risk-analysis

Portfolio VaR and CVaR calculations use historical, parametric, and Monte Carlo methods to quantify risk. Monte Carlo VaR simulates diverse market conditions to estimate potential losses, while CVaR measures tail risk beyond the VaR threshold.

Historical VaR computes risk directly from past return series data, whereas parametric VaR assumes a specific statistical distribution. Both methods quantify portfolio risk, but parametric VaR offers faster computation while historical VaR captures actual market dynamics.

Stress testing applies historical and hypothetical scenarios to a portfolio return series to evaluate performance under adverse market conditions. This risk analysis computes maximum drawdown and scenario-based risk decompositions to identify vulnerabilities across diverse market events.

EVT tail estimation using the POT method is needed when analyzing extreme tail risk beyond standard VaR models. It estimates extreme value theory parameters for rare market events, providing more accurate risk metrics for severe portfolio losses than historical or parametric approaches.

Maximum drawdown analysis runs alongside VaR, CVaR, and stress test modules within a single risk-analysis workflow. Loading the provided return series executes all risk metrics together, delivering comprehensive portfolio risk quantification across multiple market conditions.