In many economic applications it is desirable to make future predictions about the financial status of a company. The focus of predictions is mainly if a company will default or not. A support vector machine (SVM) is one learning method which uses historical data to establish a classification...

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...

This article presents a financial scoring model estimated on Czech corporate accounting data. Seven financial indicators capable of explaining business failure at a 1-year prediction horizon are identified. Using the model estimated in this way, an aggregate indicator of the creditworthiness of...

In the recent theoretical literature on lending risk, the coordination problem in multi-creditor relationships have been analyzed extensively. We address this topic empirically, relying on a unique panel data set that includes detailed credit-file information on distressed lending relationships...

We examine chief executive officer (CEO) career and compensation changes for large firms filing for Chapter 11. One-third of the incumbent CEOs maintain executive employment, and these CEOs experience a median compensation change of zero. However, incumbent CEOs leaving the executive labor...

Banks entering an emerging market face a lot of uncertainty about the risks involved in lending. We use a unique unbalanced panel of nearly 700 short-term loans made to SMEs in Slovakia between January 2000 and June 2005. Of the loans granted, on average 6.0 per cent of the firms defaulted....

This paper employs the methodology of Wilson (1997) on Hungarian data to conduct a macro stress test in relation to banks’ corporate loan portfolio. First, sector specific models of bankruptcy are estimated, where the bankruptcy frequency is linked to the general health of the economy. Data on...

The determinants of transitions between different states of financial distress are analyzed using two versions of Markov chain models: a multinomial logit model without random effects and a multinomial logit model capturing such unobservable factors. The empirical analysis is based on a panel...

The moral hazard incentives of the bank safety net predict that distressed banks take on more risk and higher leverage. Since many factors reduce these incentives, including charter value, regulation, and managerial incentives, the net economic effect of these incentives is an empirical...

The determinants of transitions between different states of financial distress are analyzed using two versions of Markov chain models: a multinomial logit model without random effects and a multinomial logit model capturing such unobservable factors. The empirical analysis is based on a panel...