Convex combinations of quadrant dependent copulas

Martín Egozcue*, Luis Fuentes García, Wing Keung WONG, Ričardas Zitikis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

It is well known that quadrant dependent (QD) random variables are also quadrant dependent in expectation (QDE). Recent literature has offered examples rigorously establishing the fact that there are QDE random variables which are not QD. The examples are based on convex combinations of specially chosen QD copulas: one negatively QD and another positively QD. In this paper we establish general results that determine when convex combinations of arbitrary QD copulas give rise to negatively or positively QD/QDE copulas. In addition to being an interesting mathematical exercise, the established results are helpful when modeling insurance and financial portfolios.

Original languageEnglish
Pages (from-to)249-251
Number of pages3
JournalApplied Mathematics Letters
Volume26
Issue number2
DOIs
Publication statusPublished - Feb 2013

Scopus Subject Areas

  • Applied Mathematics

User-Defined Keywords

  • Convex combination
  • Copula
  • Quadrant dependence
  • Quadrant dependence in expectation

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