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The scope of this study is to investigate the capability of AI methods to accurately detect and predict credit risks based on retail borrowers' features. The comparison of logistic regression, decision tree, and random forest showed that machine learning methods are able to predict credit...
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find that there is a significant difference across the industries. The financial sector has the highest misreporting …
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This paper analyzes the influence of downside risk on defaultable bond returns. By introducing a defaultable bond … bond excess returns using a portfolio-level analysis and Fama-MacBeth regressions. We find that downside risk is a strong … and robust predictor for future bond returns. In addition, due to the higher proportion of abnormal transactions in the …
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realized defaults. Furthermore, it predicts future equity and corporate bond returns, even after controlling for many existing …
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correlation, and dependence on various explanatory variables. At the same time, it allows computing analytically the unexpected … credit loss. We propose and empirically implement estimation of the model based on aggregate and exposure level Moody …'s default and recovery data. The results confirm existence of significantly positive default and recovery rate correlation. We …
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