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
| Bias | Description | Mitigation |
|---|
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