This paper investigates the determinants of nonperforming loans (NPL), with a special focus on house price fluctuations. Using a panel of U.S. banks, the analysis is carried out across different loan categories and different types of banks. It is found that house price fluctuations significantly affect the dynamics of NPL, while the magnitude of the impact varies across loan categories and bank types.

This study analyses credit default risk for firms in the Asian and Pacific region by applying two methodologies: a Support Vector Machine (SVM) and a logistic regression (Logit). Among different financial ratios suggested as predictors of default, leverage ratios and the company size display a higher discriminating power compared to others. An analysis of the dependencies between PD and financial ratios is provided along with a comparison with Europe (Germany). With respect to forecasting accuracy the SVM has a lower model risk than the Logit on average and displays a more robust performance. This result holds true across different years.

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