/backtesting-frameworks

name: backtesting-frameworks
description: Build robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs. Use when developing trading algorithms, validating strategies, or building backtesting infrastructure.

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 | | ---------------- | ------------------------- | ----------------------- | | **Look-ahead** | Using future information | Point-in-time data | | **Survivorship** | Only testing on survivors | Use delisted securities | | **Overfitting** | Curve-fitting to history | Out-of-sample testing | | **Selection** | Cherry-picking strategies | Pre-registration | | **Transaction** | Ignoring trading costs | Realistic cost models |

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