Extreme Value Theory

Extreme Value Theory (EVT) focuses on modeling and predicting the probability of rare, extreme events, crucial for risk assessment in diverse fields. Current research emphasizes robust estimation of EVT parameters, particularly in high-dimensional settings, employing techniques like distributionally robust optimization, generative adversarial networks (GANs), and various deep learning architectures to address data scarcity and model misspecification. These advancements improve the accuracy of risk predictions in applications ranging from finance and climate modeling to machine learning algorithm performance analysis and network anomaly detection. The resulting improved risk assessments have significant implications for decision-making across numerous sectors.