risk-analysis

You can calculate VaR and CVaR for a portfolio by providing your net-asset values or return series to compute historical, parametric, and Monte Carlo risk estimates. This process outputs deterministic, reproducible risk metrics for decision-making.

To measure maximum drawdown and tail risk in backtests, apply peak-to-trough decline analysis alongside extreme-value theory concepts to assess fat tails. This yields structured risk reporting that identifies severe portfolio declines and tail-risk exposure.

Yes, you can run stress testing across multiple asset classes using both historical and hypothetical scenarios. The framework evaluates portfolio resilience under adverse conditions and generates actionable risk insights for risk managers and traders.

Yes, you need to provide your portfolio returns or net-asset values as input data to perform Monte Carlo risk simulation. This initial data allows the framework to compute forward-looking risk estimates, VaR, CVaR, and drawdown metrics.

Yes, historical VaR calculation produces deterministic and reproducible results suitable for structured risk reporting. The computation applies historical, parametric, and Monte Carlo methods to deliver consistent risk metrics for decision-making.

Use parametric VaR for rapid, distribution-assumption-based risk estimates, while Monte Carlo simulation suits forward-looking scenario analysis and complex tail-risk modeling. Monte Carlo evaluates extreme-value concepts to assess fat tails across multiple asset classes.