correlation-crisis

Stress-test a portfolio by computing separate correlation matrices for calm, mid, high, and crisis regimes, then simulating regime shifts to evaluate portfolio resilience and hedging effectiveness under each condition.

Asset correlations typically increase during market crises, reducing diversification benefits and elevating tail risk; regime-aware correlation analysis isolates these crisis-period matrices to quantify true extreme-event exposure.

Use Value at Risk (VaR), Conditional Value at Risk (CVaR), maximum drawdown, and tail ratio to assess extreme event exposure and quantify potential portfolio losses during crisis regimes.

Build regime-dependent hedging strategies by analyzing regime-specific correlation matrices across multi-asset portfolios, identifying diversification gaps in crisis periods, and stress-testing hedges against simulated regime shifts.

Yes, monitor portfolio tail-risk exposure by applying dynamic regime classification to continuously assess regime-specific correlation matrices and calculate reporting metrics like VaR and CVaR for each regime.

Identify diversification gaps by computing regime-specific correlation matrices and comparing calm-period correlations against crisis-period correlations to detect assets that lose diversification benefits under stress.