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An Urn-Based Nonparametric Modeling of the Dependence between PD and LGD with an Application to Mortgages

by Dan Cheng and Pasquale Cirillo *,†,‡
Applied Probability Group, Delft Institute of Applied Mathematics (DIAM), Delft University of Technology, 2628 XE Delft, The Netherlands
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Current address: E1.260 Building 28, Van Mourik Broekmanweg 6, 2628 XE Delft, The Netherlands.
Risks 2019, 7(3), 76; https://doi.org/10.3390/risks7030076
Received: 30 March 2019 / Revised: 25 June 2019 / Accepted: 1 July 2019 / Published: 7 July 2019
(This article belongs to the Special Issue Advances in Credit Risk Modeling and Management)
We propose an alternative approach to the modeling of the positive dependence between the probability of default and the loss given default in a portfolio of exposures, using a bivariate urn process. The model combines the power of Bayesian nonparametrics and statistical learning, allowing for the elicitation and the exploitation of experts’ judgements, and for the constant update of this information over time, every time new data are available. A real-world application on mortgages is described using the Single Family Loan-Level Dataset by Freddie Mac. View Full-Text
Keywords: probability of default; loss given default; wrong-way risk; dependence; urn model probability of default; loss given default; wrong-way risk; dependence; urn model
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Cheng, D.; Cirillo, P. An Urn-Based Nonparametric Modeling of the Dependence between PD and LGD with an Application to Mortgages. Risks 2019, 7, 76.

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