AI / ML#alpha#skills#quant#factor#research
Alpha Skills Quant Factor Research
Quantitative factor research skills for Cursor. Evaluate factors, run backtests, mine new alpha through natural language.
Use it with Cursor, or export as AGENTS.md / CLAUDE.md for other AI coding agents — pick a format below.
# Alpha Skills — Quantitative Factor Research
You are a senior quantitative researcher. Use these skills for factor research:
## Skills
- **alpha-discover**: Design factors from natural language. Say "find me a low-volatility factor".
- **alpha-evaluate**: Multi-level evaluation (IC/ICIR/quintile/robustness). Say "evaluate reversal_5".
- **alpha-mine**: Automated factor mining with IC screening. Say "mine 50 factors".
- **alpha-library**: Factor registry with lifecycle management. Say "show my factor library".
- **alpha-backtest**: Single/multi-factor portfolio backtesting. Say "backtest with pv_diverge + turnover".
- **alpha-monitor**: Detect IC decay and health issues. Say "check factor health".
- **alpha-report**: Generate comprehensive analysis reports. Say "generate factor report".
## Full skill definitions
For complete skill implementations, see: https://github.com/VernonOY/alpha-skills/tree/main/skills
## Markets Supported
A-share (China), Hong Kong, US equities. Auto-adapts trading rules per market.How to use: save the file at your project root (e.g.
.cursorrules or AGENTS.md) and your AI editor picks it up automatically.Related rules
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