risk-metrics-calculation

To calculate VaR and CVaR for a portfolio, provide a time series of numeric periodic returns. The toolkit computes historical, parametric, and Cornish-Fisher VaR alongside CVaR to quantify potential portfolio losses under different assumptions.

Key risk-adjusted metrics for portfolio performance include Sharpe, Sortino, Calmar, and Omega ratios. These metrics evaluate returns relative to risk exposure, accounting for volatility and downside deviation to provide performance attribution.

Yes, you can compute rolling risk metrics and run stress-testing scenarios for multi-asset portfolios. The calculation supports dynamic market monitoring by applying configurable annualization and horizons across your input returns.

To measure maximum drawdown and drawdown duration, input your numeric returns series. The toolkit calculates the peak-to-trough decline and the duration of the recovery period to quantify portfolio risk exposure.

You need a time series of numeric periodic returns as input data, along with optional benchmark data. The calculations use numpy, pandas, and scipy to process the returns and generate a full risk summary.

Portfolio risk calculation supports both single-asset and multi-asset portfolios. It computes VaR, CVaR, drawdowns, and risk-adjusted metrics across rolling and stress-testing scenarios for either asset scope.