Rating agencies claim to look through the cycle when assigning corporate credit ratings, which entails that they are able to separate trend components of default risk from transitory ones. To test whether agencies possess this competence, I take market-based estimates of 1-year default probabilities of corporate bond issuers and estimate their long-run trend using the Hodrick-Prescott filter, local regression, or centered moving averages. I find that ratings help identify the current split into trend and cycle. In addition, rating stability is similar to the one of hypothetical ratings based on long-term trends. The results are robust to the use of different filter techniques. They are confirmed by a model-free analysis, which shows that ratings predict future changes in market-based default probability estimates. Since the examined trends are forward-looking in the sense that the trend filtering algorithms use future data, agency ratings exhibit important characteristics one would expect from ratings that see through the cycle.
Review of Quantitative Finance and Accounting – Springer Journals
Published: Apr 8, 2012
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