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CDO Squared Pricing Using Gaussian Mixture Model with Transformation of Loss Distribution

David X. Li

AIG Asset Management

Michael Hong Liang

Barclays Capital

September 5, 2005

We present a new approach to price CDO Squared-type transactions consistently with the pricing of the underlying CDOs. We first present an extension to the current market standard model using a Gaussian mixture (GM) copula model instead of one parameter single Gaussian Copula model. It shows that GM broadly captures the correlation skew shown in the index tranche market, but not exactly and across time or across term structure. Then using an analogy to the option pricing for CDO tranche pricing we extract an implied loss distribution from the observed index tranche market or a set of bespoke pricing of the underlying baby portfolios. To strike a balance of matching the underlying baby CDO pricing and having a plausible economic correlation model to price CDO squared-type trades we create a loss distribution transformation for each baby CDO portfolio between the implied loss distribution from the index tranche market or bespoke pricing and the loss distribution from the GM model. This way, we can match the pricing for all baby portfolios or tranches, and at the same time, we price bespoke CDO and CDO squared with a broadly skew aware correlation model. In the future we could further calibrate the parameters in the GM model to the CDO squared market if its pricing becomes more observable.

Number of Pages in PDF File: 27

Keywords: CDO Squared, Gaussian Mixture Copula, Implied Loss Distribution, Loss Distribution Transformation

JEL Classification: G13, C1

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Date posted: March 23, 2006  

Suggested Citation

Li, David X. and Liang, Michael Hong, CDO Squared Pricing Using Gaussian Mixture Model with Transformation of Loss Distribution (September 5, 2005). Available at SSRN: https://ssrn.com/abstract=890766 or http://dx.doi.org/10.2139/ssrn.890766

Contact Information

David Xianglin Li (Contact Author)
AIG Asset Management ( email )
80 Pine Street
New York, NY 10005
United States
+12127705384 (Phone)
Michael Hong Liang
Barclays Capital ( email )
London EC3P 3AH
United Kingdom
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