  Extremal dependence between international stock markets is of particular
interest in today's global financial landscape. However, previous studies have
shown this dependence is not necessarily stationary over time. We concern
ourselves with modeling extreme value dependence when that dependence is
changing over time, or other suitable covariate. 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.
