Maximize risk-adjusted return (Sharpe/Calmar) on NZD/USD 15-min data. GradientBoostingClassifier chosen for strong generalisation with tabular features, low learning rate + early stopping prevents overfitting. SL=0.5%, TP=1.0% gives 1:2 R:R ratio. Threshold=0.55 filters marginal signals.

Maximize risk-adjusted return (Sharpe/Calmar). XGBoost with regularisation (alpha, lambda, gamma, min_child_weight) to reduce overfitting on 15-min EUR/USD data. Shallow trees (max_depth=4) and column/row subsampling prevent memorisation of noise. Horizon=4 bars (1 hour) balances signal quality vs trade frequency. Session filter [7,17] UTC focuses on liquid London/NY overlap. SL=0.5%, TP=1.0% gives 1:2 R/R. Threshold=0.55 filters marginal predictions while keeping enough trad

Maximize risk-adjusted return (Sharpe). GradientBoostingClassifier chosen for strong performance on tabular financial data with moderate feature counts. Deeper ensemble (400 estimators, depth 4) with early stopping captures non-linear BB squeeze patterns. Subsample=0.75 and sqrt features reduce overfitting. SL 0.5% / TP 1.0% gives 1:2 R:R ratio. Session filter 06-20 UTC covers London + NY sessions where USD/JPY liquidity is highest.