We propose a model that can capture the typical features of multivariate extreme events observed in financial time series,namely clustering behavior in magnitudes and arrival times of multivariate extreme events,and time-varying dependence.The model is developed in the framework of the peaks-over-threshold approach in extreme value theory and relies on a Poisson process with self-exciting intensity.We discuss the properties of the model,treat its estimation,deal with testing goodness-of-fit,and develop a simulation algorithm.The model is applied to return data of two stock markets and four major European banks.This is a joint work with Oliver Grothe and Volodymyr Korniichuk.