Abstract
Default dependencies among many different issuers play an important role in the quantification of a portfolio’s credit risk exposure for many reasons. E.g.:
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Specifying an appropriate model for dependent defaults is the core problem in valuing CDOs, multi-name credit derivatives and other financial instruments where portfolios of other defaultable financial instruments are present. Different dependence structures produce different default distributions, which in turn affect the pricing of these instruments. They are actively traded which requires a methodology to measure default and market risks on a day-by-day basis. A consistent model for default correlations is essential to price and hedge these instruments.
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While the actual loss in a portfolio due to the default of a single obligor may be small (unless the risk exposure is very large) the effects of simultaneous defaults of several issuers can be catastrophic. However, little is known about the drivers of default risk at the portfolio level.
“Incorporating default correlation in any portfolio credit risk analysis is difficult because of the lack of good data on default correlation, and the complexity of developing realistic models of default correlations that capture its dependence on credit quality, region, industry and time horizon.”
Krishan Nagpal and Reza Bahar
“We are developing toward the Titanic solution. We only build bigger and bigger ships, but not remembering there are still icebergs.”
Norbert Walter
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© 2004 Springer-Verlag Berlin Heidelberg
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Schmid, B. (2004). Correlated Defaults. In: Credit Risk Pricing Models. Springer Finance. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24716-6_4
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DOI: https://doi.org/10.1007/978-3-540-24716-6_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-07335-9
Online ISBN: 978-3-540-24716-6
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