Continuous versus Categorical Bond Ratings: the Role of Analysts' Forecasts in Bond Pricing

This study examines the role of analysts' forecasts from bond investors' perspective. The main argument is that categorical bond ratings may contain limited differential power to bond investors about default risk. Therefore, bond investors may use all available information including analysts' forecasts to convert categorical ratings to continuous ratings in order to establish yield differentials between higher-quality and lower-quality bonds within single rating categories. Accordingly, I expect analysts' forecasts to provide incremental explanatory power to bond yield premium after controlling the categorical bond ratings. In addition, I expect that continuous bond ratings derived from a conjectural model outperform categorical bond ratings in explaining bond yield premium. Henceforth, this study aims to empirically test these two hypotheses. I extract new bond issuance from Security Database Corporation (SDC) and the final sample comprises a pooled sample of 763 observations. The results show that analysts' forecasts provide significantly incremental explanatory power in explaining bond yield premium, especially when perceived default risk is high and when information asymmetry is high. I further find that the above-documented association does not change significantly after regulation Fair Disclosure (FD) took effect and does not depend on the use of the proceeds from debt financing. Furthermore, I show through an ordered logit model that bond investors presumably use analysts' forecasts together with other information to develop continuous and thus more differential ratings to complement original categorical bond ratings in pricing bonds. The results imply that grouping probability of default into limited categories of bond ratings may add rather than reduce information noise to bond investors.