Factor Analysis Skill

Workflow Checklist

Copy and track progress:

code

Factor Analysis Progress:
- [ ] Step 1: Define asset universe and analysis window
- [ ] Step 2: Gather return series and benchmark context
- [ ] Step 3: Run Fama-French factor regression
- [ ] Step 4: Interpret factor loadings and significance
- [ ] Step 5: Translate exposures into practical actions

Step 1: Define Universe and Window

Confirm target under analysis:

•Single asset, strategy, or portfolio
•Frequency (daily/weekly/monthly)
•Lookback window and sub-periods

State expectations before computation (e.g., growth tilt, quality tilt) so output can validate or challenge priors.

Step 2: Gather Return Series and Context

Use financial_research to collect adjusted price history and compute returns for:

•Target asset/portfolio
•Relevant benchmark index

Ensure data quality:

•Missing values handled
•Corporate actions reflected in adjusted series
•Calendar alignment across series

If regime context is needed, use financial_research news/macro events to explain structural shifts.

Step 3: Run Fama-French Analysis with quant_analysis

Use quant_analysis with run_factor_analysis.

Expected output components:

•Alpha estimate
•Betas to core factors (e.g., market, size, value, profitability, investment)
•Fit quality and confidence indicators

If available, run rolling-window factor analysis to detect exposure drift over time.

Step 4: Interpret Loadings and Significance

Interpret each exposure in investment terms:

•Positive/negative sign implications
•Economic meaning of magnitude
•Stability across periods

Separate statistically meaningful effects from noise.

Highlight red flags:

•Unintended concentration in one factor
•Unstable betas across regimes
•Alpha disappearing after factor adjustment

Step 5: Translate to Actionable Portfolio Decisions

Convert findings into practical guidance:

•Keep exposures that match stated objective
•Reduce unintended factor bets
•Add complementary assets/strategies to rebalance style drift

If optimization is needed, suggest follow-up with quant_analysis portfolio optimization while preserving desired factor profile.

Close with:

•Current factor fingerprint
•Main source of return and risk
•Monitoring triggers for re-running factor analysis