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 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...

The ultimate aim of this paper is to generate micro-level risk measures, which can provide a useful input for further research. To this end, this paper estimates bankruptcy probabilities for Hungarian firms using probit estimation. The estimated models show reasonable performance in...

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...

We examine how equity-market frictions that restrict pessimistic trading, such as short-sale constraints, affect assessments of default risk. We find that these frictions decrease the usefulness of equity-market variables for identifying defaulting firms but increase their usefulness for...

In this paper we use a reduced form model for the analysis of Portfolio Credit Risk. For this purpose, we fit a Dynamic Factor model, DF, to a large dataset of default rates proxies and macrovariables for Italy. Multi step ahead density and probability forecasts are obtained by employing both...

In this paper we use a reduced form model for the analysis of Portfolio Credit Risk. For this purpose, we fit a Dynamic Factor model, DF, to a large dataset of default rates proxies and macrovariables for Italy. Multi step ahead density and probability forecasts are obtained by employing both...

In this paper, we evaluate an alternative approach for bankruptcy prediction that measures the financial healthiness of firms that have coupon-paying debts. The approach is based on the framework of Leland and Toft (1996), which is an extension of a widely-used model; the Black-Scholes-Merton...