backtesting-frameworks

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

Backtesting Frameworks

Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates.

When to Use This Skill

- Developing trading strategy backtests

- Building backtesting infrastructure

- Validating strategy performance

- Avoiding common backtesting biases

- Implementing walk-forward analysis

- Comparing strategy alternatives

Core Concepts

1. Backtesting Biases