Generalized Pareto Copulas: A Key to Multivariate Extremes

Michael Falk; Simone Padoan

Open Conference Systems, 50th Scientific meeting of the Italian Statistical Society

Michael Falk, Simone Padoan

Last modified: 2018-06-04

Abstract

This talk presents generalized Pareto copulas (GPC), which turn out to be a key to multivariate extreme value theory.Any GPC can be represented in an easy analytic way using a particular type of norm on $\mathbb{R}^d$, called $D$-norm. The characteristic property of a GPC is its exceedance stability.GPC might help to end the debate: What is a \emph{multivariate} generalized Pareto distribution?

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