Backtest single- and multi-factor portfolios with gate checks and IS/OOS evaluation.
npx skills add https://github.com/VernonOY/alpha-skills --skill alpha-backtest
Please help me install this Agent Skill. Skill: alpha-backtest Source: https://github.com/VernonOY/alpha-skills/tree/main/skills/alpha-backtest Command: npx skills add https://github.com/VernonOY/alpha-skills --skill alpha-backtest
Backtest engine for single- and multi-factor portfolios enables rigorous evaluation with gate checks, ensuring robust strategy validation.
Run a backtest on your selected factors to evaluate performance and stability across markets.
High-intent search queries and answers about installing and using this skill.
The backtest engine evaluates single-factor and multi-factor portfolios using in-sample and out-of-sample evaluation, portfolio construction, turnover accounting, and detailed performance metrics like NAV and drawdown.
IS/OOS evaluation splits historical data to validate factor strategies on unseen segments, ensuring portfolio robustness by comparing in-sample training performance against out-of-sample testing results.
Yes, running a factor backtest requires a data-loading pipeline, factor definitions, a backtest engine, and gate-configured rules sourced from your project config to process the evaluation.
Performance reporting includes NAV, drawdown, and monthly performance metrics, alongside turnover accounting, to provide a comprehensive view of factor portfolio stability.
Yes, the backtest engine supports both single-factor and multi-factor strategies, applying the same deterministic gate checks and IS/OOS evaluation to evaluate individual factor performance.
Gate checks apply deterministic rules during portfolio construction to ensure rigorous strategy validation, preventing weak factor models from passing evaluation stages.
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