skills.rest
JacobHsu
JacobHsuCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

factor-research

Compute IC/IR metrics and quantile backtests for candidate factors from aligned CSV inputs.

Updated Apr 9, 2026
Search Tags:#python#multi-factor#investment-research#factor-analysis#ic-ir#quantile-backtest
One-click install
npx skills add https://github.com/JacobHsu/vibe-trading-agent --skill factor-research-jacobhsu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: factor-research
Source: https://github.com/JacobHsu/vibe-trading-agent/tree/main/agent/src/skills/factor-research
Command: npx skills add https://github.com/JacobHsu/vibe-trading-agent --skill factor-research-jacobhsu

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill eliminates guesswork when evaluating candidate factor signals by systematically applying IC/IR statistics and quantile backtests to aligned factor and return datasets. Without these diagnostics, analysts waste time building spreadsheets, risk look-ahead bias, and misinterpret whether a factor truly separates winners from losers.

Core Features & Use Cases

  • IC/IR Computation & Standards: Generates daily IC series, IC summaries, and IR metrics while flagging thresholds for predictive power, stability, and directional consistency.
  • Quantile Backtesting Insight: Produces group equity curves, long-short spreads, and monotonicity cues so you can detect nonlinear or unstable factors and consider reversing weak signals.
  • Factor Combination Recommendations: Explores equal-weight, IC-weighted, and orthogonalized aggregation strategies to merge validated factors into a composite signal for portfolio construction, such as blending momentum and value in A-share universes.

Quick Start

Ask the agent to run the factor_analysis tool on your prepared factor and return CSVs and save the IC/IR summaries plus quantile equity curves into a designated output folder.

Frequently Asked Questions about factor-research

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

FAQPage Schema
How do I compute IC and IR metrics for multi-factor investment research?▼

To compute IC and IR metrics for multi-factor investment research, you can use automated factor analysis tools that process aligned factor and return CSV files to generate daily IC series, summaries, and IR statistics.

How do I run a quantile backtest on cross-sectional equity factors?▼

Running a quantile backtest on cross-sectional equity factors requires feeding aligned factor and return CSV files into a factor analysis tool, which then produces group equity curves, long-short spreads, and monotonicity cues.

Can I evaluate A-share or crypto factors using quantile backtests and IC analysis?▼

Yes, you can evaluate A-share, US/HK equities, crypto, or futures factors using quantile backtests and IC analysis, provided you supply aligned factor and return CSV datasets for the respective markets.

What is the best way to combine multiple validated factors into a composite signal?▼

The best way to combine multiple validated factors into a composite signal is by exploring equal-weight, IC-weighted, and orthogonalized aggregation strategies to merge validated factors for portfolio construction.

Why does my factor backtest show weak or unstable predictive power?▼

Your factor backtest may show weak or unstable predictive power if the quantile group equity curves lack monotonicity, indicating a nonlinear or unstable factor that may require signal reversal.

Do I need aligned CSV inputs to evaluate factor strength with IC/IR metrics?▼

Yes, you need aligned factor and return CSV files plus an output directory parameter to deterministically generate IC series, summaries, and group equity curves when evaluating factor strength.

Related Skills

Explore More Finance & Accounting Skills→
ebrahim-saniebrahim-sani

factor-research

Evaluate cross-sectional financial factors with IC/IR statistics and quantile backtests.

Community
Intermediate
GGwujunGGwujun

multi-factor

Rank stocks by standardizing momentum, reversal, volatility, and volume_ratio factors.

Community
Advanced
loanntcloanntc

factor-research

Compute IC/IR stability and quantile backtests for cross-sectional factor signals.

Community
Intermediate
Liangwei-zhangLiangwei-zhang

factor-research

Compute cross-sectional factor exposures and forward returns with IC/IR metrics and quantile backtests.

Community
Intermediate