MPS-RR 2004-21
October 2004

How to model multivariate extremes if one must?

Abstract

In this paper we discuss some approaches to modeling extremely large values in multivariate time series. In particular, we discuss the notion of multivariate regularly varying as key to modeling multivariate heavy-tailed phenomena. The latter notion has found a variety of applications in queuing theory, stochastic networks, telecommunications, insurance, finance and other areas. We contrast this approach with modeling multivariate extremes by using the multivariate student distribution and copulas.

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