Check a dataset before analysis
Find missing values, inconsistent formats, duplicates, and questions that could invalidate results.
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.
--- version: 4.1.0-fractal name: backtesting-frameworks-c9e284c7d702 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. ## 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. ## 🧠 Knowledge Modules (Fractal Skills) ### 1. [implementation-playbook](./sub-skills/implementation-playbook.md)--- version: 4.1.0-fractal name: backtesting-frameworks-c9e284c7d702 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. ## 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. ## 🧠 Knowledge Modules (Fractal Skills) ### 1. [implementation-playbook](./sub-skills/implementation-playbook.md)
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.