This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...

Ziel des vorliegenden Diskussionspapiers ist es, einen Beitrag zur Verbesserung der Vergleichbarkeit der Schätzgüteergebnisse von Insolvenzprognosestudien zu leisten. Hierzu werden zunächst in der Literatur verwendete kategoriale, ordinale und kardinale Schätzgütemaße vorgestellt. Es wird...

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 era of Basel II a powerful tool for bankruptcy prognosis is vital for banks. The tool must be precise but also easily adaptable to the bank's objections regarding the relation of false acceptances (Type I error) and false rejections (Type II error). We explore the suitability of Smooth...

Russian banks have been strongly influenced by the worldwide financial crisis which started in the second half of 2008. This was caused by a combination of domestic, regional and international factors. We estimate an early warning model for the Russian crisis. We identified 47 Russian banks...

Traditional methods for evaluating corporate credit risk rarely consider the impact of the macro economy on corporate value and performance. We argue that lenders and management can obtain valuable information about the need for and approach to restructuring by decomposing default predictions...

We use a vector error correction model to study the long-term relationship between aggregate expected default frequency and the macroeconomic development, i.e. CPI, industry production and short-term interest rate. The model is used to forecast the median expected default frequency of the...

We demonstrate improvements in predictive power when introducing spline functions to take account of highly non-linear relationships between firm failure and earnings, leverage, and liquidity in a logistic bankruptcy model. Our results show that modeling excessive non-linearities yields...

We address a number of comparative issues relating to the performance of failure prediction models for small, private firms. We use two models provided by vendors, a model developed by the National Bank of Belgium, and the Altman Z-score model to investigate model power, the extent of...

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...