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

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • Korol, Tomasz & Korodi, Adrian, 2011. "An Evaluation of Effectiveness of Fuzzy Logic Model in Predicting the Business Bankruptcy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 92-107, September.
    • Handle: RePEc:rjr:romjef:v::y:2011:i:3:p:92-107
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    References listed on IDEAS

    as
    1. 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.
    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. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Bhanu Pratap SINGH & Alok Kumar MISHRA, 2019. "Sensitivity of bankruptcy prediction models to the change in econometric methods," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(620), A), pages 71-86, Autumn.
    2. Tomasz Korol, 2021. "Evaluation of the Macro- and Micro-Economic Factors Affecting the Financial Energy of Households," Energies, MDPI, vol. 14(12), pages 1-14, June.
    3. Umair Bin YOUSAF & Khalil JEBRAN & Man WANG, 2022. "A Comparison of Static, Dynamic and Machine Learning Models in Predicting the Financial Distress of Chinese Firms," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 122-138, April.
    4. Fejér-Király Gergely, 2015. "Bankruptcy Prediction: A Survey on Evolution, Critiques, and Solutions," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 3(1), pages 93-108, December.
    5. Korol Tomasz, 2017. "Evaluation of the factors influencing business bankruptcy risk in Poland," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 13(2), pages 22-35, December.
    6. Gheorghita DINCA & Mirela Camelia BABA & Marius Sorin DINCA & Bardhyl DAUTI & Fitim DEARI, 2017. "Insolvency Risk Prediction Using the Logit and Logistic Models: Some Evidences from Romania," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(4), pages 139-157.
    7. Tomasz Korol & Anestis Fotiadis, 2016. "Applying Fuzzy Logic of Expert Knowledge for Accurate Predictive Algorithms of Customer Traffic Flows in Theme Parks," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1451-1468, November.

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    More about this item

    Keywords

    bankruptcy; crisis; prediction; fuzzy logic; ratings;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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