ABSTRACT
Abstract Multivariate extreme value distributions are useful in modeling extreme dependence within a multivariate random vector. In order to model dynamic dependency of extreme values in spatial and time series data, some parametric models have been proposed in the literature, which share some important properties of a multivariate extreme value distribution and are employed to studies of weather extremes, extreme co-movements of financial markets, economic contagions, material reliability, and internet traffic analyses. This chapter provides an overview of the current development of these models.
