backtesting-frameworks

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Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates.

Testing & QA 40,440 stars 6528 forks Updated today 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. ## 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.

Details

Author
sickn33
Repository
sickn33/antigravity-awesome-skills
Created
4 months ago
Last Updated
today
Language
Python
License
MIT

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