A reinforced urn process modeling of recovery rates and recovery times

Dan Cheng, Pasquale Cirillo

Research output: Contribution to journalArticleScientificpeer-review

12 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)1-17
JournalJournal of Banking & Finance
Publication statusPublished - 20 Aug 2018


  • recovery risk
  • LGD
  • recovery rate
  • recovery time
  • Beta-Stacy Process
  • Urn Models
  • RUP


Dive into the research topics of 'A reinforced urn process modeling of recovery rates and recovery times'. Together they form a unique fingerprint.

Cite this