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Portfolio Credit Risk with Extremal Dependence: Asymptotic Analysis and Efficient Simulation
Year Of Publication: 2006
Month Of Publication: February
Pages: 40
Download Count: 404
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Comment Num: 0
Language: EN
Who Can Read: Free
Date: 2-27-2007
Publisher: Administrator
We consider the risk of a portfolio comprised of loans, bonds, and financial instrumentsthat are subject to possible default. In particular, we are interested in performance measuressuch as the probability that the portfolio incurs large losses over a fixed time horizon and theexpected excess loss given that large losses are incurred during this horizon. Contrary to thenormal copula that is commonly used in practice (e.g., in the CreditMetrics system), we assumea portfolio dependence structure that is semiparametric, does not hinge solely on correlation,and supports extremal dependence among obligors. A particular instance within the proposedclass of models is the so-called t-copula model that is derived from the multivariate Studentt distribution and hence generalizes the normal copula model. The size of the portfolio, theheterogenous mix of obligors, and the fact that default events are rare and mutually dependentmakes it quite complicated to calculate portfolio credit risk either by means of exact analysisor na¨ıve Monte Carlo simulation. The main contributions of this paper are twofold. We firstderive sharp asymptotics for portfolio credit risk that illustrate the implications of extremaldependence among obligors. Using this as a stepping stone, we develop importance samplingalgorithms that are shown to be asymptotically optimal and can be used to efficiently computeportfolio credit risk via Monte Carlo simulation
Bassamboo, Achal Sign in to follow this author
Juneja, Sandeep Sign in to follow this author
Zeevi, Assaf Sign in to follow this author
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