Publication
Title
An analytic approach to credit risk for large corporate bond and loan portfolios
Author
Abstract
We derive an analytic approximation to the credit loss distribution of large portfolios by letting the number of exposures tend to infinity. Defaults and rating migrations for individual exposures are driven by a factor model in order to capture co-movements in changing credit quality. The limiting credit loss distribution obeys the empirical stylized facts of skewness and heavy tails. We show how portfolio features like the degree of systematic risk, credit quality and term to maturity affect the distributional shape of portfolio credit losses. Using empirical data, it appears that the Basle 8% rule corresponds to quantiles with confidence levels exceeding 98%. The limit law's relevance for credit risk management is investigated further by checking its applicability to portfolios with a finite number of exposures. Relatively homogeneous portfolios of 300 exposures can be well approximated by the limit law. A minimum of 800 exposures is required if portfolios are relatively heterogeneous. Realistic loan portfolios often contain thousands of exposures implying that our analytic approach can be a fast and accuratealternative to the standard Monte-Carlo simulation techniques adopted in much of the literature. (C) 2001 Elsevier Science B.V. All rights reserved.
Language
English
Source (journal)
Journal of banking and finance. - Amsterdam
Publication
Amsterdam : 2001
ISSN
0378-4266
DOI
10.1016/S0378-4266(00)00147-3
Volume/pages
25 :9 (2001) , p. 1635-1664
ISI
000170581200002
Full text (Publisher's DOI)
UAntwerpen
Publication type
Subject
External links
Web of Science
Record
Identifier
Creation 07.03.2017
Last edited 26.04.2023
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