Systemic Tail Risk Distribution

Abstract

We introduce the systemic tail risk distribution of a financial market to characterize the asset return linkages during financial crisis. This distribution provides the probabilities that several assets of a market lose a large part of their nominal value given that the price of at least one of them collapses. It introduces a new way of assessing the stability of a financial market during potential systemic risk events. We propose a new type of multivariate extreme value distribution for high-dimensional vectors to model the extremal dependence between asset prices, and we use efficient likelihood inference methods to estimate the parameters of the systemic tail risk distribution. Our real data show that the empirical static systemic tail risk distribution is U-shaped, while the empirical conditional distribution is L-shaped.