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New bankruptcy prediction models for Polish companies

Author

Listed:
  • Marek Gruszczynski

    (Department of Applied Econometrics, Warsaw School of Economics)

  • Piotr Ciesielski

    (Warsaw School of Economics)

  • Mariusz Domeracki

    (Warsaw School of Economics)

Abstract

New logit models for predicting bankruptcy of Polish companies are presented. Major features of these approaches are: (1) selection of appropriate companies to the sample as the key step of the research, (2) well defined samples, (3) the reasoning based on the unified financial state-ments and (4) acceptable results of prediction – within samples as well as for the hold-out sam-ples. In addition, the presented models of Stepien and Strak [2004], Ciesielski [2004] and Dom-eracki [2004] have been validated for the best companies on the Warsaw Stock Exchange. The validation principle states that the estimate of the probability of bankruptcy for such company shall be less than 0.5. New models for predicting bankruptcy of Polish companies well fit into the current research in the field of financial applications of microeconometrics.

Suggested Citation

  • Marek Gruszczynski & Piotr Ciesielski & Mariusz Domeracki, 2005. "New bankruptcy prediction models for Polish companies," Working Papers 21, Department of Applied Econometrics, Warsaw School of Economics.
    • Handle: RePEc:wse:wpaper:21
    as

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    File URL: http://kolegia.sgh.waw.pl/pl/KAE/struktura/IE/struktura/ZES/Documents/Working_Papers/aewp04-05.pdf
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    Citations

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    Cited by:

    1. Prusak Błażej, 2019. "Corporate Bankruptcy Prediction in Poland Against the Background of Foreign Experience," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 15(1), pages 10-19, March.

    More about this item

    Keywords

    bankruptcy; financial distress; financial indicators; binomial logit;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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