Bivariate extreme-value copulas with discrete Pickands dependence measure

Jan Frederik Mai, Matthias Scherer

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

A two-parametric family of bivariate extreme-value copulas (EVCs), which corresponds to precisely the bivariate EVCs whose Pickands dependence measure is discrete with at most two atoms, is introduced and analyzed. It is shown how bivariate EVCs with arbitrary discrete Pickands dependence measure can be represented as the geometric mean of such basis copulas. General bivariate EVCs can thus be represented as the limit of this construction when the number of involved basis copulas tends to infinity. Besides the theoretical value of such a representation, it is shown how several properties of the represented copula can be deduced from properties of the involved basis copulas. An algorithm for the computation of the representation is given.

Original languageEnglish
Pages (from-to)311-324
Number of pages14
JournalExtremes
Volume14
Issue number3
DOIs
StatePublished - Sep 2011

Keywords

  • Dependence function
  • Extreme-value copula
  • Pickands dependence measure

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