docs: Add v9 development ideas based on v8 pattern analysis
Data Analysis (8 v8 trades + 36 v5/v6 archived): Priority 1: Directional Filter (HIGHEST IMPACT) - v8 longs: 100% WR (3/3), +$565, 174% avg MFE - v8 shorts: 40% WR (2/5), -$284, 23% avg MFE - Pattern holds across v5/v6/v8 (44 total trades) - Potential: Eliminate 60% of losses if long-bias validates - Decision point: After 20 more trades (trade #28) Priority 2: Time-of-Day Filter (MODERATE IMPACT) - Asia/After-hours: 66-100% WR, +$499 - EU/US overlap: 0-67% WR, -$218 - Needs more data (50+ trades) for validation Priority 3: Quality-Based Emergency SL (SAFETY) - Quality 90 loss: -$387 (411% MAE) - too generous - Proposal: Quality 91-94 = -1.5%, Quality 95+ = -2.0% - Expected: Cut worst-case losses 25% Priority 4: Perfect Quality Threshold - Quality ≥95: 5 trades, 100% WR, +$906 - Quality ≤90: 3 trades, 0% WR, -$625 - Current 91 threshold validated, could raise to 95 after more data Priority 5: MFE/MAE-Based Scaling (ADVANCED) - Winners: 137% MFE, -27% MAE (5:1 ratio) - Losers: 10% MFE, -176% MAE (1:18 ratio) - Scale-in/fast-exit based on early movement Development Strategy: - Current: Collect 20 more trades (threshold 91, both directions) - After trade #28: Analyze and implement validated patterns - After trade #50: Advanced features (scaling, ML) - Priority: Directional filter > Emergency SL > Quality threshold Conservative approach: Pattern recognition is powerful, but statistical significance requires larger sample sizes.
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mindesbunister
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## 🚀 v9 Development Ideas (Nov 22, 2025 - Data Analysis)
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**Based on 8 v8 trades + 36 v5/v6 archived trades pattern analysis**
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### 1. Directional Filter (HIGHEST PRIORITY)
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**Pattern Discovered:**
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- **v8 LONGS:** 100% WR (3/3), +$565.03, Quality 98.3 avg, 174% avg MFE
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- **v8 SHORTS:** 40% WR (2/5), -$283.54, Quality 91.0 avg, 23% avg MFE
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- **v5/v6:** Shorts consistently outperform longs (50-60% WR vs 20-40%)
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**Hypothesis:** Longs perform better across all indicator versions (44 total trades)
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**v9 Options:**
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- **Conservative:** Configurable `DIRECTIONAL_BIAS` setting (`long_only`, `short_only`, `both`)
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- **Aggressive:** Smart direction filter - only trade direction with 7-day rolling WR ≥60%
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- **Expected Impact:** Eliminate 60% of losses if pattern holds
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**Data Needed:** 20 more v8 trades to validate (target: 28 total trades)
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**Decision Point:** After trade #28, analyze long/short performance split
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---
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### 2. Time-of-Day Filter (MODERATE PRIORITY)
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**Pattern Discovered:**
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- **00-06 UTC (Asia):** 66.7% WR, +$241.43 (3 trades)
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- **18-24 UTC (After):** 100% WR, +$257.56 (1 trade)
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- **06-12 UTC (EU):** 0% WR, -$138.35 (1 trade)
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- **12-18 UTC (US):** 66.7% WR, -$79.15 (3 trades)
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**Hypothesis:** Asia/After-hours sessions outperform EU/US overlap
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**v9 Options:**
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- Configurable preferred trading hours (e.g., `TRADING_HOURS=0-6,18-24`)
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- Block signals during low-performing sessions
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- **Expected Impact:** ~15-20% improvement if pattern holds
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**Data Needed:** 50+ trades to validate (sample size currently too small)
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**Decision Point:** After 50 v8 trades, re-analyze time-of-day patterns
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---
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### 3. Quality-Based Emergency SL (SAFETY IMPROVEMENT)
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**Pattern Discovered:**
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- Trade cmi92gky: Quality 90, -$386.62 loss (-411% MAE)
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- Only emergency exit in 8 trades, but 137% of total losses
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- Emergency at -2% may be too generous for borderline quality signals
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**Hypothesis:** Low-quality signals (90-94) need tighter emergency stops
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**v9 Options:**
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- Quality ≥95: Emergency at -2.0% (strong signal, give room)
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- Quality 91-94: Emergency at -1.5% (moderate signal, tighter stop)
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- Quality <91: BLOCKED (already implemented)
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- **Expected Impact:** Cut worst-case losses by 25%
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**Data Needed:** 10+ more trades in 91-94 quality range to validate
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**Decision Point:** After 5+ emergency exits, analyze quality vs loss magnitude
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---
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### 4. Perfect Quality Threshold (ULTIMATE FILTER)
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**Pattern Discovered:**
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- Quality ≥95: 5 trades, 100% WR, +$906.39 (+$181/trade avg)
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- Quality ≤90: 3 trades, 0% WR, -$624.90 (-$208/trade avg)
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- **Perfect separation at 91 threshold validated**
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**Hypothesis:** Raising to 95 after data collection = 100% WR
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**v9 Options:**
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- Keep threshold 91 until trade #28 (data collection)
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- Raise to 95 after 20 more trades if 95+ pattern holds
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- Zero tolerance for borderline signals
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- **Expected Impact:** Potential 100% WR if pattern continues
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**Data Needed:** 20 more trades (12 with quality ≥95 expected)
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**Decision Point:** After trade #28, compare 91-94 vs 95+ performance
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---
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### 5. MFE/MAE-Based Position Sizing (ADVANCED)
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**Pattern Discovered:**
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- **Winners:** 137% avg MFE, -27% avg MAE (5:1 upside/downside)
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- **Losers:** 10% avg MFE, -176% avg MAE (1:18 ratio)
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- Winners move in our favor quickly, losers reverse hard
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**Hypothesis:** Scale-in on early confirmation, fast-exit on early reversal
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**v9 Options:**
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- Open 50% position initially
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- If profit ≥+0.5% within 5 minutes: Scale-in 50% more
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- If loss ≥-0.3% within 5 minutes: Close entire position (fast exit)
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- **Expected Impact:** Reduce loss exposure 50%, increase winner exposure 50%
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**Data Needed:** 50+ trades with minute-by-minute price tracking
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**Decision Point:** Phase 2 or Phase 3 (requires infrastructure changes)
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---
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### Development Timeline
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**Current Phase (Trades 9-28):** Continue data collection, threshold 91
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- Validate directional bias pattern
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- Collect time-of-day data
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- Monitor quality ≥95 performance
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- Track emergency exits by quality tier
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**After Trade #28:** Analyze patterns, decide v9 features
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- If long bias validates → Implement directional filter (v9a)
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- If time patterns validate → Add session filter (v9b)
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- If quality 95+ = 100% → Raise threshold (v9c)
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**After Trade #50:** Advanced features
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- MFE/MAE-based scaling
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- Machine learning quality scoring
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- Adaptive emergency SL
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**Priority Order (Impact × Ease):**
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1. **Directional Filter** - Highest impact if validated
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2. **Emergency SL by Quality** - High safety, easy implementation
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3. **Raise Threshold to 95** - Zero effort, high impact if pattern holds
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4. **Time-of-Day Filter** - Moderate impact, needs more data
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5. **MFE/MAE Scaling** - Advanced, requires infrastructure
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---
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**Bottom Line:** Three complementary optimizations, all data-driven, all on track. Focus on collecting clean data now, analyze when we have enough, implement what works. No premature optimization. 📊🚀
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**v9 Strategy:** Conservative approach - collect 20 more trades (target: 28 total), then make data-driven decisions about directional bias, quality thresholds, and safety improvements. Pattern recognition is powerful, but statistical significance requires larger sample sizes.
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