Strategy Learning & Optimization
Uses automated optimization (regime-based + grid search) to tune strategy weights based on your trade history. Weights are used live by the trading engine. Apply only when improved.
What this optimizes: the six internal scoring weights per strategy
(
trend, momentum, volume, structure, volatility, riskQuality) used by the live engine.
It does not tune your Trading Settings values like
autoTradeMinScore, SL/TP %, or feature toggles — those stay where you set them.
You're viewing the platform default weights. Sign in to see and tune your own.
Strategy Performance
| Strategy | Trades | Wins | Losses | Win Rate | Avg R:R | Expectancy | Status |
|---|---|---|---|---|---|---|---|
| Momentum | 37 | 20 | 17 | 54.1% | 0.91 | 0.033 | Active |
| Position | 96 | 50 | 46 | 52.1% | 1.12 | 0.105 | Active |
| Mean Reversion | 24 | 11 | 13 | 45.8% | 0.96 | -0.102 | Weak (reducing weight) |
| Breakout | 237 | 153 | 84 | 64.6% | 1.11 | 0.363 | Active |
| Trend Following | 18 | 12 | 6 | 66.7% | 0.79 | 0.194 | Active |
| Scalping | 26 | 19 | 7 | 73.1% | 0.55 | 0.133 | Active |
| Swing | 31 | 12 | 19 | 38.7% | 0.86 | -0.280 | Weak (reducing weight) |
Current Scoring Weights
These weights determine how much each dimension contributes to a strategy's score. The learning engine adjusts them based on trade outcomes.
| Strategy | Trend | Momentum | Volume | Structure | Volatility | Risk Qual | Actions |
|---|---|---|---|---|---|---|---|
| Momentum | 21 | 29 | 16 | 7 | 15 | 12 | |
| Position | 35 | 20 | 15 | 20 | 5 | 5 | |
| Mean Reversion | 10 | 25 | 20 | 15 | 20 | 10 | |
| Breakout | 15 | 20 | 25 | 20 | 15 | 5 | |
| Trend Following | 30 | 25 | 15 | 15 | 10 | 5 | |
| Scalping | 5 | 20 | 20 | 15 | 25 | 15 | |
| Swing | 30 | 25 | 15 | 20 | 5 | 5 |
Performance by Regime
How each strategy performs in different market conditions.
| Strategy | Trending | Ranging | Volatile | Compression | Mixed |
|---|---|---|---|---|---|
| Momentum | 4W / 4L (50%) | - | 6W / 5L (55%) | - | - |
| Position | 18W / 18L (50%) | 7W / 4L (64%) | 15W / 13L (54%) | - | 0W / 1L (0%) |
| Mean Reversion | 0W / 2L (0%) | 3W / 5L (38%) | 4W / 2L (67%) | - | - |
| Breakout | 11W / 9L (55%) | 67W / 39L (63%) | 28W / 8L (78%) | - | 7W / 1L (88%) |
| Trend Following | 1W / 0L (100%) | - | 11W / 6L (65%) | - | - |
| Scalping | 4W / 1L (80%) | - | 5W / 1L (83%) | - | 0W / 1L (0%) |
| Swing | 4W / 14L (22%) | 1W / 0L (100%) | - | - | - |
How the Learning Engine Works
1. Record outcomes
Every closed trade saves its strategy type, market regime, P&L, and risk/reward ratio.
Every closed trade saves its strategy type, market regime, P&L, and risk/reward ratio.
2. Calculate expectancy
Expectancy = (Win Rate x Avg R:R) - (Loss Rate x 1). Positive = profitable strategy over time.
Expectancy = (Win Rate x Avg R:R) - (Loss Rate x 1). Positive = profitable strategy over time.
3. Adjust weights
After 10+ trades, strategies with negative expectancy get scoring weights reduced by 5%. Strategies with high expectancy (>0.5) get a 2% boost.
After 10+ trades, strategies with negative expectancy get scoring weights reduced by 5%. Strategies with high expectancy (>0.5) get a 2% boost.
4. Live use in signals
Strategy weights above are passed to the trading engine. Each strategy’s score uses its learned weights. Regime gating (e.g. no Mean Reversion in trending) and min 5 trades per strategy apply.
Strategy weights above are passed to the trading engine. Each strategy’s score uses its learned weights. Regime gating (e.g. no Mean Reversion in trending) and min 5 trades per strategy apply.
Note: Weight adjustments are gradual. A strategy needs 20+ trades with negative expectancy before weights start decreasing.
Optimize: Click "Optimize" next to a strategy (10+ trades) to run automated weight optimization. Only apply when improved.