- 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.
- risk
- safe
- source
- community
- license
- MIT
# Backtesting Frameworks
Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates.
## Use this skill when
- Developing trading strategy backtests
- Building backtesting infrastructure
- Validating strategy performance and robustness
- Avoiding common backtesting biases
- Implementing walk-forward analysis
## Do not use this skill when
- You need live trading execution or investment advice
- Historical data quality is unknown or incomplete
- The task is only a quick performance summary
## Instructions
- Define hypothesis, universe, timeframe, and evaluation criteria.
- Build point-in-time data pipelines and realistic cost models.
- Implement event-driven simulation and execution logic.
- Use train/validation/test splits and walk-forward testing.
- If detailed examples are required, open `resources/implementation-playbook.md`.
## Safety
- Do not present backtests as guarantees of future performance.
- Avoid providing financial or investment advice.
## Resources
- `resources/implementation-playbook.md` for detailed patterns and examples.
## When to Use
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.
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