backtesting-frameworks

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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.

Testing & QA 36,166 stars 3920 forks Updated yesterday MIT

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Skill Content

# 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 ...

Details

Author
wshobson
Repository
wshobson/agents
Created
10 months ago
Last Updated
yesterday
Language
Python
License
MIT

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