Open-source Barra-style US equity factor risk model — daily estimation, weekly builds, public validation. Free artifacts, MCP server for AI agents.
View on GitHub ↗Decompose US equity portfolio risk into its factor spectrum.
Explorer: https://risk-prism-production.up.railway.app · Agent model card: /model.md
An open-source, Barra-style fundamental factor risk model built to be usable by AI agents out of the box: a Python library, an MCP server, and weekly-published model artifacts covering most liquid US common stocks.
- 9 style factors (size, value, growth, momentum, beta, volatility, liquidity, quality, leverage — value, quality and leverage are multi-descriptor composites, volatility is beta-orthogonalized residual volatility) + 30 industries (Fama-French scheme) + a market factor - Free, redistributable data chain: fundamentals and SIC codes from SEC EDGAR (public domain), prices from pluggable providers - Hybrid distribution: precomputed artifacts (exposures, factor covariance, specific risk) are published on a weekly schedule, and the full pipeline is open so anyone can reproduce or extend them
Disclaimer: research software, provided as-is. Nothing here is investment advice.
The live deployment serves a JSON API over the newest weekly build — interactive docs at /api/docs:
Endpoints: GET /api/v1/meta · GET /api/v1/factors · GET /api/v1/assets/{ticker} · GET /api/v1/coverage?tickers=… · POST /api/v1/portfolio-risk · POST /api/v1/stress-test · GET /api/v1/registry (catalog of published builds). Same surface as the MCP server; self-host it with pip install ".[api]" && riskprism-api (artifacts auto-download from the latest release at boot). Details in docs/API.md.
From the project README.
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