This paper aims to analyze the derivatives disclosure in banks' annual risk reports. In this paper, the author uses …, with particular reference to credit derivatives. The empirical research is conducted on a sample of large European banks …

We use machine learning methods to create a comprehensive measure of credit risk based on qualitative information … future credit rating downgrades) relative to existing credit risk measures developed by prior research (e.g., z-score). We … little evidence that the existing measures of credit risk developed by prior research explain within-firm variation in credit …

This paper models how to calculate credit spreads on high-yield bond issues if the corporation has no underlying traded … traded — are not necessary to develop a model which maintains an acceptable explanatory power around 70% (R2 ) of the credit …

default risk of a loan portfolio. A number of papers document that recent machine learning models outperform traditional …, while providing accurate risk measures. …