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An Evaluation of Effectiveness of Fuzzy Logic Model in Predicting the Business Bankruptcy

  • Korol, Tomasz

    ()

    (Gdansk University of Technology, Poland, Faculty of Management and Economics)

  • Korodi, Adrian

    ()

    (“Politehnica” University of Timisoara, Romania, Faculty of Automation and Computers, Deparment of Automation and Applied Informatics)

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    In front of the current global financial crisis, the future existence of the firms is uncertain. The characteristics and the dynamics of the current world and the interdependences between the financial and economic markets around it demand a continuous research for new methods of bankruptcy prediction. The purpose of this article is to present a fuzzy logic-based system that predicts bankruptcy for one, two and three years before the possible failure of companies. The proposed fuzzy model uses as inputs financial ratios, that is dynamics of the financial ratios. In order to design and to implement the model, authors have used financial statements of 132 stock equity companies (25 bankrupt and 107 nonbankrupt). The paper presents also the testing and validation of the created fuzzy logic models.

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    File URL: http://www.ipe.ro/rjef/rjef3_11/rjef3_2011p92-107.pdf
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    Article provided by Institute for Economic Forecasting in its journal Romanian Journal for Economic Forecasting.

    Volume (Year): (2011)
    Issue (Month): 3 (September)
    Pages: 92-107

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    Handle: RePEc:rjr:romjef:v::y:2011:i:3:p:92-107
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    1. Ooghe, H. & De Prijcker, S., 2006. "Failure processes and causes of company bankruptcy: a typology," Vlerick Leuven Gent Management School Working Paper Series 2006-21, Vlerick Leuven Gent Management School.
    2. Nastac, Iulian & Dobrescu, Emilian & Pelinescu, Elena, 2007. "Neuro-Adaptive Model for Financial Forecasting," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 4(3), pages 19-41, September.
    3. Daianu, Daniel & Lungu, Laurian, 2008. "Why Is This Financial Crisis Occurring? How To Respond To It?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(4), pages 59-87, December.
    4. S. Balcaen & H. Ooghe, 2004. "35 years of studies on business failure: an overview of the classical statistical methodologiesand their related problems," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/248, Ghent University, Faculty of Economics and Business Administration.
    5. Morariu, Nicolae & Iancu, Eugenia & Vlad, Sorin, 2009. "A Neural Network Model for Time-Series Forecasting," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 213-223, December.
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