Commit Graph

10 Commits

Author SHA1 Message Date
Brent Neale 23d8288fa3 Update param sweep results with S8_OB grid (27 combos)
S8_OB PASS: best params DISP_ATR=2.5, TP1=2.0, Window=40
(IS PF=1.39, OOS PF=1.59, Gen=1.382). S9_Filtered also PASS.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 23:02:12 +10:00
Brent Neale ea5472b737 Add S8 Order Block (GBP_USD/M15) to Phase 2 portfolio
Tested all 9 untested strategies across 22 pair combos. S8 Order Block
on GBP_USD was the standout: OOS PF=2.14, WR=65.4%, Gen=1.850 PASS.
Parameter sweep confirmed DISPLACEMENT_ATR=2.0, TP1_ATR_MULT=1.0,
OB_RETEST_WINDOW=40 as best params (all top-5 PASS OOS validation).

Portfolio now 4 strategies: S7_Tight, S9_Filtered, S3, S8_OB.
OOS portfolio: 82 trades, PF=1.61, WR=64.6%, Sharpe=2.98, +672 pips.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 21:00:30 +10:00
Brent Neale bdab78ee48 Add S10 VWAP Mean Reversion and S11 ADX Trend Pullback strategies, drop both from portfolio
Implemented two M15 intraday strategies to diversify the portfolio:
- S10: VWAP mean reversion in ranging markets (ADX<30, RSI(9) extremes)
- S11: ADX trend pullback to 20 EMA in strong trends (ADX>30, rising)

Added rsi_9 and atr_10 to the indicator pipeline for both strategies.

Backtested on IS (2021-2022) and OOS (2023): both strategies produced
insufficient trade counts on M15 and failed generalization. S10 best
result was EUR_GBP at Gen 0.65 (WARN). S11 collapsed to 0% WR OOS
across all param sweep combos. Both dropped from active portfolio —
3-strategy core (S7_Tight, S9_Filtered, S3) remains unchanged.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 16:23:23 +10:00
Brent Neale 9c5d55ec46 Refine Phase 2 portfolio: data-driven filters, drop S4F and S9
S7: add RSI floor (RSI<40 = 0% WR) and ATR percentile cap (high-vol
regime = worse RR). IS flips from PF 0.68 to 1.52, OOS holds at 1.80.

S3: add confluence gate (C>=4) and skip hours 09-10 (0% WR). IS PF
1.06 -> 1.22, OOS PF 1.07 -> 1.23.

S9_Filtered: add skip_monday (unreliable Asian ranges after weekend
gaps). IS PF 1.10 -> 1.31, OOS holds strong at 2.26.

Drop S9/GBP_USD (negative PF across all param combos) and S4F/EUR_AUD
(overfit: IS 1.43 collapses to OOS 0.48). 3-strategy portfolio: all
PASS generalization, IS PF 1.29, OOS PF 1.55, Gen 1.46.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 10:25:09 +10:00
Brent Neale 4f911b2072 Add Phase 2 backtesting pipeline: IS/OOS split, param sweep, generalization scoring
Externalize hardcoded params in S4F (5 params) and S3 (9 params) as class
attributes for sweep compatibility. Add unified backtest runner with IS/OOS
validation and generalization scores, plus parameter grid sweep (90 combos)
with OOS validation. S7/S9/S9_Filtered pass generalization; S4F/S3 confirm
defaults are near-optimal.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 10:25:08 +10:00
Brent Neale af994b0fbe Add Phase 1 trade preview PNGs, live engine state, remove master prompt PDF
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-19 14:54:04 +10:00
Brent Neale 072ac0f245 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>
2026-02-19 14:46:51 +10:00
Brent Neale 39a6536284 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>
2026-02-19 13:56:03 +10:00
Brent Neale edbe359d1b 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>
2026-02-18 20:42:16 +10:00
Brent Neale dce54845c2 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>
2026-02-18 06:04:40 +10:00