Backtesting Frameworks

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

2. Proper Backtest Structure

Historical Data      │      ▼┌─────────────────────────────────────────┐│              Training Set               ││  (Strategy Development & Optimization)  │└─────────────────────────────────────────┘      │      ▼┌─────────────────────────────────────────┐│             Validation Set              ││  (Parameter Selection, No Peeking)      │└─────────────────────────────────────────┘      │      ▼┌─────────────────────────────────────────┐│               Test Set                  ││  (Final Performance Evaluation)         │└─────────────────────────────────────────┘

3. Walk-Forward Analysis

Window 1: [Train──────][Test]Window 2:     [Train──────][Test]Window 3:         [Train──────][Test]Window 4:             [Train──────][Test]                                     ─────▶ Time

Detailed worked examples and patterns

Detailed sections (starting with ## Implementation Patterns) live in references/details.md. Read that file when the navigation summary above is insufficient.

Best Practices

Do's

• Use point-in-time data - Avoid look-ahead bias
• Include transaction costs - Realistic estimates
• Test out-of-sample - Always reserve data
• Use walk-forward - Not just train/test
• Monte Carlo analysis - Understand uncertainty

Don'ts

• Don't overfit - Limit parameters
• Don't ignore survivorship - Include delisted
• Don't use adjusted data carelessly - Understand adjustments
• Don't optimize on full history - Reserve test set
• Don't ignore capacity - Market impact matters