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Bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline

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  • Paul P. M. Pompe
  • Jan Bilderbeek

Abstract

Using large amounts of data from small and medium‐sized industrial firms, this study examines two aspects of bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline. The results show that especially models generated from the final annual report published prior to bankruptcy were less successful in the timely prediction of failure. Furthermore, it was found that economic decline coincided with the deterioration of a model's performance. With respect to the methods used, we found that neural networks had a somewhat better overall performance than multiple discriminant analysis. Copyright © 2005 John Wiley & Sons, Ltd.

Suggested Citation

  • Paul P. M. Pompe & Jan Bilderbeek, 2005. "Bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 13(2), pages 95-112, June.
    • Handle: RePEc:wly:isacfm:v:13:y:2005:i:2:p:95-112
    DOI: 10.1002/isaf.259
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    References listed on IDEAS

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    Cited by:

    1. du Jardin, Philippe, 2021. "Forecasting corporate failure using ensemble of self-organizing neural networks," European Journal of Operational Research, Elsevier, vol. 288(3), pages 869-885.

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