Confidence intervals for corporate default rates

Rating agency default studies provide estimates of mean default rates over multiple time horizons but have never included estimates of the standard errors of the estimates. This is due at least in part to the challenge of accounting for the high degree of correlation induced by their cohort-based methodologies. In this article, Richard Cantor, David Hamilton and Jennifer Tennant present a method for estimating confidence intervals for corporate default rates derived through a bootstrapping approach

Historical average cumulative default rates by rating category and investment horizon are among rating agencies' most widely referenced statistics. In any finite sample, however, the historical mean default rate may overstate or understate the underlying population's true risk of default, depending upon whether the particular set of issuers included in the sample happen to experience lower or higher than expected default incidence. Quantitative credit analysts and risk managers are, therefore