A reinforced urn process modeling of recovery rates and recovery times

Journal article (2018)

Authors

D. Cheng Applied Probability - EEMCS
P. Cirillo Applied Probability - EEMCS
Research Group
Applied Probability (EEMCS) (TU Delft)
Recovery rate Recovery risk LGD Recovery time Beta-Stacy Process Urn Models RUP
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Published Date

20-08-2018

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Delft Institute of Applied Mathematics

Research Group

Applied Probability

Abstract

Answering a major demand in modern credit risk management, we propose a nonparametric survival approach for the modeling of the recovery rate and the recovery time of a defaulted counterparty, by introducing what we call the Recovery Reinforced Urn Process, a special type of combinatorial stochastic process.
The new model allows for the elicitation and exploitation of prior knowledge and experts’ judgements, and for the constant update of this information over time, as soon as new data become available. We show how to use it to perform Bayesian nonparametric prediction about the recovered amounts and the (total) recovery time of a series of defaulted exposures.
An application to real data is provided using the Single Family Loan-Level Dataset by Freddie Mac.