Working Paper No. 563
By Arnold Polanski and Evarist Stoja
Tail interdependence is defined as the situation where extreme outcomes for some variables are informative about such outcomes for other variables. We extend the concept of multi-information to quantify tail interdependence at different levels of extremity, decompose it into systemic and residual part and measure the contribution of a constituent to the interdependence of a system. Further, we devise statistical procedures to test: a) tail independence; b) whether an empirical interdependence structure is generated by a theoretical model; and c) symmetry of the interdependence structure in the tails. The application of this approach to multidimensional financial data confirms some known and uncovers new stylized facts on extreme returns.