Skills

Alpha Zoo

Browse and bench the bundled alpha zoos, prebuilt cross-sectional factor libraries...

Install

npx skills add HKUDS/Vibe-Trading --skill alpha-zoo -g -a claude-code -y
Repository
HKUDS/Vibe-Trading37.4k
Category
Engineering
Updated
3d ago
License
MIT
Context cost
Lightabout 866 tokens
Runs scripts
No, instructions only

What it does

Browse and bench the bundled alpha zoos, prebuilt cross-sectional factor libraries (Kakushadze 101, GTJA 191, Qlib 158, Fama-French / Carhart). Use when the user asks "which alphas exist", wants metadata on a named alpha, or wants to run IC/IR on a whole zoo over a universe.

Alpha Zoo

Purpose

When the user asks about prebuilt cross-sectional alphas, Kakushadze 101, GTJA 191, Qlib 158, Fama-French / Carhart, or wants to bench a whole zoo on an investable universe (CSI 300, S&P 500, BTC-USDT, ...), this skill orients you. The zoo is the curated library; the bench is the evaluator.

Tools Available

ToolWhen to use
alpha_zooBrowse the library. action=list_alphas to enumerate (filterable by zoo / theme / universe), action=get_alpha for one alpha's metadata, action=health for registry load status.
alpha_benchRun IC / IR on one alpha or a whole zoo over a universe + period. Emits an HTML report.
factor_analysisAd-hoc factor evaluation from a user-supplied factor CSV + return CSV. Use this when the user has their own factor (not in the zoo).

Decision Tree

  • "list all momentum alphas" → alpha_zoo with action=list_alphas, theme=momentum.
  • "show me gtja191_alpha_001" → alpha_zoo with action=get_alpha, alpha_id=gtja191_alpha_001.
  • "bench all of GTJA 191 on CSI 300 from 2020 to 2024" → alpha_bench with zoo=gtja191, universe=csi300, period=2020-2024.
  • "is the registry healthy" → alpha_zoo with action=health, surfaces loaded, failed, and per-error reasons.
  • User uploads my_factor.csv → factor_analysis (zoo tools are for prebuilt alphas only).

Zoo Inventory

ZooDescriptionApprox. count
kakushadze101Formulaic alphas from Kakushadze's 2015 paper. Mix of momentum, reversal, volume, and microstructure.~101
gtja191Guotai Junan 191 alphas, A-share focused cross-sectional factors.~191
qlib158Microsoft Qlib's 158 alpha factors, features tuned for ML pipelines.~158
classicalFama-French 3/5-factor + Carhart momentum.<10

Counts are nominal; check alpha_zoo action=health for the live count currently loaded.

Constraints

Read the whole SKILL.md on GitHub

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