Efficient estimation of large portfolio loss probabilities in t-copula models

Chan, Joshua C. C. and Kroese, Dirk P. (2010) Efficient estimation of large portfolio loss probabilities in t-copula models. European Journal of Operational Research, 205 2: 361-367. doi:10.1016/j.ejor.2010.01.003

Author Chan, Joshua C. C.
Kroese, Dirk P.
Title Efficient estimation of large portfolio loss probabilities in t-copula models
Journal name European Journal of Operational Research   Check publisher's open access policy
ISSN 0377-2217
Publication date 2010-09-01
Sub-type Article (original research)
DOI 10.1016/j.ejor.2010.01.003
Volume 205
Issue 2
Start page 361
End page 367
Total pages 7
Place of publication Amstelveen, The Netherlands
Publisher Elesevier
Language eng
Formatted abstract
We consider the problem of accurately measuring the credit risk of a portfolio consisting of loans, bonds and other financial assets. One particular performance measure of interest is the probability of large portfolio losses over a fixed time horizon. We revisit the so-called t-copula that generalizes the popular normal copula to allow for extremal dependence among defaults. By utilizing the asymptotic description of how the rare event occurs, we derive two simple simulation algorithms based on conditional Monte Carlo to estimate the probability that the portfolio incurs large losses under the t-copula. We further show that the less efficient estimator exhibits bounded relative error. An extensive simulation study demonstrates that both estimators outperform existing algorithms. We then discuss a generalization of the t-copula model that allows the multivariate defaults to have an asymmetric distribution. Lastly, we show how the estimators proposed for the t-copula can be modified to estimate the portfolio risk under the skew t-copula model.
© 2010 Elsevier B.V. All rights reserved.
Keyword Credit risk
Copula models
Rare-event simulation
Cross-entropy method
Conditional Monte Carlo
Credit risk
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Received 10 June 2009; accepted 4 January 2010. Available online 11 January 2010.

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
Official 2011 Collection
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Citation counts: TR Web of Science Citation Count  Cited 19 times in Thomson Reuters Web of Science Article | Citations
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Created: Sun, 18 Apr 2010, 10:05:32 EST