Introduction to Extreme Value Theory: Applications to Risk Analysis and Management

Abstract

We present an overview of Univariate Extreme Value Theory (EVT) providing standard and new tools to model the tails of distributions. One of the main issues in the statistical literature of extremes concerns the tail index estimation, which governs the probability of extreme occurrences. This estimation relies heavily on the determination of a threshold above which a Generalized Pareto Distribution (GPD) can be fitted. Approaches to this estimation may be classified into two classes, one qualified as `supervised', using standard Peak Over Threshold (POT) methods, in which the threshold to estimate the tail is chosen graphically according to the problem, the other class collects unsupervised methods, where the threshold is algorithmically determined.