riskmodels-api-portal

RiskModels provides factor decompositions and ETF-executable hedge ratios for ~3,000 US equities, with history dating back to 2006. The API is AI-agent ready, including a built-in Model Context Protocol (MCP) server for seamless integration with LLMs.

RiskModels API Developer Portal

This repository is the authoritative public API reference for the RiskModels equity risk model API, featuring:

• 📚 Comprehensive API Documentation — OpenAPI 3.0.3 specification, guides, and examples
• 🌐 Developer Portal — Beautiful Next.js site (this repo) deployed at riskmodels.app
• 🐍 Python & TypeScript Examples — Production-ready code in examples/
• 🤖 AI Agent Integration — MCP server, OAuth2, and agent manifest

🚀 Quick Links

• Developer Portal: riskmodels.app
• Live API Docs: riskmodels.net/docs/api/erm3
• Get API Key: riskmodels.app/get-key
• API Terms: riskmodels.net/terms/api
• Issues: github.com/Cerebellum-Archive/RiskModels_API/issues

📖 API Overview

The RiskModels API provides institutional-grade equity risk analysis:

• Daily factor decompositions — market, sector, subsector explained-risk fractions for ~3,000 US equities
• Hedge ratios — dollar-denominated ETF hedge amounts (L1/L2/L3) designed to remain executable with liquid raw ETFs
• Historical time series — split- and dividend-adjusted returns plus rolling hedge ratios (2006–present)
• AI-agent ready — OAuth2, per-request billing, machine-readable manifests

Data coverage: Universe uni_mc_3000 (~3,000 top US stocks), updated daily.

Why The Engine Matters

RiskModels is designed to be useful for real portfolio work, not just descriptive analytics:

• Built to be time-safe — the engine is designed to avoid common sources of forward contamination such as recycled tickers, snapshot shares, and retroactive universe contraction
• Grounded in a real Security Master — ticker-level outputs sit on top of a point-in-time identity layer built for identifier continuity, symbol changes, and historically defensible shares data
• Hierarchical by design — the model separates market, sector, and subsector structure rather than collapsing everything into a flat beta view
• Tradeable in practice — the published hedge ratios are designed to work with liquid ETFs at execution time, not only with synthetic or orthogonalized factors
• Built on adjusted return series — split- and dividend-adjusted returns make the decomposition and hedge ratios more economically consistent over long horizons

For a deeper explanation of the engine design choices behind these claims, see the methodology docs and API reference.

🐍 Python SDK (riskmodels-py)

Prefer the Python SDK over raw REST for agent-native workflows — ticker resolution, semantic field normalization, validation with instructional errors, and LLM-ready context formatting are built in.

Install:

pip install riskmodels-py[xarray]

Quickstart:

from riskmodels import RiskModelsClient, to_llm_context

client = RiskModelsClient.from_env()
pa = client.analyze({"NVDA": 0.4, "AAPL": 0.6})
print(to_llm_context(pa))

Documentation:

• Package README — install, methods, agent-native helpers
• Quickstart — 60-second setup path
• API Docs — agent-native helpers reference table

🤖 MCP Server (v3.0.0-agent)

RiskModels includes a first-class MCP (Model Context Protocol) server, enabling AI agents to directly query risk data and perform factor analysis.

MCP Connection:

• SSE Endpoint: https://riskmodels.app/api/mcp/sse
• Authentication: Bearer token (API key or OAuth2 JWT)
• Discovery: https://riskmodels.net/.well-known/mcp.json

Available Tools:

• riskmodels_list_endpoints — List all available API endpoints with summaries, tags, and costs
• riskmodels_get_capability — Get detailed schema for a specific capability (e.g., "ticker-returns", "metrics")
• riskmodels_get_schema — Fetch JSON response schema for a given endpoint path
• analyze_portfolio — Analyze portfolio positions with risk metrics and hedge ratios
• hedge_portfolio — Compute optimal hedge notionals using ERM3 factor model
• get_risk_decomposition — Get monthly L3 factor risk decomposition time series

See the mcp-server/ directory for installation and usage instructions.

💻 Developer Portal (This Repo)

This repo now includes a Next.js developer portal with:

• ✨ Hero landing page with feature highlights
• 📚 MDX-powered documentation (README_API.md, AUTHENTICATION_GUIDE.md)
• 🔍 Interactive API reference (Redoc OpenAPI viewer)
• 💡 Code examples with syntax highlighting and copy buttons
• 🎯 Step-by-step quickstart guide

Local Development

# Install dependencies
npm install

# Option A: Copy env template and fill in Supabase/Stripe keys manually
cp .env.example .env.local

# Option B: Use Doppler (recommended for team consistency)
# Ensure `doppler login` is done, then:
doppler secrets download --no-file --format env > .env.local

# Generate OpenAPI JSON for Redoc
npm run build:openapi

# Run dev server
npm run dev

Environment Management with Doppler:

This repo uses Doppler for secrets management. The doppler.yaml is pre-configured for the erm3 project:

# Verify setup (should show project: erm3, config: dev)
doppler setup

# List all secrets
doppler secrets

# Get a specific secret
doppler secrets get STRIPE_SECRET_KEY

# Export dev secrets to .env.local for curl testing and local dev
npm run doppler:env

# Push production secrets to Vercel (requires vercel login + project link)
npm run vercel:sync-env:doppler

For curl/API testing with Doppler secrets:

# 1. Export secrets to .env.local
npm run doppler:env

# 2. Source them for your shell session
source .env.local

# 3. Use in curl commands
curl -H "Authorization: Bearer $RISKMODELS_API_SERVICE_KEY" \
  https://riskmodels.app/api/health

See DEPLOYMENT.md for detailed Vercel/Doppler integration.

Visit http://localhost:3000

Build & Deploy

# Build for production
npm run build

# Start production server
npm start

Deployment: See DEPLOYMENT.md for Vercel setup, env vars, and Supabase/Stripe config.

📂 Repository Structure

RiskModels_API/
├── app/                      # Next.js app (new)
│   ├── page.tsx              # Hero landing page
│   ├── layout.tsx            # Root layout with Navbar/Footer
│   ├── docs/[[...slug]]/     # MDX docs renderer
│   ├── api-reference/        # Redoc OpenAPI viewer
│   ├── examples/             # Code examples showcase
│   └── quickstart/           # Quickstart guide
├── components/               # React components (new)
│   ├── Navbar.tsx
│   ├── Footer.tsx
│   ├── Hero.tsx
│   ├── CodeBlock.tsx
│   └── Logo.tsx
├── content/docs/             # MDX content (new)
│   ├── api.mdx
│   └── authentication.mdx
├── examples/                 # Original examples
│   ├── python/
│   └── typescript/
├── mcp-server/               # MCP (Model Context Protocol) server
├── public/                   # Static assets (new)
│   ├── transparent_logo.svg
│   └── openapi.json          # Generated from OPENAPI_SPEC.yaml
├── styles/                   # Global styles (new)
├── lib/                      # Utilities (new)
├── OPENAPI_SPEC.yaml         # Canonical OpenAPI spec
├── README_API.md             # API reference (source for content/docs/api.mdx)
├── AUTHENTICATION_GUIDE.md   # Auth guide (source for content/docs/authentication.mdx)
├── SEMANTIC_ALIASES.md       # Field definitions
└── package.json              # Next.js deps (new)

🛠️ Tech Stack (Developer Portal)

• Framework: Next.js 15 (App Router)
• Styling: Tailwind CSS 3.4, dark mode default
• MDX: @next/mdx for documentation
• API Reference: Redoc (OpenAPI 3.0 viewer)
• Code Highlighting: Custom CodeBlock with copy button
• Fonts: Inter (system-ui fallback)
• Colors: Blue primary (hsl(217, 91%, 60%)), zinc/slate dark palette

Borrowed visual style from Risk_Models (logo, colors, typography).

📄 Documentation Files

Document	Description
README_API.md	Complete API overview, endpoints, key concepts
API_TERMS.md	API Terms of Service (riskmodels.net/terms/api)
PLAID_HOLDINGS_UX.md	Plaid connection flow and holdings API user experience
AUTHENTICATION_GUIDE.md	Bearer token, OAuth2, Supabase JWT, rate limits
DOCS_PROCESS.md	Process for adding new documentation
SEMANTIC_ALIASES.md	Field definitions, units, formulas
RESPONSE_METADATA.md	_agent block, response headers, pricing
ERROR_SCHEMA.md	Error codes and recovery patterns
OPENAPI_SPEC.yaml	OpenAPI 3.0.3 specification (v3.0.0-agent)

🔗 Related Repositories

• Risk_Models — Next.js production app (riskmodels.net)
• ERM3 — Python risk model computation engine
• BWMACRO — High-level docs and tracking

🤝 Contributing

We welcome pull requests, especially to improve the OpenAPI spec — clearer descriptions, better schemas, and more examples help everyone.

• OpenAPI spec: CONTRIBUTING.md — PRs to OPENAPI_SPEC.yaml are encouraged
• Issues: Open an issue for bugs or feature requests
• Examples: Submit new examples via PR to examples/
• Docs: Improve documentation by editing MDX files in content/docs/

📧 Support

• API Support: [e-mail]
• Issues: github.com/Cerebellum-Archive/RiskModels_API/issues
• Status: riskmodels.net/status

📜 License

See LICENSE for details.

© 2026 Blue Water Macro Corp. All rights reserved.