Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: http://hdl.handle.net/10419/27334
Autoren: 
Auria, Laura
Moro, Rouslan A.
Datum: 
2008
Reihe/Nr.: 
DIW Discussion Papers 811
Zusammenfassung: 
This paper introduces a statistical technique, Support Vector Machines (SVM), which is considered by the Deutsche Bundesbank as an alternative for company rating. A special attention is paid to the features of the SVM which provide a higher accuracy of company classification into solvent and insolvent. The advantages and disadvantages of the method are discussed. The comparison of the SVM with more traditional approaches such as logistic regression (Logit) and discriminant analysis (DA) is made on the Deutsche Bundesbank data of annual income statements and balance sheets of German companies. The out-of-sample accuracy tests confirm that the SVM outperforms both DA and Logit on bootstrapped samples.
Schlagwörter: 
Company rating
bankruptcy analysis
support vector machines
JEL: 
C13
G33
C45
Dokumentart: 
Working Paper
Nennungen in sozialen Medien:

Datei(en):
Datei
Größe
488.07 kB





Publikationen in EconStor sind urheberrechtlich geschützt.