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alpha-zoo

Evaluate financial cross-sectional factor libraries with Python and HTML reporting.

Updated May 25, 2026
Search Tags:#financial research#factor analysis#alpha zoo#IC/IR#universe analysis
One-click install
npx skills add https://github.com/NigarumOvum/AutoTrading --skill alpha-zoo-nigarumovum
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: alpha-zoo
Source: https://github.com/NigarumOvum/AutoTrading/tree/main/Vibe-Trading/agent/src/skills/alpha-zoo
Command: npx skills add https://github.com/NigarumOvum/AutoTrading --skill alpha-zoo-nigarumovum

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill simplifies financial research by providing access to a collection of pre-built cross-sectional factor libraries and the tools to evaluate them.

Core Features & Use Cases

  • Browsing Alphas: List available alphas, retrieve metadata, and check the health of the registry.
  • Benchmarking Alphas: Run IC/IR on alphas or entire zoos over specified universes and periods.
  • Custom Factor Evaluation: Analyze user-supplied factors from CSV files.
  • Use Case: When analyzing financial data, you can use this skill to quickly assess the performance of various alpha factors or entire libraries against a given universe.

Quick Start

Use the alpha-zoo skill to benchmark the GTJA 191 alpha zoo on the S&P 500 from 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 run cross-sectional factor analysis on a custom universe?▼

Cross-sectional factor analysis evaluates financial factor libraries by calculating IC/IR metrics over specified universes and periods. You can benchmark pre-built alpha zoos or analyze user-supplied custom factors from CSV files.

What is an alpha zoo in financial research?▼

An alpha zoo is a curated collection of pre-built cross-sectional factor libraries used for investment research. It allows you to browse available alphas, retrieve metadata, and check the health of the factor registry.

Can I evaluate my own custom financial factors from a CSV file?▼

Yes, you can evaluate custom financial factors supplied via CSV files. The skill processes these user-supplied factors to calculate performance metrics and generate HTML reports for your investment research workflows.

What's the best way to benchmark GTJA 191 alphas on the S&P 500?▼

Benchmarking GTJA 191 alphas on the S&P 500 utilizes Python to calculate IC/IR metrics over a specified period. This skill applies the factor library directly to your target universe to assess performance results.

Does this factor analysis tool require any specific Python dependencies?▼

No specific Python dependencies are required. The skill operates independently to perform universe analysis and factor evaluation, utilizing Python internally for calculations and HTML for reporting outputs.

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