Enterprise Feature
This feature is available on the Enterprise plan. The documentation below describes its full capabilities so you can evaluate whether it fits your workflow. Contact us to learn more about upgrading your access.
Overview
Factor Intelligence uses Principal Component Analysis (PCA) to decompose market returns into underlying factor exposures. It reveals the hidden risk factors driving stock prices, shows how sectors and individual stocks load onto these factors, and provides actionable insights for factor-based portfolio construction and risk management.
What is PCA?
Principal Component Analysis is a statistical method that transforms a large set of correlated variables (stock returns) into a smaller set of uncorrelated variables called principal components (factors). Each factor captures a different dimension of market behavior. The first factor typically captures the most variance and often represents broad market risk.
Note
Tabs
Summary of the PCA analysis including variance explained by each factor, the factor loadings matrix, and key statistics.
- -Scree plot showing variance explained per factor
- -Cumulative variance explained chart
- -Top factor loadings table
- -Factor interpretation suggestions
Sector-level factor exposure heatmap showing how each GICS sector loads onto the principal components.
- -Sector x Factor correlation heatmap
- -Sector clustering by factor exposure
- -Cross-sector diversification insights
Individual stock factor loadings table. Search any stock to see its exposure to each factor.
- -Searchable stock factor loadings table
- -Factor exposure bar chart per stock
- -Peer comparison by factor profile
Understanding Factor Columns
Each column labeled F1, F2, F3, etc. represents a principal component (factor). The values in these columns are factor loadings, which indicate how strongly a stock or sector is influenced by that factor.
| Loading Value | Interpretation |
|---|---|
| > +0.5 | Strong positive exposure — stock moves with this factor |
| +0.2 to +0.5 | Moderate positive exposure |
| -0.2 to +0.2 | Weak exposure — factor has minimal influence |
| -0.5 to -0.2 | Moderate negative exposure — moves against this factor |
| < -0.5 | Strong negative exposure — moves inversely with this factor |
Portfolio Applications
- ●Factor Tilting: Overweight stocks with desired factor exposures
- ●Risk Decomposition: Understand what factors drive your portfolio risk
- ●Hedging: Identify stocks or sectors with offsetting factor exposures
- ●Diversification: Ensure portfolio spans multiple independent factors
How to Use
- ●Start with the Overview tab to understand the factor structure
- ●Review the Sectors tab to see which sectors share similar factor profiles
- ●Use the Stocks tab to analyze factor exposure for specific positions
- ●Look for stocks with complementary factor profiles for diversification
- ●Monitor factor shifts over time as market regimes change
Combining with Other Tools
- ●Use factor loadings to check your Portfolio Manager holdings for unintended factor concentrations
- ●Cross-reference sector factor loadings with ETF Technical scores to confirm sector rotation signals
- ●Combine with Market Regimes — different factors lead in different regimes (momentum in bull, value in recovery)
- ●Use factor analysis insights to build better-diversified portfolios in the Portfolio Manager
This platform provides data and analysis tools for educational and informational purposes only. Nothing on this platform constitutes financial advice, investment recommendations, or solicitation to buy or sell any securities. Always conduct your own research and consult with a qualified financial advisor before making investment decisions.