Journal
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
Volume 28, Issue 2, Pages 320-328Publisher
AMER STATISTICAL ASSOC
DOI: 10.1198/jbes.2009.07236
Keywords
Basel II; Bayesian inference; Correlated defaults; Prior assessment; Risk management; Robustness
Funding
- Danish National Research Foundation
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Default is a rare event, even in segments in the midrange of a bank's portfolio. Inference about default rates is essential for risk management and for compliance with the requirements of Basel II. Most commercial loans are in the middle-risk categories and are to unrated companies. Expert information is crucial in inference about defaults. A Bayesian approach is proposed and illustrated using a prior distribution assessed from an industry expert. The binomial model, most common in applications, is extended to allow correlated defaults. A check of robustness is illustrated with an epsilon-mixture of priors.
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