evaluate-cross-sectional
CommunityAssess cross-sectional factor performance for stock selection.
Finance & Accounting#quantitative research#stock selection#turnover#ic#icir#factor evaluation#cross-sectional factor
Authorxingwudao
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Manually calculating and interpreting cross-sectional factor performance metrics is time-consuming, error-prone, and inconsistent, especially for AI agents that require standardized, reproducible evaluation workflows for stock selection and multi-asset ranking strategies.
Core Features & Use Cases
- Standardized Metric Calculation: Computes core cross-sectional factor evaluation metrics including IC, Rank IC, ICIR, multi-horizon decay, and turnover in a single consistent workflow.
- Built-in Best Practice Enforcement: Includes a review checklist and explicit red lines to prevent common errors like forward-return leakage, insufficient symbol counts, and ignoring trading cost impacts from high turnover.
- Use Case: A quantitative researcher can use this skill to evaluate a 20-day price momentum factor across 500 S&P 500 stocks to determine if the factor has sufficient predictive power and stability to be included in a live trading strategy.
Quick Start
Use the evaluate-cross-sectional skill to assess the performance of your cross-sectional value factor across mid-cap US stocks for the past 3 years.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: evaluate-cross-sectional Download link: https://github.com/xingwudao/open-xquant/archive/main.zip#evaluate-cross-sectional Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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