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Construction Elements Of Bankruptcy Prediction Models In Multi–Dimensional Early Warning Systems

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  • Jaros³aw Kaczmarek

    ()
    (Cracow University of Economics, Poland)

Abstract

A consequence of the inevitability of the occurrence of internal crises in companies is the taking of preventive action in place of purely remedial measures. In this respect a significant role is played by Early Warning Systems (EWS), which provide early warning information and financial threat assessments relating to the continuation of operations and bankruptcy not only for individual companies as such but also for companies as a whole. The limitations of existing models used for EWS purposes have led to the elaboration of new models, estimated on one of the largest hitherto drawn up teaching sets, constituting more than five hundred bankrupt companies. These models also distinguish themselves through the application of innovative methods and precise instruments; the structural concept of these models for multi–dimensional EWS purposes, accompanied by elements used for predicting, is presented in this article.

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Bibliographic Info

Article provided by Czestochowa Technical University, Department of Management in its journal Polish Journal of Management Studies.

Volume (Year): 5 (2012)
Issue (Month): 1 ( June)
Pages: 136-149

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Handle: RePEc:pcz:journl:v:5:y:2012:i:1:p:136-149

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Related research

Keywords: bankruptcy; bankruptcy prediction; early warning system; logistic regression model;

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  1. Rousseeuw, Peter J. & Christmann, Andreas, 2003. "Robustness against separation and outliers in logistic regression," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 43(3), pages 315-332, July.
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