Time-varying extreme value dependence with application to leading European stock markets

We concern ourselves with modeling extreme value dependence when that dependence is changing over time, or other suitable covariate. Modeling nonstationarity in marginal distributions has been the focus of much recent literature in applied extreme value modeling. By comparison, approaches to modeling nonstationarity in the extremal dependence structure have received relatively little attention. Working within a framework of asymptotic dependence, we introduce a regression model for the angular density of a bivariate extreme value distribution that allows us to assess how extremal dependence evolves
over a covariate. We apply the proposed model to assess the dynamics governing extremal dependence of some leading European stock markets over the last three decades, and find evidence of an increase in extremal dependence over recent years.