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 | 57 | 33 | 24 | 57.9% | 1.03 | 0.175 | Active |
| Breakout | 526 | 363 | 163 | 69.0% | 1.01 | 0.387 | Active |
| Mean Reversion | 55 | 31 | 24 | 56.4% | 0.80 | 0.015 | Active |
| Momentum | 157 | 126 | 31 | 80.3% | 1.60 | 1.088 | Strong |
| Scalping | 70 | 37 | 33 | 52.9% | 0.62 | -0.143 | Weak (reducing weight) |
| Swing | 109 | 59 | 50 | 54.1% | 0.88 | 0.017 | Active |
| Position | 87 | 43 | 44 | 49.4% | 0.81 | -0.106 | 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%) | - | 37W / 24L (61%) | 2W / 3L (40%) | - |
| Breakout | 180W / 66L (73%) | 39W / 23L (63%) | 30W / 21L (59%) | 6W / 10L (38%) | 7W / 0L (100%) |
| Mean Reversion | 13W / 19L (41%) | 3W / 1L (75%) | 5W / 5L (50%) | - | 1W / 1L (50%) |
| Momentum | 47W / 21L (69%) | - | 51W / 3L (94%) | 12W / 8L (60%) | - |
| Scalping | 11W / 12L (48%) | 3W / 2L (60%) | 5W / 3L (63%) | 1W / 0L (100%) | 2W / 0L (100%) |
| Swing | 51W / 41L (55%) | 3W / 1L (75%) | - | 5W / 6L (45%) | 1W / 0L (100%) |
| Position | 31W / 35L (47%) | 4W / 5L (44%) | 2W / 3L (40%) | 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.