 Brent Neale
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072ac0f245
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Phase 2: Live paper trading engine + extended backtesting analytics
Track A — Live paper trading system:
- Extract PositionManager from backtester into shared src/position_manager.py
- Refactor backtester/engine.py to delegate to PositionManager
- New src/live/ package: data_feed (OANDA polling), executor (paper/live orders),
engine (LiveEngine orchestrator with 5 strategy slots), run.py entry point
- Add phase2 config to system.yaml (S7_Tight, S9, S9_Filtered, S4F, S3)
Track B — Extended backtesting analytics:
- Regime analysis: per-year (2021-2023) breakdown shows 4/5 strategies trending UP
- Correlation analysis: S7+S3 GBP_JPY overlap=16.9% (moderate), S9 pairs=12% (low)
- Kelly sizing: S9_Filtered half-Kelly=7.3%, S4F=2.4%, S3=1.6% with Monte Carlo DD
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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2026-02-19 14:46:51 +10:00 |
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Brent Neale
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39a6536284
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Phase 1 complete: S7-S9 Smart Money strategies, expanded pair testing, consolidated scorecard
- S7 Liquidity Sweep: built, tested across 6 pairs, tight SL (1.0 ATR) on GBP_JPY
is Phase 2 candidate (107 trades, OOS PF 1.39, gen ratio 1.81)
- S8 Order Block: built, tested on GBP_JPY (watchlist, 32 trades, OOS PF 1.55)
- S9 London Session: built, tested across 8 pairs with filter experiments
GBP_USD (OOS PF 1.45) and GBP_AUD filtered (OOS PF 1.94) advance to Phase 2
- Added OBV indicator to technical.py
- Added GBP_NZD to engine spread/pip config
- Standalone OANDA fetcher (bypasses Supabase dependency)
- Fetched EUR_GBP, EUR_USD, GBP_NZD H1 data (2021-2023)
- Consolidated STRATEGY_LEARNINGS.md with full Phase 1 scorecard and 11 design principles
- Phase 2 roster: S7/GBP_JPY, S9/GBP_USD, S9F/GBP_AUD, S4-F/EUR_AUD, S3/GBP_JPY
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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2026-02-19 13:56:03 +10:00 |
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Brent Neale
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edbe359d1b
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Phase 1 complete: S3-S6 strategies, S4 variant analysis, learnings doc
- S3 Key Level Breakout: best performer (52-53% WR, PF ~1.0 on JPY crosses)
- S4 EMA Ribbon: tested 7 variants (D/E/F/F-v2/G/G-Minimal), exhausted
- Only EUR_AUD S4-F marginally profitable (PF 1.06)
- Detailed filter funnel analysis revealed contradictory filter stacking
- S5 Momentum Exhaustion: extended to 5 pairs, PF 0.43-0.77
- S6 EMA Bounce: 59-60% WR but PF 0.83-0.84, needs SL/TP restructuring
- Added STRATEGY_LEARNINGS.md with design principles and next steps
- Added M5 data downloader for 3-timeframe strategies
- Updated README with full strategy scorecard
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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2026-02-18 20:42:16 +10:00 |
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Brent Neale
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dce54845c2
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Phase 1: Event-driven backtester, 5 strategies, and baseline results
- Built event-driven backtesting engine with spread/slippage modeling,
3-TP partial closes, trailing stops, and rich trade logging (20+ features)
- Implemented 5 strategy signal generators (MA Breakout, VWAP Reversal,
Key Level Breakout, EMA Ribbon Scalp, Momentum Exhaustion)
- Full indicator library (EMA, SMA, RSI, ATR, MACD, ADX, Stochastic,
Session VWAP bands, swing points, key levels, RSI divergence)
- Data pipeline: Dukascopy download, validation, 70/30 train/test split
- Baseline results: all 5 strategies generate 200+ trades on training data
(Jan 2021 - Aug 2023), best profit factors 0.82-0.96 on select pairs
- Trade logs and reports saved for Phase 3 ML feature engineering
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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2026-02-18 06:04:40 +10:00 |
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