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http://dx.doi.org/10.29220/CSAM.2020.27.5.579

A dynamic Bayesian approach for probability of default and stress test  

Kim, Taeyoung (Korea Enterprise Data Co. Ltd.)
Park, Yousung (Department of Statistics, Korea University)
Publication Information
Communications for Statistical Applications and Methods / v.27, no.5, 2020 , pp. 579-588 More about this Journal
Abstract
Obligor defaults are cross-sectionally correlated as obligors share common economic conditions; in addition obligors are longitudinally correlated so that an economic shock like the IMF crisis in 1998 lasts for a period of time. A longitudinal correlation should be used to construct statistical scenarios of stress test with which we replace a type of artificial scenario that the banks have used. We propose a Bayesian model to accommodate such correlation structures. Using 402 obligors to a domestic bank in Korea, our model with a dynamic correlation is compared to a Bayesian model with a stationary longitudinal correlation and the classical logistic regression model. Our model generates statistical financial statement under a stress situation on individual obligor basis so that the genearted financial statement produces a similar distribution of credit grades to when the IMF crisis occurred and complies with Basel IV (Basel Committee on Banking Supervision, 2017) requirement that the credit grades under a stress situation are not sensitive to the business cycle.
Keywords
Bayesian model; dynamic longitudinal correlation; probability of default; stress test;
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