The credit business is an essential part of each banks' activities. With regard to the increasing regulatory obligations, the risk management and the associated minimum capital requirements gain in importance. Banks have got the possibility to determine their credit risk by an internal rating...

In this paper, we examine the German business cycle (from 1955 to 1994) in order to identify univariate and multivariate outliers as well as influence points corresponding to Linear Discriminant Analysis. The locations of the corresponding observations are compared and economically interpreted.

Most studies about the shadow economy focus on the estimation of the aggregate size. However, this study aims to address the sectoral or micro aspects of this phenomenon using the data from the textile sector in Turkey. It uses discriminant analysis and ordered and logistic regression models to...

Wie schon vor einem Jahr wurde die aktuelle Konjunkturprognose (Anfang 1999) in das RWI Klassifikationsschema eingeordnet. Danach liegt die wirtschaftliche Entwicklung des Zeitraums 1998-3 bis 2000-4 im Grenzbereich zwischen Aufschwung und oberem Wendepunkt. Vor einem Jahr war die damalige...

This paper illustrates the Support Vector Method for the classification problem with two and more classes. In particular, the multi-class classification Support Vector Method of Weston and Watkins (1998) is correctly formulated as a quadratic optimization problem. Then, the method is applied to...

When comparing methods for classification, often the rating relies on their prediction accuracy alone. One reason for this is that this is the aspect that can be most easily measured. Yet, often one wants to learn more about the problem than only how to predict. The interpretation of the...

This paper develops a specification of the credit scoring model with high discriminatory power to analyze data on loans at the retail banking market. Parametric and non- parametric approaches are employed to produce three models using logistic regression (parametric) and one model using...