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 | 61 | 35 | 26 | 57.4% | 1.01 | 0.154 | Active |
| Breakout | 992 | 640 | 351 | 64.5% | 0.89 | 0.219 | Active |
| Mean Reversion | 58 | 32 | 26 | 55.2% | 0.81 | -0.001 | Weak (reducing weight) |
| Momentum | 159 | 128 | 31 | 80.5% | 1.67 | 1.149 | Strong |
| Scalping | 115 | 58 | 57 | 50.4% | 0.65 | -0.168 | Weak (reducing weight) |
| Swing | 139 | 74 | 65 | 53.2% | 0.83 | -0.026 | Weak (reducing weight) |
| Position | 112 | 57 | 55 | 50.9% | 0.81 | -0.079 | 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 | 1W / 3L (25%) | - | 38W / 24L (61%) | 2W / 3L (40%) | - |
| Breakout | 245W / 94L (72%) | 105W / 84L (56%) | 33W / 22L (60%) | 10W / 11L (48%) | 23W / 1L (96%) |
| Mean Reversion | 14W / 19L (42%) | 3W / 2L (60%) | 5W / 5L (50%) | - | 1W / 1L (50%) |
| Momentum | 49W / 21L (70%) | - | 51W / 3L (94%) | 12W / 8L (60%) | - |
| Scalping | 13W / 16L (45%) | 4W / 4L (50%) | 5W / 3L (63%) | 1W / 0L (100%) | 4W / 2L (67%) |
| Swing | 58W / 53L (52%) | 3W / 2L (60%) | - | 5W / 6L (45%) | 1W / 0L (100%) |
| Position | 39W / 42L (48%) | 4W / 5L (44%) | 5W / 6L (45%) | 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.