Maximize risk-adjusted return (Sharpe/Calmar) via XGBoost with deep SMA-based trend features (20/50/200), momentum, volatility, RSI, MACD, Bollinger Bands, Stochastics, CCI, Donchian channels, and bar microstructure. Regularised tree ensemble (L1+L2, subsampling) prevents overfit on 15-min FX data. 2:1 reward-to-risk with 0.5% SL / 1.0% TP targets consistent positive expectancy. Session filter [6,18] UTC focuses on liquid London+NY overlap. Trend filter sma_50 suppresses counter-trend noise.

Maximize risk-adjusted return (Sharpe). XGBoost with moderate depth and heavy regularisation (gamma, alpha, lambda) prevents overfit on AUD/USD 15-min data. Bollinger Bands capture mean-reversion; ATR normalises volatility; RSI + MACD confirm momentum; 2:1 TP:SL ratio supports positive expectancy.

Maximize risk-adjusted return on GBP/USD 15-min bars. Strategy combines required SMA (20/50/200) distance and cross features with ADX trend strength, RSI divergence, Bollinger squeeze, Keltner, MACD histogram slope, Stochastic, CCI, Williams %R, and candle-structure ratios. XGBoost with strong regularisation and subsampling prevents overfitting on the relatively short 1-year window. Session filter 06-18 UTC keeps execution in liquid London/NY hours; 0.5% SL and 1.0% TP yield

Maximize risk-adjusted return (Sharpe / Calmar) on EUR/USD 15-min. GradientBoostingClassifier chosen for robustness to noisy FX features and good probability calibration. Shallow trees (depth 4), high n_estimators with early stopping prevent overfitting. Subsample=0.75 adds stochasticity. SL=0.5%, TP=1.0% gives 1:2 R:R. Session filter 07-18 UTC captures London+NY overlap. min_atr filters out flat/illiquid periods. sma_50 trend filter aligns trades with medium-term momentum. T

Maximize risk-adjusted return (Sharpe / Calmar). GradientBoostingClassifier chosen for its strong performance on tabular financial data with noisy labels. Shallow trees (max_depth=4) with shrinkage (lr=0.04) and subsample=0.75 reduce overfitting. Early stopping (n_iter_no_change=30) prevents over-training. SL=0.5%, TP=1.0% gives a 1:2 risk/reward ratio. Session filter 06-20 UTC captures London + New York overlap for GBP/USD.

Maximize risk-adjusted return (Sharpe / Calmar). GradientBoostingClassifier with moderate depth (4) and low learning rate (0.03) to reduce overfitting on 15-min NZD/USD. SL=0.5%, TP=1.0% gives 1:2 RR. EMA 50/200 cross is the primary trend feature; ATR normalises volatility context. Supplementary RSI, MACD, Bollinger, Stochastic and candle-body features capture momentum and mean-reversion signals. Early stopping via n_iter_no_change guards against overfit on the training parti