Most investing tools show correlations. CausalFolio shows causes. We use structural causal models to separate market noise from true company signals — producing alpha you can actually trust.
Unlike correlation-based tools, CausalFolio uses structural causal models (SCM) to separate market noise from company-specific alpha.
Decomposes portfolio covariance Σ_obs = Σ_do + C. The interventional matrix Σ_do removes macro confounders, producing stress-resistant allocations.
Perplexity-powered live web research delivers earnings data, analyst consensus, and competitive landscape — updated every run.
Federal Reserve economic data (FFR, VIX, CPI) integrated as causal covariates, not just decorative overlays.
| FEATURE | CAUSALFOLIO | OTHERS |
|---|---|---|
| Factor attribution method | Causal SCM (OLS + do-calculus) | Correlation / factor models |
| Portfolio construction | Σ_do (interventional covariance) | Σ_obs (confounded covariance) |
| Macro integration | FRED FFR, VIX, CPI as covariates | Manual overlay / decorative |
| AI intelligence | Live Perplexity web research | Static news aggregation |
| Confound detection | φ̄ confounded fraction metric | Not available |
| Regime analysis | High/low vol regime decomposition | Not available |
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All analysis is for research purposes only and does not constitute investment advice. Market data sourced from Yahoo Finance, FRED, and Perplexity.