alpha-zoo

Benchmark alpha factor libraries using IC and IR metrics.

Updated Jun 30, 2026
One-click install
npx skills add https://github.com/20YN04/vibe-trading-macos --skill alpha-zoo-20yn04
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: alpha-zoo
Source: https://github.com/20YN04/vibe-trading-macos/tree/main/agent/src/skills/alpha-zoo
Command: npx skills add https://github.com/20YN04/vibe-trading-macos --skill alpha-zoo-20yn04

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill solves the complexity of managing and evaluating large libraries of quantitative trading factors, allowing users to quickly identify and test alpha signals without manual coding.

Core Features & Use Cases

  • Alpha Library Browsing: Explore prebuilt factor libraries like Kakushadze 101, GTJA 191, and Qlib 158 with metadata filtering.
  • Performance Benchmarking: Run IC and IR analysis on specific factors or entire zoos across defined universes and time periods.
  • Use Case: A researcher wants to compare the performance of all momentum-based factors from the GTJA 191 library against the CSI 300 index over the last four years to identify high-potential signals.

Quick Start

Use the alpha_bench tool to run an evaluation of the gtja191 zoo on the csi300 universe for the period 2020 to 2024.

Frequently Asked Questions about alpha-zoo

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I benchmark quantitative alpha factors across different market universes?

To benchmark quantitative alpha factors, use the alpha_bench tool to evaluate specific factor libraries against defined market universes and time periods, generating IC and IR performance reports without lookahead bias.

What prebuilt cross-sectional alpha factor libraries are available for systematic evaluation?

Available prebuilt cross-sectional alpha factor libraries include Kakushadze 101, GTJA 191, and Qlib 158, which you can explore and filter using metadata to identify high-potential trading signals.

Can I test momentum-based factors from the GTJA 191 library against the CSI 300 index?

Yes, you can evaluate momentum-based factors from the GTJA 191 library against the CSI 300 universe over a specified time period to compare performance and identify high-potential alpha signals.

How do I run an IC and IR analysis on an alpha factor zoo without lookahead bias?

Run IC and IR analysis on an alpha factor zoo by using the alpha_bench tool, which systematically evaluates factor performance across market universes while ensuring reports are generated without lookahead bias.

Does alpha factor benchmarking require integration with internal registry and factor analysis modules?

Yes, alpha factor benchmarking requires integration with internal registry and factor analysis modules to execute performance reports and systematically evaluate cross-sectional alpha signals without manual coding.