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This paper investigates the information in corporate credit ratings. If ratings are to be informative indicators of credit risk, they must reflect what a risk-averse investor cares about: both raw default probability and systematic risk. We find that ratings are relatively inaccurate measures of raw default probability—they are dominated as predictors of failure by a simple model based on publicly available financial information. However, ratings do contain relevant information since they are related to a measure of exposure to common (and undiversifiable) variation in default probability (“failure beta”). Systematic risk is shown to be related to joint default probabilities in the context of the Merton [Merton RC (1974) On the pricing of corporate debt: The risk structure of interest rates. J. Finance 29(2):449–470] model. Empirically, it is related to credit default swap spreads and risk premia. Given the multidimensional nature of credit risk, it is not possible for one measure to capture all the relevant information. This paper was accepted by Gustavo Manso, finance.
Credit Rating, Credit Risk, Default Probability, Forecast Accuracy, Systematic Default Risk, jel: jel:G12, jel: jel:G24, jel: jel:G33
Credit Rating, Credit Risk, Default Probability, Forecast Accuracy, Systematic Default Risk, jel: jel:G12, jel: jel:G24, jel: jel:G33
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 159 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |