with default base_risk=0.01 (1%)
- Did NOT use the 2% value from SESSION_WHITELIST_CONFIG
- Result: Position sizes still only 0.01 lot
SOLUTION:
- Added base_risk parameter to AdvancedPositionManager.__init__()
- Updated notebook Cell 9 to pass SESSION_WHITELIST_CONFIG['max_risk_per_trade']
- Now correctly uses 2% base risk for adaptive sizing
EXPECTED RESULT:
- High Confidence (≥80%): 2% × 1.5 = 3% → ~0.03 Lot
- Medium Confidence (≥70%): 2% × 1.0 = 2% → ~0.02 Lot
- Low Confidence (<70%): 2% × 0.5 = 1% → ~0.01 Lot
FILES CHANGED:
- advanced_position_management.py: Added base_risk parameter
- TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb: Pass config value to manager
2025-12-24 16:43:27 +01:00
cbazza
c685bdf83f
Add Dashboard Autostart Setup for Windows
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- start_dashboard.bat: Manual start with console output
- start_dashboard_silent.bat: Silent background start
- install_dashboard_autostart.bat: One-click autostart installation
- uninstall_dashboard_autostart.bat: Remove autostart
- DASHBOARD_AUTOSTART_SETUP.md: Complete documentation
Features:
- Automatic startup on Windows login
- Opens browser at http://localhost:8501
- Silent background execution
- Easy install/uninstall
- Troubleshooting guide included
2025-12-23 11:02:35 +01:00
cbazza
a1b5d6a190
Increase base risk from 1% to 2% for better position sizing
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- Changed max_risk_per_trade from 0.01 to 0.02
- Enables Adaptive Position Sizing to work effectively:
- High confidence (≥80%): 3% risk → ~0.03 lot
- Medium confidence (≥70%): 2% risk → ~0.02 lot
- Low confidence (<70%): 1% risk → ~0.01 lot
- Previous 1% base risk resulted in only 0.01 lot trades
2025-12-23 09:27:49 +01:00
cbazza
d03453e834
Add activation checklist for multi-TF filter
Deploy to Windows VPS / deploy (push) Has been cancelled
2025-12-20 19:17:40 +01:00
cbazza
39cefd315c
Integrate Multi-TF Filter into Notebook
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- Cell 25: Info Markdown über neue Lösung
- Cell 26: Alter Filter deaktiviert (auskommentiert)
- Cell 27: Neuer Multi-TF Filter aktiviert
- Cell 28: Test-Cell zum Verifizieren
Ready to run!
2025-12-20 19:16:14 +01:00
cbazza
e9b6662547
Fix: Multi-Timeframe Ranging Filter - Löst Problem mit blockierten Trades
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- Problem: Alter Filter nutzte nur H1 (ADX 9.90) und blockierte Trades
- Gold war aber auf D1 im Trend (ADX 28.25)
- Lösung: Multi-TF Filter prüft H1, H4, D1 mit Gewichtung
- Neue Logik: D1 > H4 > H1, intelligente Entscheidung
- Dokumentation: Installation, Problemanalyse, Lösung
Files:
- multi_timeframe_regime_filter.py: Neuer Filter
- MULTI_TF_FILTER_INSTALLATION.md: Installationsanleitung
- PROBLEM_GELOEST.md: Zusammenfassung
- PROBLEM_ANALYSE.md: Detaillierte Diagnose
2025-12-20 19:13:13 +01:00
cbazza
f3041dbb01
Update: sync latest notebook and add December 2025 trade performance data
Deploy to Windows VPS / deploy (push) Has been cancelled
2025-12-20 18:21:15 +01:00
cbazza
bb180acf7a
Add setup scripts and documentation for Git workflow
Deploy to Windows VPS / deploy (push) Has been cancelled
2025-12-20 18:12:39 +01:00
cbazza
16790d1807
Remove Windows Zone.Identifier file that causes issues on Windows
Deploy to Windows VPS / deploy (push) Has been cancelled
2025-12-20 18:05:23 +01:00
cbazza
17e6fb83e5
added GITEA Actions and setup
Deploy to Windows VPS / deploy (push) Has been cancelled
2025-12-17 08:34:55 +01:00
cbazza
cbd6584db5
all changes done over the last 2 weeks
2025-12-16 22:02:15 +01:00
cbazza and Claude
596718e30b
feat: Trading Bot V1.8 - Aggressive Mode + Infrastructure
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## Major Features
- Session Filter: NY-only trading (13:00-21:00 UTC)
- SQLite Database: Structured trade logging
- Telegram Bot: Real-time notifications (@Xausd_digger_bot)
- Streamlit Dashboard: Visual monitoring & analytics
- JSON Import: Historical data migration
## Infrastructure
- trading_database.py: SQLite trade storage
- telegram_notifier.py: Telegram integration
- infrastructure_patch.py: Combined DB + Telegram
- trading_dashboard.py: Real-time web dashboard
- import_json_to_db.py: JSON to SQLite migration
## Session Filter (V1.8 Aggressive Mode)
- session_filter_patch.py: Whitelist-based filter
- Blocks: Asian, London, Overlap sessions
- Active: NY session only (best performance: 47.6% WR)
- Base confidence: 60%
## Documentation
- V1.8_AGGRESSIVE_MODE_AKTIVIERT.md
- FIX_DUPLICATE_SCHEDULER.md
- DASHBOARD_WINDOWS_SERVER.md
- SQLITE_TELEGRAM_SETUP.md
- PROJECT_CLEANUP.md
## Cleanup
- Archived old V1.1-V1.7 versions
- Removed obsolete analysis scripts (replaced by dashboard)
- Added .gitignore for secrets and temp files
## Breaking Changes
- Requires telegram_config.json (use template)
- Requires Python packages: streamlit, plotly
🤖 Generated with [Claude Code](https://claude.com/claude-code )
Co-Authored-By: Claude <noreply@anthropic.com >
2025-11-26 21:14:01 +01:00
cbazza
b61cb9b8f9
many ki generated scripts and versions added
2025-09-24 09:36:36 +02:00
cbazza
13f64c5211
latest version 1.3
2025-09-16 13:30:07 +02:00
cbazza
f7b72f0145
Trading Bot V1.3 added
2025-09-11 17:34:32 +02:00
cbazza
5553cb8db7
tradng Bot V1.1 added
2025-09-03 23:17:02 +02:00
cbazza
b74d05c6ce
every new file till today
2025-05-27 13:23:26 +02:00
cbazza
3e6beb7b3b
added workfile to manage pwds and save them to the os keyring
2025-04-27 11:26:30 +02:00
cbazza
e52fc7a87b
manuelle Korrektur Volumen und neue Berechnung FB1-4 sowie current diff hinzugefügt
2025-04-27 10:23:00 +02:00
cbazza
7487234e81
added v01
2025-04-25 15:27:30 +02:00