backtesting-frameworks
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.
Install
git clone https://github.com/wshobson/agents /tmp/agents && ln -s /tmp/agents/plugins/quantitative-trading/skills/backtesting-frameworks ~/.claude/skills/backtesting-frameworks
From README
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 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 | Proper Backtest Structure Walk-Forward Analysis Detailed worked examples and patterns Detailed sections (starting with ## Implementation...
More from this repo
python-packaging
Used to create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to...
ai-debt-detector
Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules.
market-sizing-analysis
Calculate TAM/SAM/SOM for market opportunities using top-down, bottom-up, and value theory methodologies.
