
Factor Research Framework
Test whether stock factors predict returns using IC/IR stats and quantile backtests
- Repository
- HKUDS/Vibe-Trading
- Stars
- 37,433
- Licence
- MIT
- Files
- 4 files
What it does
When installed, the agent can evaluate whether a numeric signal (such as momentum, value, or volatility) actually helps pick winning instruments across a group of stocks or other assets. It guides the agent to build aligned factor and forward-return tables, call a factor_analysis tool, and judge results using IC/IR statistics and quantile group backtests. It can also help combine several factors into a composite using equal, IC-based, or orthogonalized weights.
Great for
- Quantitative researchers screening candidate alpha factors across many instruments
- Analysts who want a structured, look-ahead-aware way to compare factors and weight them
Skip it if
- Casual investors looking for stock picks: the skill evaluates factor statistics, not investment advice, and backtest results can mislead when overfit
- Single-asset price forecasting: the framework is designed for cross-sectional evaluation across multiple instruments
Try asking
- “Test whether a 20-day momentum factor has predictive power across my stock universe”
- “Compare IC and IR for value and quality factors and tell me which to keep”
- “Build an IC-weighted composite of my three factors using a 252-day trailing window”
- “Check whether my volatility factor shows monotonic quantile group returns”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 4 original files, the MIT licence and an attribution note.
factor-research.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip factor-research.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip factor-research.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Verify that factor and return CSVs align exactly by date and code, and that returns are forward returns after the observation date, to avoid look-ahead bias
- Treat IC mean above 0.10 as a warning sign to check for data leakage rather than a success
- Use out-of-sample testing before relying on any factor or weighting scheme
What's inside
- references/combination.md
- references/neutralization.md
- references/research_contract.md
- SKILL.md
Redistributed unmodified from HKUDS/Vibe-Trading under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.