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

Journal article (2019)

Authors

D. Cheng Applied Probability - EEMCS
P. Cirillo Applied Probability - EEMCS
Research Group
Applied Probability (EEMCS) (TU Delft)
Copyright: © 2019 D. Cheng, P. Cirillo
DOI: https://doi.org/10.3390/risks7030076
Wrong-way risk Dependence Loss given default Probability of default Urn model
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Published Date

2019-7

Language

English

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Delft Institute of Applied Mathematics

Research Group

Applied Probability

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.