Enhance PositionGuard in SmartRiskManager with real-time profit velocity
($/s) and acceleration ($/s²) tracking for smarter exit decisions.
Changes:
- Add 7 velocity/acceleration fields to PositionGuard dataclass
- Add _calculate_velocity_acceleration(), _update_stagnation(), get_velocity_summary()
- Add 4 new exit checks: [VEL-EXIT], [DECEL], [VEL-WARN], [STAGNANT]
- Enhance early cut with velocity trigger alternative (vel < -0.4)
- Stricter profit_growing: requires momentum > 0 AND velocity > 0
- Reduce position check interval 10s → 5s for more data points
- Add per-ticket [MOMENTUM] log every 30s in main loop
- Revert unused momentum_tracker integration from position_manager
- Add deprecation note to profit_momentum_tracker.py
All velocity checks respect the 15-minute grace period.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add 15-min grace period before early cut (wait 1 M15 candle to develop)
- Replace equity chart with AI Assistant card (real-time insights in Indonesian)
- Merge filter toggles into EntryFilterCard (remove separate FiltersConfigCard)
- Fix filter config API URL typo (8001 → 8000)
- Fix tooltip blocking switch clicks (move Switch outside TooltipTrigger)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
**H1 Bias Fix:**
- Fixed cache check to ensure loop_count=1 always calculates H1 bias
- Changed exception log from DEBUG to WARNING for visibility
- Added log on first calculation (loop==1) in addition to every 4 loops
- Result: H1 bias now correctly calculated from first candle
**Filter Config Infrastructure (WIP):**
- Added FilterConfigManager (src/filter_config.py) for dynamic filter control
- Added data/filter_config.json with 11 entry filters (flash_crash, regime, risk, session, spread, h1_bias, ml_confidence, signal_combination, cooldown, time_filter, market_close)
- Added API endpoints: GET/POST /api/filters/config
- Note: Bot integration pending — requires wrapper around all filter checks
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Dark mode: class-based theme toggle with localStorage persistence and flash prevention
- Trade History (/trades): paginated table, stats cards, equity curve chart with DB API endpoints
- Backtest Viewer (/backtests): log parser for 35 backtest results, sidebar + detail + comparison tabs
- Model Insights: dashboard card + dialog showing feature importance, regime distribution, training history
- Alert/Signal Log (/alerts): signal stats, filterable table with execution tracking
- API: 8 new endpoints with psycopg2 DB connection pool
- Dark mode sweep across books page, about dialog, and all dashboard components
- Architecture docs rewritten with Mermaid diagrams (23 docs)
- README and FEATURES.md rewritten bilingual (Indonesian + English)
- main_live.py: write model_metrics.json on startup and retrain
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Fix 'dict' has no attribute 'spread' by using .get("spread", 0)
- Add 3-retry loop to close_position() with fresh price each attempt
- Match retry pattern from send_order() for consistency
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Major Issue #1: Confidence Calculation Calibration
- Added calculate_confidence() method with weighted scoring
- Base 40% + Structure 15% + BOS/CHoCH 12% + FVG 8% + OB 10% + Trend 10%
- Capped at 85% (never 100% certain)
Major Issue #2: Pullback Filter ATR-based
- Replaced hardcoded $2, $1.5 thresholds
- Now uses bounce_threshold = 0.15 * ATR
- consolidation_threshold = 0.10 * ATR
Major Issue #3: Smarter Time-based Exit
- Don't cut winners short if profit growing
- Check ML agreement before timeout
- Extend time to 8h if profit > $10 and growing
Major Issue #4: Slippage Validation
- Check actual vs expected price after execution
- Log warning if slippage > 0.15% of price
- Use actual price for position tracking
Major Issue #5: Partial Fill Handling
- Check if filled volume < requested volume
- Log warning with fill ratio
- Use actual volume for position tracking
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
main_live.py:
- Switch main loop from time-based (1s) to candle-based (M15)
- Add position-only checks between candles (every 10s)
- Fix memory leak in signal persistence dict (cleanup stale entries)
- Raise auto-retrain rollback AUC threshold from 0.52 to 0.60
src/ml_model.py:
- Add 50-bar gap between train/test split to prevent temporal leakage
src/smart_risk_manager.py:
- Remove dangerous "Smart Hold" behavior (holding losers waiting for golden time)
- Replace with proper early cut logic (loss >30% + negative momentum)
src/smc_polars.py:
- Fix lookahead bias in FVG detection (remove shift(-1), use confirmed bars only)
- Fix lookahead bias in Swing Points (use center=False rolling window)
- Fix lookahead bias in Order Blocks (validate with current bar, not future)
- Enforce minimum 1:2 Risk:Reward ratio on all signals
- Always use current_close as entry price (no stale FVG/OB zone prices)
- Add ATR sanity check with realistic XAUUSD default ($12)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- XGBoost ML model with 37 features for market direction prediction
- Smart Money Concepts (SMC): Order Blocks, FVG, BOS, CHoCH
- HMM market regime detection (trending/ranging/volatile)
- ATR-based stop loss with 1.5 ATR minimum distance
- Broker-level SL protection with fallback
- Time-based exit (max 6 hours per trade)
- Session-aware trading optimized for London/NY overlap
- Auto-retraining based on market conditions
- Telegram notifications and web dashboard
- Backtest results: 63.9% win rate, 2.64 profit factor, 4.83 Sharpe
Backtest period: Jan 2025 - Feb 2026, 654 trades, $4,189 net P/L
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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