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

Qihe Tang, Zhongyi Yuan

Research output: Contribution to journalArticle

13 Citations (Scopus)

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

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Multivariate Regular Variation
Asymptotic Analysis
Archimedean Copula
Tail Behavior
Heavy Tails
Value at Risk
Multivariate Models
Asymptotic Estimates
Structural Model
Tail
Regular variation
Loss given default
Asymptotic analysis
Modeling
Estimate

All Science Journal Classification (ASJC) codes

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

Cite this

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Asymptotic Analysis of the Loss Given Default in the Presence of Multivariate Regular Variation. / Tang, Qihe; Yuan, Zhongyi.

In: North American Actuarial Journal, Vol. 17, No. 3, 01.07.2013, p. 253-271.

Research output: Contribution to journalArticle

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