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 |
|---|---|---|---|---|---|---|---|
| Trend Following | 28 | 17 | 11 | 60.7% | 1.27 | 0.378 | Active |
| Breakout | 158 | 106 | 52 | 67.1% | 1.06 | 0.382 | Active |
| Mean Reversion | 30 | 21 | 9 | 70.0% | 0.93 | 0.351 | Active |
| Momentum | 121 | 109 | 12 | 90.1% | 1.73 | 1.460 | Strong |
| Scalping | 3 | 2 | 1 | 66.7% | 0.46 | -0.026 | Learning (3/10) |
| Swing | 23 | 12 | 11 | 52.2% | 0.95 | 0.018 | Active |
| Position | 23 | 9 | 14 | 39.1% | 0.82 | -0.288 | 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 |
|---|---|---|---|---|---|---|---|
| Trend Following | 30 | 25 | 15 | 15 | 10 | 5 | |
| Breakout | 15 | 20 | 25 | 20 | 15 | 5 | |
| Mean Reversion | 10 | 25 | 20 | 15 | 20 | 10 | |
| Momentum | 20 | 30 | 20 | 10 | 10 | 10 | |
| Scalping | 5 | 20 | 20 | 15 | 25 | 15 | |
| Swing | 30 | 25 | 15 | 20 | 5 | 5 | |
| Position | 35 | 20 | 15 | 20 | 5 | 5 |
Performance by Regime
How each strategy performs in different market conditions.
| Strategy | Trending | Ranging | Volatile | Compression | Mixed |
|---|---|---|---|---|---|
| Trend Following | 0W / 1L (0%) | - | 21W / 11L (66%) | 2W / 3L (40%) | - |
| Breakout | 53W / 22L (71%) | 9W / 9L (50%) | 15W / 4L (79%) | 6W / 6L (50%) | 3W / 0L (100%) |
| Mean Reversion | 10W / 9L (53%) | 2W / 0L (100%) | 5W / 5L (50%) | - | 1W / 0L (100%) |
| Momentum | 41W / 11L (79%) | - | 50W / 3L (94%) | 2W / 2L (50%) | - |
| Scalping | 1W / 1L (50%) | - | 2W / 0L (100%) | 1W / 0L (100%) | - |
| Swing | 14W / 9L (61%) | 1W / 1L (50%) | - | 0W / 5L (0%) | 1W / 0L (100%) |
| Position | 5W / 14L (26%) | 2W / 1L (67%) | 2W / 1L (67%) | - | - |
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.