# Market Risk

> Institutional-grade equity analysis for self-directed investors.

Website: https://www.marketrisk.dev
Builder: 132 Engineering (https://www.132eng.dev)
Full context: https://www.marketrisk.dev/llms-full.txt

## What It Does

Enter a stock ticker. The engine runs 18 analytical methods in your browser and produces 19 interactive visualisations with contextual education on every chart. All computation is client-side JavaScript — fully transparent, no black boxes.

## Key Features

- **Stochastic DCF** — 5,000 Monte Carlo simulations of a discounted cash flow model. Produces a fair value distribution, not a single number.
- **Monte Carlo Simulation** — 5,000 GBM price paths. Probability of profit, expected return, P10–P90 range, fan chart.
- **Risk Metrics** — VaR, CVaR, volatility cone, Sharpe, Sortino, max drawdown, mean reversion Z-score.
- **Factor Regression** — Four-factor OLS decomposition with R², alpha, and per-factor betas.
- **Stress Testing** — Sector-specific scenarios with per-factor impact breakdown.
- **Portfolio Engine** — Cholesky decomposition Monte Carlo, efficient frontier, correlation matrix, diversification ratio.
- **Sector Models** — 11 GICS sectors with appropriate valuation models. Banks use DDM with tangible book anchor. REITs use NAV floor. Utilities use regulated rate base.
- **Chart Insight System** — Click any chart for contextual analysis (your numbers explained) and educational background (what the method is, its history, how professionals use it).

## Pricing

$25/month or $150/year

## Technical Stack

Node.js, Express, EJS, Alpine.js, Supabase (Postgres + Auth), Plotly, Chart.js. Data from Financial Modeling Prep and FRED. ~15,300 lines of code. 30 API endpoints. 100% client-side computation.

## Pages

- /dashboard — Saved analyses and portfolios
- /search — Stock ticker search
- /analysis/:id — Full analysis with 19 charts
- /strategy/:id — Portfolio view with correlation, frontier, stress tests
- /onboarding — Risk profiling questionnaire