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

Dan Cheng and Pasquale Cirillo
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Dan Cheng: Applied Probability Group, Delft Institute of Applied Mathematics (DIAM), Delft University of Technology, 2628 XE Delft, The Netherlands
Pasquale Cirillo: Applied Probability Group, Delft Institute of Applied Mathematics (DIAM), Delft University of Technology, 2628 XE Delft, The Netherlands

Risks, 2019, vol. 7, issue 3, 1-21

Abstract: 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.

Keywords: probability of default; loss given default; wrong-way risk; dependence; urn model (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:7:y:2019:i:3:p:76-:d:246367

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