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 | 35 | 18 | 17 | 51.4% | 0.86 | -0.044 | Weak (reducing weight) |
| Position | 58 | 32 | 26 | 55.2% | 1.22 | 0.225 | Active |
| Mean Reversion | 24 | 11 | 13 | 45.8% | 0.96 | -0.102 | Weak (reducing weight) |
| Breakout | 65 | 41 | 24 | 63.1% | 1.18 | 0.376 | Active |
| Trend Following | 11 | 6 | 5 | 54.5% | 0.71 | -0.068 | Weak (reducing weight) |
| Scalping | 5 | 4 | 1 | 80.0% | 0.46 | 0.168 | Learning (5/10) |
| Swing | 10 | 5 | 5 | 50.0% | 0.82 | -0.090 | 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 | 3W / 4L (43%) | - | 6W / 5L (55%) | - | - |
| Position | 13W / 8L (62%) | 3W / 2L (60%) | 8W / 9L (47%) | - | - |
| Mean Reversion | 0W / 2L (0%) | 3W / 5L (38%) | 4W / 2L (67%) | - | - |
| Breakout | 6W / 3L (67%) | 18W / 9L (67%) | 6W / 3L (67%) | - | - |
| Trend Following | 1W / 0L (100%) | - | 5W / 5L (50%) | - | - |
| Scalping | - | - | 1W / 1L (50%) | - | - |
| Swing | 1W / 5L (17%) | - | - | - | - |
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.