On the asymptotics of tail conditional expectation for portfolio loss under bivariate Eyraud-Farlie-Gumbel-Morgenstern copula and heavy tails

Guo dong Xing, Xiaohu Li, Shanchao Yang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In the setting of bivariate Eyraud-Farlie-Gumbel-Morgenstern copula and heavy tails characterized by the power law of tail decay, we present the asymptotics of tail conditional expectation for portfolio loss as the confidence level tends to one. In order to illustrate the obtained result, a numerical example and its relevant simulation are carried out.

Original languageEnglish
Pages (from-to)2049-2058
Number of pages10
JournalCommunications in Statistics: Simulation and Computation
Volume49
Issue number8
DOIs
StatePublished - 2 Aug 2020

Keywords

  • Asymptotics
  • Bivariate Eyraud-Farlie-Gumbel-Morgenstern copula
  • Portfolio loss
  • Power-law
  • Tail conditional expectation

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