Valuing Retail Credit Tranches with Structural, Double Mixture Models

Abstract

This study considers the class of double mixtures to model a general dependence structure beyond the typical conditional independence assumption among the entities in a homogeneous credit portfolio. The two mixing components are (i) the marginal distributions of the systemic and idiosyncratic factors and (ii) the conditional probability measure that incorporates the further dependence structure among the idiosyncratic factors, given the systemic factor. For a large portfolio, the fair spread of a structured retail credit tranche is expressed in terms of the sums of single integrals, which can be easily computed numerically. We discuss the behaviors of tranche spreads under several double mixture models, and calibrate these models to market data. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 35:849–867, 2015

Sum of Bernoulli Mixtures: Beyond Conditional Independence

“…Future directions of research include the application of double mixture models to pricing of credit derivatives such as CDOs, on a completely homogeneous pool (e.g., Bae et al [24]). …”

Model specification and collateralized debt obligation (mis)pricing

“…Broer () find that disagreement about the default correlations increases the value of structured collateral. Erlenmaier and Gersbach (), Bae, Iscoe, and Kim (), and Andreoli, Ballestra, and Pacelli () also explore appropriate ways of estimating the default correlation and CDO pricing.…”