Variance-Covariance Approach

The variance-covariance approach is a parametric method for calculating Value at Risk that assumes asset returns follow a normal distribution. It relies on the estimated standard deviation of asset returns and the correlations between assets in a portfolio.

By multiplying these factors, the model determines the potential loss at a specific confidence level. This method is computationally efficient and provides a quick estimate of risk for large portfolios.

However, its reliance on the assumption of normality is a significant drawback in crypto markets, where returns often exhibit extreme outliers. It tends to underestimate the probability of severe market crashes.

Because it assumes linear relationships, it may also fail to accurately measure the risk of complex derivative positions. While useful for a quick assessment, it is often supplemented by more robust simulation methods.

It remains a foundational concept in classical portfolio theory.