risk-analysis

To calculate VaR and CVaR, the skill uses statistical modeling and extreme value theory to quantify potential losses and identify fat-tail risks within your portfolio's loss distribution. It provides professional-grade financial risk metrics for comprehensive assessment.

You can stress test your portfolio by simulating its performance against historical crises like the 2020 COVID shock or hypothetical market shocks like sudden rate hikes. This evaluates portfolio resilience under extreme financial conditions.

Yes, you can run Monte Carlo simulations to project future price paths using Geometric Brownian Motion. This estimates loss probabilities and helps evaluate potential drawdowns for your financial portfolio.

Yes, this risk analysis tool requires numpy, pandas, and scipy as dependencies to perform statistical modeling and comprehensive financial risk measurement. These libraries support the underlying calculations for VaR and Monte Carlo simulations.

CVaR and maximum drawdown analysis help you move beyond simple volatility metrics to understand extreme tail risks and potential loss distributions. This approach reveals your portfolio's vulnerability to severe market drops and crisis scenarios.