factor-backtest
factor-backtest is an Investment analysis & markets skill for AI agents, published by minihellboy in the factorminer repository on GitHub. Skillspace rates factor-backtest D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Combine a factor library into a composite signal and quintile-backtest it under transaction costs — long-short return, monotonicity, turnover, and tearsheets. Use for the portfolio-level view that single-factor IC does not give. Triggers on "backtest", "composite signal", "combine factors", "long-short return", "portfolio", "quintile", "tearsheet", "transaction costs".
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 92
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.