PT - JOURNAL ARTICLE AU - Mark Johnson AU - Karyl Leggio AU - Yoon S. Shin TI - Assessment of Credit Risk Models on Rule 144A Corporate Bonds AID - 10.3905/jfi.2018.1.064 DP - 2018 Aug 22 TA - The Journal of Fixed Income PG - jfi.2018.1.064 4099 - https://pm-research.com/content/early/2018/08/22/jfi.2018.1.064.short 4100 - https://pm-research.com/content/early/2018/08/22/jfi.2018.1.064.full AB - Accurate assessment of credit risk can improve the performance of bond portfolio managers. Using credit ratings and market-based credit risk models from S&P and Bloomberg, we investigate the performance of four credit risk models in the Rule 144A corporate bond markets in the United States over the 1990–2015 period. We divide our sample into straight bonds and convertible bonds and find that (1) when it comes to straight bonds, discrete models such as S&P’s credit ratings and Bloomberg ratings determine yields more accurately than the continuous market-based models of S&P and Bloomberg; (2) with regard to convertible bonds, a convertible option has a stronger effect than credit ratings in determining yields, and only Bloomberg default risk ratings, not S&P credit ratings, determine the yields; (3) for convertible bonds, the continuous market-based models of S&P and Bloomberg affect yields more significantly than discrete models; and (4) when it comes to predicting actual defaults, Bloomberg models are superior to S&P’s models, and the Bloomberg discrete model has more power than its continuous counterpart.