VaRBridge

VaRBridge is a web app that generates defensible Value-at-Risk for small-to-mid investment teams who don’t have a quant stack. It connects to custodians/brokers and CSVs, normalizes positions, and runs standard VaR methods (historical, parametric, Monte Carlo) with clear assumptions, data-quality flags, and audit-ready exports. The product is intentionally boring: fewer models, more reliability. An AI assistant helps map tickers/identifiers, detect corporate actions, and explain why VaR moved (e.g., concentration, volatility spike, correlation shift) without pretending to “predict markets.” It also provides stress scenarios (rate shock, equity drawdown, FX move) alongside VaR so risk isn’t a single number. Expect limits: if data is bad or illiquid assets dominate, the app will say so and quantify confidence bands rather than fabricate precision.