A limit distribution of credit portfolio losses with low default probabilities

Xiaojun Shi, Qihe Tang, Zhongyi Yuan

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


This paper employs a multivariate extreme value theory (EVT) approach to study the limit distribution of the loss of a general credit portfolio with low default probabilities. A latent variable model is employed to quantify the credit portfolio loss, where both heavy tails and tail dependence of the latent variables are realized via a multivariate regular variation (MRV) structure. An approximation formula to implement our main result numerically is obtained. Intensive simulation experiments are conducted, showing that this approximation formula is accurate for relatively small default probabilities, and that our approach is superior to a copula-based approach in reducing model risk.

Original languageEnglish (US)
Pages (from-to)156-167
Number of pages12
JournalInsurance: Mathematics and Economics
StatePublished - Mar 1 2017

All Science Journal Classification (ASJC) codes

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


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