Maximize risk-adjusted return (Sharpe/Calmar) on EUR/USD 15-min data. GradientBoostingClassifier chosen for strong out-of-bag regularisation via subsample=0.75 and early stopping (n_iter_no_change=30). max_depth=4 limits overfitting on mean-reversion regime. learning_rate=0.04 with 400 trees balances bias-variance. Signal threshold 0.56 filters low-confidence signals for better precision. Session filter 06-18 UTC targets London+NY overlap with highest liquidity. SL=0.5%, TP=1

Maximize risk-adjusted return (Sharpe/Calmar) on EUR/USD 15-min. XGBoost with moderate depth and strong regularisation to avoid overfitting on noisy FX data. 2:1 TP:SL ratio with trend filter on SMA-50 to avoid counter-trend noise. Session filter 06-20 UTC covers London + NY overlap for best liquidity.

Maximise risk-adjusted return on AUD/USD 15-min bars. XGBoost chosen for its ability to capture non-linear interactions between the EMA-cross regime, RSI momentum, volatility (NATR/BB width), and time-of-day. Shallow trees (max_depth=4) with strong regularisation (reg_lambda=1.5, gamma=0.1) reduce overfitting on the limited 1-year window. 2:1 R:R (SL=0.5%, TP=1.0%) improves Sharpe; reverse on opposite signal captures trend momentum without missing transitions.