Asymptotic Analysis of the Loss Given Default in the Presence of Multivariate Regular Variation

Qihe Tang, Zhongyi Yuan

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

Consider a portfolio of n obligors subject to possible default. We propose a new structural model for the loss given default, which takes into account the severity of default. Then we study the tail behavior of the loss given default under the assumption that the losses of the n obligors jointly follow a multivariate regular variation structure. This structure provides an ideal framework for modeling both heavy tails and asymptotic dependence. Multivariate models involving Archimedean copulas and mixtures are revisited. As applications, we derive asymptotic estimates for the value at risk and conditional tail expectation of the loss given default and compare them with the traditional empirical estimates.

Original languageEnglish (US)
Pages (from-to)253-271
Number of pages19
JournalNorth American Actuarial Journal
Volume17
Issue number3
DOIs
StatePublished - Jul 1 2013

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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