Default Probability Estimation in Small Samples: With an application to sovereign bonds

by Walter Orth of University of Cologne

February 9, 2012

Abstract: In small samples and especially in the case of small true default probabilities, standard approaches to credit default probability estimation have certain drawbacks. Most importantly, standard estimators tend to underestimate the true default probability which is clearly an undesirable property from the perspective of prudent risk management. As an alternative, we present an empirical Bayes approach to default probability estimation and apply the estimator - which is capable of multi-period predictions - to a comprehensive sample of Standard & Poor's rated sovereign bonds. By means of a simulation study, we then show that the empirical Bayes estimator is more conservative and more precise under realistic data generating processes.

JEL Classification: C11, C41, G15,G28.

Keywords: Low-default portfolios, empirical Bayes, sovereign default risk, simulation study.

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