Summary
- Robust backtesting systems that avoid look-ahead bias, survivorship bias, and overfitting.
- Event-driven and vectorized backtester implementations with realistic transaction cost modeling, slippage, and commission handling Walk-forward optimization and Monte Carlo simulation for strategy robustness testing across multiple time windows Comprehensive performance metrics including Sharpe, Sortino, Calmar ratios, drawdown analysis, and win-rate calculations Point-in-time data handling, out-of-sample validation, and parameter grid search to prevent curve-fitting and selection bias