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Neural Networks in Bankruptcy Prediction - A Comparative Study on the Basis of the First Hungarian Bankruptcy Model

Virág, Miklós and Kristóf, Tamás (2005) Neural Networks in Bankruptcy Prediction - A Comparative Study on the Basis of the First Hungarian Bankruptcy Model. Acta Oeconomica, 55 (4). pp. 403-425.

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Official URL: http://www.akademiai.com/content/p8h5h42647353582/


Abstract

The article attempts to answer the question whether or not the latest bankruptcy prediction techniques are more reliable than traditional mathematical–statistical ones in Hungary. Simulation experiments carried out on the database of the first Hungarian bankruptcy prediction model clearly prove that bankruptcy models built using artificial neural networks have higher classification accuracy than models created in the 1990s based on discriminant analysis and logistic regression analysis. The article presents the main results, analyses the reasons for the differences and presents constructive proposals concerning the further development of Hungarian bankruptcy prediction.

Item Type:Article
Series Number / Identification Number:10.1556/AOecon.55.2005.4.2
Uncontrolled Keywords:solvency, bankruptcy modelling, bankruptcy prediction, discriminant analysis, logistic regression, neural networks
Subjects:Mathematics, Econometrics
Finance
ID Code:147
Deposited By: dr Miklós Virág
Deposited On:10 Nov 2010 16:35
Last Modified:03 Jul 2012 00:23

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