Synthetic Credit Ratings and the Inefficiency of Agency Ratings

Abstract

This study develops and evaluates a model that generates synthetic credit ratings using accounting and market-based information. The model performs well in explaining agency ratings, suggesting that fitted values for unrated companies are likely to be reasonably precise. Moreover, the synthetic ratings explain cross sectional differences in credit default swap (CDS) spreads, even after controlling for contemporaneous agency ratings. Compared with synthetic ratings, agency ratings explain a greater proportion of the variation in CDS spreads, but their differential informativeness is relatively small and has declined substantially over the past decade. This decline is possibly due to post-crisis Securities and Exchange Commission regulation that limits rating agencies’ ability to obtain confidential information from rated companies. Consistent with the finding that agency ratings do not fully impound the information in synthetic ratings, the difference between synthetic and agency ratings predicts changes in agency ratings in subsequent months, especially for small companies. There is no evidence of substantial improvement over the past 4 decades in the timeliness of agency ratings with respect to the information in synthetic ratings. Investors in large companies appear to process the synthetic rating information in a timely fashion, as the difference between synthetic and agency ratings does not predict changes in CDS spreads or in the stock prices of these companies. For small companies, however, there is some predictability.