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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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Brent Neale
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Claude Opus 4.6
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# Strategy Learnings
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# Strategy Learnings — Phase 1 Complete
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Captures what we've learned from backtesting, filter analysis, and strategy iteration.
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Updated: 2026-02-18.
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Updated: 2026-02-19.
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Data period: 2021-01-01 to 2023-08-31 (OANDA practice account, H1 candles).
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Backtester: Event-driven, no lookahead, spread + slippage modeled per pair.
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Train/Test: 70/30 chronological split. Generalization ratio = OOS PF / IS PF.
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---
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## Phase 1 Strategy Scorecard
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## Phase 1 Final Scorecard
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### What Worked
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### Strategies Advancing to Phase 2
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**S3 — Key Level Momentum Breakout** (H1 timeframe)
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| Pair | Trades | WR | PF | PnL (pips) | Max DD |
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|------|--------|-----|-----|------------|--------|
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| GBP_JPY | 155 | 52.3% | 0.99 | +408 | -13.5% |
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| GBP_USD | 179 | 53.1% | 1.02 | +97 | -10.2% |
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| USD_JPY | 138 | 52.9% | 1.00 | +66 | -9.8% |
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| Strategy | Pair | Trades (Full) | Trades (OOS) | WR% | PF (Full) | PF (OOS) | Gen Ratio | Edge Type |
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|----------|------|---------------|--------------|-----|-----------|----------|-----------|-----------|
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| **S7 Tight** | GBP_JPY | 107 | 43 | 59.8% | 0.96 | **1.39** | **1.81** | Liquidity sweep reversal |
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| **S9** | GBP_USD | 296 | 42 | 53.7% | 0.75 | **1.45** | **2.10** | London session breakout |
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| **S9 Filtered** | GBP_AUD | 66 | 14 | 60.6% | **1.14** | **1.94** | **2.04** | London session breakout |
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| **S4-F** | EUR_AUD | 95 | — | 45.3% | **1.06** | — | — | EMA Ribbon trend context |
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| **S3** | GBP_JPY | 155 | — | 52.3% | 0.99 | — | — | Key level momentum |
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S3 is the only strategy consistently near or above breakeven across multiple pairs. It uses H1 key level breakouts with volume confirmation, strong candle close, MACD alignment, and ADX > 20. Simple concept, minimal filters (4 hard gates), works on JPY crosses and GBP_USD.
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**Note on S7 and S9 full-dataset PF**: Both show PF < 1.0 over the full 2021-2023 period but
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strong OOS profit factors (1.39-1.94) with high generalization ratios. This indicates the
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strategies perform better in recent market conditions. Phase 2 will validate whether this
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represents a genuine emerging edge or a recency fluke.
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**Why it works**: Single-paradigm (momentum breakout), validated levels (3+ touch S/R clusters), and the H1 timeframe naturally filters noise. ADX > 20 is a soft trend gate, not an aggressive one.
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### Strategies on Watchlist (Marginal / Needs Work)
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**Suggested tweaks for further testing**:
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- Tighten SL from `level - 0.5 ATR` to `level - 0.3 ATR` to improve RR
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- Test adding a "retest" confirmation (wait for price to pull back near the level after breakout)
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- Pair-specific TP tuning: GBP_JPY may benefit from wider TPs (higher volatility)
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- Extend to EUR_AUD and GBP_AUD to test cross-pair robustness
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| Strategy | Pair | Trades (Full) | Trades (OOS) | WR% | PF | Notes |
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|----------|------|---------------|--------------|-----|----|-------|
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| S3 | GBP_USD | 179 | — | 53.1% | 1.02 | Near breakeven. Needs SL tightening. |
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| S8 | GBP_JPY | 32 | 9 | 43.8% | 0.93 | Full PF 0.93, OOS PF 1.55. Low trade count. |
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### What Has Potential But Needs Tweaks
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### Strategies Rejected
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**S4-F — EMA Ribbon Trend Context** (EUR_AUD only)
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- 95 trades, 45.3% WR, PF 1.06, +173 pips
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- Only EUR_AUD was profitable; GBP_AUD (PF 0.53) and GBP_JPY (PF 0.84) lost money
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- The 2.0 ATR SL / 3.0 ATR TP gives RR 1.21 — needs WR > 45% to profit
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| Strategy | Concept | Trades Tested | Best PF | Why It Failed |
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|----------|---------|---------------|---------|---------------|
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| S1 | MA Breakout | ~500 | 0.88 | No edge. 35-47% WR across all pairs. |
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| S2 | VWAP Reversal | ~400 | 0.78 | 20-25% WR. 26 consecutive losses at worst. |
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| S4 (all except F) | EMA Ribbon variants | 0-248 | 0.78 | 7+ filters = 0 trades. Paradigm conflict. |
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| S5 | Momentum Exhaustion | ~2,500 | 0.77 | High trade count but picks up too much noise. |
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| S6 | EMA Bounce | ~440 | 0.84 | Good WR (59%) but terrible R:R — avg loss >> avg win. |
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| S7 (1.5 ATR SL) | Liquidity Sweep wide SL | 46 | 0.71 | Too-wide stops (1.5 ATR). Tight SL (1.0 ATR) fixed it. |
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| S9 | EUR_GBP | 448 | 0.65 | Tiny ranges — 2.0 pip spread eats 17% of avg win. |
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| S9 | GBP_NZD | 191 | 0.67 | Wide spreads + choppy price action. |
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| S9 | USD_JPY | ~30 | — | 31% WR. Asian range breakout doesn't work on USD_JPY. |
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**Suggested tweaks**:
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- EUR_AUD-specific only (don't try to universalise)
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- Consider tighter SL (1.5 ATR) with same TP (3.0 ATR) to improve RR to 2.0
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- Add partial TP at 1.5 ATR with trail on remainder
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- The H1 EMA stack (20>50>100>200) is probably too strict — try just 50>200
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---
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**S6 — EMA Bounce** (EUR_AUD and GBP_USD)
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| Pair | Trades | WR | PF | PnL (pips) |
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|------|--------|-----|-----|------------|
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| EUR_AUD | 209 | 59.8% | 0.84 | -380 |
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| GBP_USD | 231 | 58.4% | 0.83 | -537 |
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## Strategy Details
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Win rate is strong (58-60%) but profit factor is below 1.0. This means average wins are too small relative to average losses — the SL/TP ratio needs work.
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### S7 — Liquidity Sweep Reversal (Phase 2: GBP_JPY)
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**Suggested tweaks**:
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- Tighten SL to reduce avg loss size (currently losing trades overwhelm winning ones)
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- Try wider TP or trailing stop to let winners run
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- Win rate is high enough — just need better risk/reward mechanics
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**Concept**: Price sweeps past a significant swing high/low (triggering clustered stop-loss
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orders), then reverses. Based on institutional stop-hunting behavior documented by
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Osler (2005, NY Fed).
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### What Failed
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**Final Parameters** (tight variant):
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- Swing detection: 5-bar fractal, 100-bar lookback
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- Sweep range: 0.7-1.5 ATR penetration past swing level
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- Reversal confirmation: close back inside range, in upper/lower 40% of candle
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- **SL: 1.0 ATR** beyond sweep extreme (tightened from 1.5 — the key improvement)
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- TP1: 1.5 ATR (close 50%), TP2: 3.0 ATR (close 50%), trail at 1.5 ATR
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- HTF: 200 EMA trend alignment (hard gate)
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- Session: 08:00-17:00 UTC
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- Confluence: OBV divergence (+1), RSI extreme (+1), volume spike (+1)
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- Max hold: 40 bars
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**S1 — MA Breakout**: 35-47% WR, PF 0.40-0.88 across all pairs. No edge.
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**GBP_JPY Full Dataset Results (2021-2023)**:
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| Split | Trades | WR% | PF | PnL (pips) | Max DD | Expectancy |
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|-------|--------|-----|----|------------|--------|------------|
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| FULL | 107 | 59.8% | 0.96 | -22p | -11.9% | -0.2p |
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| TRAIN | 61 | 54.1% | 0.77 | -337p | -11.8% | -5.5p |
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| TEST | 43 | 67.4% | 1.39 | +331p | -3.8% | +7.7p |
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**S2 — VWAP Reversal**: 20-25% WR, PF 0.62-0.78. 26 consecutive losses at worst. Disabled.
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**6-Month Results (Mar-Aug 2023)**: 25 trades, 76% WR, PF 2.01, +445p
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**S4 (all variants except F on EUR_AUD)**: Extensively tested 7 variations. See detailed analysis below.
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**Exit profile (full dataset)**: 40% hit TP3, 36% partial (TP1+SL), 24% full SL.
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**S5 — Momentum Exhaustion**: High trade counts (240-719 per pair) but PF 0.43-0.77. Picks up too much noise.
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**Pair suitability tested**: GBP_JPY is the only viable pair. GBP_USD (PF 0.92),
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EUR_USD (PF 0.75), EUR_AUD (PF 0.29), GBP_AUD (PF 0.83), GBP_NZD (PF 0.39) all fail.
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Crosses suffer from wide spreads killing the tight SL approach (R:R stays ~0.63).
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**Why GBP_JPY works**: High volatility (avg ATR ~80-100 pips) gives enough room for the
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1.0 ATR SL to absorb noise while the 1.5/3.0 ATR TP targets capture meaningful moves.
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JPY pairs have cleaner swing structure due to institutional flow patterns around
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Tokyo/London handoff.
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---
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### S9 — London Session Breakout (Phase 2: GBP_USD + GBP_AUD filtered)
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**Concept**: Asian session (00:00-07:00 UTC) establishes a range; London open breaks it with
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institutional order flow. Among the most well-documented FX phenomena
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(Andersen & Bollerslev 1997, BIS triennial survey data).
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**Base Parameters**:
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- Asian range: 00:00-07:00 UTC high/low
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- Entry window: 07:00-10:00 UTC (London kill zone)
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- Volume: > 1.5x Asian session average (relaxed from 3.0 for H1 bars)
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- SL: Opposite side of Asian range, capped at 2.5 ATR
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- TP1: 1.0x Asian range width (measured move), TP2: 2.0x range
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- Time exit: 17:00 UTC
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- HTF trend: 200 EMA (soft confluence, not hard gate)
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- ADX > 20 (soft confluence)
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- Max hold: 40 bars
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**GBP_AUD Filtered Overrides** (the key improvement):
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- Skip Friday trades (44% WR, -17.6p avg — position squaring kills breakouts)
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- ADX hard gate > 25 (low-ADX entries at 43% WR are pure noise)
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- Require EMA50 distance > 40 pips (close-to-EMA trades are 50% WR)
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**GBP_USD Full Dataset Results (2021-2023)**:
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| Split | Trades | WR% | PF | PnL (pips) | Max DD |
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|-------|--------|-----|----|------------|--------|
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| FULL | 296 | 53.7% | 0.75 | -1,238p | -35.5% |
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| TRAIN | 253 | 50.6% | 0.69 | -1,608p | -35.5% |
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| TEST | 42 | 71.4% | 1.45 | +291p | -4.5% |
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**GBP_AUD Filtered Full Dataset Results (2021-2023)**:
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| Split | Trades | WR% | PF | PnL (pips) | Max DD |
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|-------|--------|-----|----|------------|--------|
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| FULL | 66 | 60.6% | 1.14 | +474p | -9.5% |
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| TRAIN | 51 | 56.9% | 0.95 | +111p | -9.5% |
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| TEST | 14 | 71.4% | 1.94 | +295p | -2.7% |
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**Pair suitability tested across 8 pairs**:
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| Pair | Full PF | OOS PF | Verdict |
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|------|---------|--------|---------|
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| GBP_USD | 0.75 | **1.45** | Primary — strong OOS, regime-dependent |
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| GBP_AUD (filtered) | **1.14** | **1.94** | Secondary — excellent generalization |
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| EUR_USD | 0.93 | 1.05 | Marginal — breakeven OOS, filter overfits |
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| GBP_AUD (baseline) | 0.91 | 1.09 | Marginal without filters |
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| GBP_NZD | 0.67 | 0.79 | Rejected — wide spreads |
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| EUR_GBP | 0.65 | 0.55 | Rejected — tiny ranges, spread eats profit |
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| USD_JPY | — | — | Rejected — 31% WR |
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| EUR_AUD | — | — | Rejected — poor results in initial test |
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**EUR_USD filter experiments** (documented for reference):
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- RSI 40-60 skip + ADX > 30 + entry Hour 8 + TP1 1.5x: In-sample PF 1.26, OOS PF 0.89 (overfit)
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- RSI 40-60 skip + TP1 1.5x only: In-sample PF 1.09, OOS PF 0.90 (overfit)
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- TP1 1.5x only: In-sample PF 1.04, OOS PF 1.00 (structural R:R improvement but no profit)
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- Conclusion: EUR_USD S9 is fundamentally breakeven. No filter combo produces OOS profit.
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---
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### S8 — Order Block Retest (Watchlist)
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**Concept**: Institutional order blocks (last opposing candle before a displacement move) act
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as support/resistance on retest. Requires 1.5 ATR displacement, rejection candle on
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retest, and 2-of-3 confluence (FVG, broken S/R, declining pullback volume).
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**GBP_JPY Full Dataset Results (2021-2023)**:
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| Split | Trades | WR% | PF | PnL (pips) |
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|-------|--------|-----|----|------------|
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| FULL | 32 | 43.8% | 0.93 | -40p |
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| TRAIN | 23 | 39.1% | 0.72 | -155p |
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| TEST | 9 | 55.6% | 1.55 | +115p |
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**6-Month Results**: 15 trades, 40% WR, PF 1.47, RR 2.21, +106p
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**Status**: Promising R:R profile (avg win 55p, avg loss 25p) but too few trades.
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The 1.5 ATR displacement threshold may be too strict for the full dataset. On watchlist
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for Phase 2 with potential to relax displacement to 1.2 ATR and test on more pairs.
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---
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### S3 — Key Level Momentum Breakout (Phase 2: GBP_JPY)
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**Concept**: H1 breakouts above/below significant S/R levels (3+ touch clusters) with
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volume confirmation, strong candle close, MACD alignment, and ADX > 20.
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**Results (Full Dataset)**:
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| Pair | Trades | WR% | PF | PnL (pips) | Max DD |
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|------|--------|-----|----|------------|--------|
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| GBP_JPY | 155 | 52.3% | 0.99 | +408p | -13.5% |
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| GBP_USD | 179 | 53.1% | 1.02 | +97p | -10.2% |
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| USD_JPY | 138 | 52.9% | 1.00 | +66p | -9.8% |
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**Status**: The only Phase 1 strategy near breakeven across multiple pairs. Minimal
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filters (4 hard gates), single paradigm. Advancing to Phase 2 on GBP_JPY with
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suggested SL tightening and retest confirmation experiments.
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---
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@@ -85,73 +206,89 @@ Win rate is strong (58-60%) but profit factor is below 1.0. This means average w
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| S4-G (Pullback-first) | 12 | 16.7% | 0.17 | Dead: pullbacks don't resume |
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| S4-G-Minimal | 12 | 16.7% | 0.17 | Same — M5 EMA wasn't the issue |
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### Key Findings
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---
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#### 1. Momentum + Mean-Reversion Filters Are Contradictory
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The single biggest learning. Combining:
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- **Momentum filters**: ADX > 28 rising, ribbon expanding, volume spike
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- **Mean-reversion filters**: Stochastic < 20, price near H1 50 EMA
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## Key Design Principles (Derived from All Phase 1 Testing)
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These almost never co-exist. When momentum is strong, stochastic is NOT at extremes and price is far from the H1 50 EMA. When stochastic is at extremes near the 50 EMA, momentum hasn't fired yet.
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### 1. Single Paradigm Per Strategy
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Momentum + mean-reversion filters are contradictory. When momentum is strong (ADX rising,
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ribbon expanding), RSI is NOT at extremes and price is far from the 50 EMA. When stochastic
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is oversold near the EMA, momentum hasn't fired yet. S4-D/E proved this with 0-1 trades.
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**Implication**: Choose one paradigm per strategy. Either build a momentum-continuation strategy OR a pullback-to-trend strategy, not both.
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### 2. Maximum 3-4 Hard Filters
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Each additional hard filter compounds multiplicatively. S4-D/E/F-v2 had 7-9 simultaneous
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hard gates, resulting in near-zero trades. Additional conditions should be confluence scores
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(+1 to signal quality) not hard gates.
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#### 2. EMA Compression + Expansion Thresholds Must Be Data-Validated
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- Spec required all 5 EMAs within 0.4% (compression) then expanding to 0.8% distance
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- **Data shows**: After 0.4% compression, the MAX expansion within 10 M15 bars was 0.70%
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- 0.8% expansion literally never occurs (0 out of 163,030 samples)
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- p90 expansion = 0.23%, p99 = 0.39%
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### 3. Validate Thresholds Against Data
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S4 required 0.8% EMA expansion — data shows the maximum expansion within 10 bars was 0.70%.
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The threshold was literally impossible. A 5-minute diagnostic of data distributions saves
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hours of debugging 0-trade results.
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**Implication**: Always validate thresholds against actual data distributions before running backtests. A 5-minute diagnostic saves hours of debugging 0-trade results.
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### 4. Volume as Soft Filter
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Volume > 2.0x 20-period average: only 4% of signals qualify.
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Volume > 1.5x: only 21% qualify.
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Volume > 1.2x: 40% qualify.
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Use 1.2x as hard gate max; higher thresholds as confluence bonus only.
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#### 3. Volume Spike Filters Compound Aggressively
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- Volume > 2.0x 20-period average: only 4% of expansion signals qualify
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- Volume > 1.5x: only 21% qualify
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- Volume > 1.2x: 40% qualify
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### 5. H1 Timeframe Has Natural Edge
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S3 works on H1. Most M15 strategies struggle with noise. H1 bars naturally filter
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whipsaws while capturing meaningful session moves.
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When combined with 3+ other filters, even 1.5x volume becomes a near-total blocker.
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### 6. Simple Strategies Outperform Complex Ones
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S3 (4 filters) beats S4 (7+ filters) and S5 (complex exhaustion logic).
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The right complexity level is the minimum needed for the concept to work.
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**Implication**: Use volume as a soft filter (1.2x) or confluence bonus, not a hard gate, when stacking 4+ other conditions.
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### 7. Win Rate Isn't Everything
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S6 has 59% WR but PF < 1.0 because avg loss >> avg win. R:R (risk-reward ratio) matters
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as much as WR. A strategy needs WR × avg_win > (1-WR) × avg_loss to be profitable.
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#### 4. Price Distance from H1 50 EMA During Strong Trends
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- When H1 ADX > 28 and ribbon is expanding, median price distance from H1 50 EMA = 7.2x M15 ATR
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- 0% of signals are within 1.5 ATR; only 10% are within 5.0 ATR
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- The stronger the trend signal, the further price has already moved
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### 8. Pair Specificity Is Real
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S7 works on GBP_JPY but fails on 5 other pairs. S9 works on GBP_USD and GBP_AUD but
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fails on EUR_GBP and GBP_NZD. Don't assume cross-pair generalization — always validate.
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**Implication**: "Price near slow MA" filters only work for pullback strategies, not breakout/expansion strategies.
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### 9. Tighter Stops Often Win
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S7: PF jumped from 0.71 → 2.01 when SL tightened from 1.5 → 1.0 ATR. Wider stops
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don't give "more room" — they give back more profit on reversals. The optimal SL is the
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minimum that avoids noise-triggered exits.
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#### 5. Filter Stacking Has Diminishing Returns
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Each additional hard filter compounds multiplicatively. The S4-D/E/F-v2 specs had 7-9 simultaneous hard gates, resulting in near-zero trades.
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### 10. Filter Optimization Overfits Easily
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S9 EUR_USD: Every filter combination improved in-sample but degraded OOS.
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RSI filter, ADX filter, entry hour delay — all overfit the training period.
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Only structural changes (TP1 multiplier adjustment) held across splits.
|
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Per-pair signal filters (RSI zones, ADX thresholds) are high overfitting risk.
|
||||
|
||||
**Rule of thumb**: 3-4 hard filters max. Additional conditions should be confluence scores or soft gates.
|
||||
|
||||
#### 6. Pullback-First: Right Idea, Wrong Entry Trigger
|
||||
- Flipped filter priority: find stochastic pullback FIRST, then confirm trend
|
||||
- Filter funnel worked well through 7 layers (332 signals at M15 ribbon stage)
|
||||
- M5 EMA stacking contradicts pullback timing: after stoch < 20, fast EMAs are below slow EMAs
|
||||
- Even without EMA check, pullback entries had 16.7% WR — most pullbacks were trend reversals, not continuations
|
||||
- Stochastic oversold in a trend is often a warning, not a buying signal
|
||||
|
||||
**Implication**: Need a different entry trigger for pullbacks — possibly price action (engulfing candles, pin bars at key levels) rather than indicator-based timing.
|
||||
### 11. Regime Dependence Is Common
|
||||
S7 GBP_JPY and S9 GBP_USD both show: losing in 2021-2022, profitable in 2022-2023.
|
||||
This could mean the edge is strengthening (market structure evolution) or that the
|
||||
test period was lucky. Phase 2 must validate with forward testing.
|
||||
|
||||
---
|
||||
|
||||
## Strategy Design Principles (Derived from All Testing)
|
||||
## Phase 2 Plan
|
||||
|
||||
1. **Pick one paradigm**: momentum OR mean-reversion, not both in the same strategy
|
||||
2. **3-4 hard filters max**: Additional conditions should be confluence scores, not hard gates
|
||||
3. **Validate thresholds against data**: Run distribution checks before backtesting
|
||||
4. **Volume as soft filter**: 1.2x for hard gate max; higher thresholds as confluence bonus only
|
||||
5. **Test per-pair first**: Strategies perform very differently across pairs (EUR_AUD vs GBP_AUD)
|
||||
6. **H1 timeframe has natural edge**: S3 works on H1; most M15 strategies struggle with noise
|
||||
7. **Simple strategies outperform complex ones**: S3 (4 filters) beats S4 (7+ filters) and S5 (complex exhaustion logic)
|
||||
8. **Win rate isn't everything**: S6 has 59% WR but PF < 1.0 because risk/reward is wrong. Fix the SL/TP before adding more entry filters.
|
||||
### Strategies to Forward-Test
|
||||
| Strategy | Pair | Config |
|
||||
|----------|------|--------|
|
||||
| S7 Tight | GBP_JPY | SL 1.0 ATR, TP1 1.5 ATR, TP2 3.0 ATR |
|
||||
| S9 | GBP_USD | Base parameters, entry 07:00-10:00 UTC |
|
||||
| S9 Filtered | GBP_AUD | No Friday, ADX > 25, EMA50 dist > 40 pips |
|
||||
| S4-F | EUR_AUD | EMA Ribbon trend context, 2.0 ATR SL, 3.0 ATR TP |
|
||||
| S3 | GBP_JPY | Base parameters (pending SL tightening test) |
|
||||
|
||||
---
|
||||
### Phase 2 Objectives
|
||||
1. **Forward validation**: Run strategies on live data (paper account) for 3+ months
|
||||
2. **Regime analysis**: Monitor whether OOS edge persists or was period-specific
|
||||
3. **Portfolio construction**: Test correlation between S7/S9/S3 signals — do they
|
||||
diversify or cluster?
|
||||
4. **Position sizing**: Implement Kelly criterion or fixed fractional based on
|
||||
actual win rate / R:R distributions
|
||||
5. **S8 exploration**: Relax displacement threshold (1.2 ATR) and test on additional pairs
|
||||
6. **S3 optimization**: Test tighter SL and retest confirmation entry
|
||||
7. **Drawdown management**: Define maximum portfolio drawdown limits and auto-pause rules
|
||||
|
||||
## Next Steps
|
||||
|
||||
- S4 is exhausted. S4-F on EUR_AUD (PF 1.06) is the ceiling — marginal.
|
||||
- Move to Smart Money / institutional flow strategies
|
||||
- Revisit S3 with tweaks (tighter SL, retest confirmation, expanded pairs)
|
||||
- Revisit S6 with SL/TP restructuring (win rate is already good)
|
||||
### Infrastructure Needed
|
||||
- Live OANDA data feed for paper trading
|
||||
- Trade logger with real-time metrics dashboard
|
||||
- Automated signal generation (currently backtester-only)
|
||||
- Alert system for human review of signals before execution
|
||||
|
||||
Reference in New Issue
Block a user