Multivariate Extreme

Multivariate extreme value theory (EVT) focuses on modeling and understanding the joint behavior of multiple variables at their extreme values, crucial for risk assessment in diverse fields like finance and environmental science. Current research emphasizes developing robust and accurate generative models, employing techniques like distributionally robust optimization, variational autoencoders, and normalizing flows tailored to handle heavy-tailed distributions and complex dependence structures. These advancements leverage machine learning methods alongside traditional EVT approaches, improving the estimation of multivariate extremes and their underlying dependencies, leading to more reliable risk predictions.