The Credit Rating Process and Estimation of Transition Probabilities: A Bayesian Approach

Stefanescu, Catalina and Tunaru, Radu and Turnbull, Stuart (2009) The Credit Rating Process and Estimation of Transition Probabilities: A Bayesian Approach. Journal of Empirical Finance, 16 (2). pp. 216-234. ISSN 0927-5398. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1016/j.jempfin.2008.10.006

Abstract

The Basel II Accord requires banks to establish rigorous statistical procedures for the estimation and validation of default and ratings transition probabilities. This raises great technical challenges when sufficient default data are not available, as is the case for low default portfolios. We develop a new model that describes the typical internal credit rating process used by banks. The model captures patterns of obligor heterogeneity and ratings migration dependence through unobserved systematic macroeconomic shocks. We describe a Bayesian hierarchical framework for model calibration from historical rating transition data, and show how the predictive performance of the model can be assessed, even with sparse event data. Finally, we analyze a rating transition data set from Standard and Poor's during 1981–2007. Our results have implications for the current Basel II policy debate on the magnitude of default probabilities assigned to low risk assets.

Item Type: Article
Uncontrolled keywords: Ratings transitions Bayesian inference Latent factors Markov Chain Monte Carlo
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Faculties > Social Sciences > Kent Business School > Accounting and Finance
Faculties > Social Sciences > Kent Business School
Depositing User: Kasia Senyszyn
Date Deposited: 06 Dec 2010 16:40
Last Modified: 10 Jun 2014 10:53
Resource URI: http://kar.kent.ac.uk/id/eprint/26118 (The current URI for this page, for reference purposes)
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