We propose a nonparametric measure of association between any number of random vectors that is based on the empirical copula process. The measure is insensitive to the dependence of components within vectors and only captures association between vectors as a whole. We calculate approximate...

The paper develops a tail risk forecasting model that incorporates the wealth of economic and financial information available to risk managers. The approach can be viewed as a regularized extension of the two-stage GARCH-EVT model of McNeil and Frey (2000) where we permit a time-varying...