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The Implementation of Fuzzy Logic in Forecasting Financial Ratios

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  • Tomasz Korol

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  • Tomasz Korol, 2018. "The Implementation of Fuzzy Logic in Forecasting Financial Ratios," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 12(2), June.
    • Handle: RePEc:wyz:journl:id:534
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    1. Carlos Serrano-Cinca, 1997. "Feedforward neural networks in the classification of financial information," The European Journal of Finance, Taylor & Francis Journals, vol. 3(3), pages 183-202.
    2. Everett, Jim & Watson, John, 1998. "Small Business Failure and External Risk Factors," Small Business Economics, Springer, vol. 11(4), pages 371-390, December.
    3. Zhang, Guoqiang & Y. Hu, Michael & Eddy Patuwo, B. & C. Indro, Daniel, 1999. "Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis," European Journal of Operational Research, Elsevier, vol. 116(1), pages 16-32, July.
    4. Nakandala, Dilupa & Samaranayake, Premaratne & Lau, H.C.W., 2013. "A fuzzy-based decision support model for monitoring on-time delivery performance: A textile industry case study," European Journal of Operational Research, Elsevier, vol. 225(3), pages 507-517.
    5. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    6. L. Lin & J. Piesse, 2004. "Identification of corporate distress in UK industrials: a conditional probability analysis approach," Applied Financial Economics, Taylor & Francis Journals, vol. 14(2), pages 73-82.
    7. Emel, Ahmet Burak & Oral, Muhittin & Reisman, Arnold & Yolalan, Reha, 2003. "A credit scoring approach for the commercial banking sector," Socio-Economic Planning Sciences, Elsevier, vol. 37(2), pages 103-123, June.
    8. Hunter, John & Isachenkova, Natalia, 2006. "Aggregate economy risk and company failure: An examination of UK quoted firms in the early 1990s," Journal of Policy Modeling, Elsevier, vol. 28(8), pages 911-919, November.
    9. Hossein Asgharian, 2003. "Are highly leveraged firms more sensitive to an economic downturn?," The European Journal of Finance, Taylor & Francis Journals, vol. 9(3), pages 219-241.
    10. du Jardin, Philippe & Séverin, Eric, 2012. "Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time," European Journal of Operational Research, Elsevier, vol. 221(2), pages 378-396.
    11. Robson, Martin T, 1996. "Macroeconomic Factors in the Birth and Death of U.K. Firms: Evidence from Quarterly VAT Registrations," The Manchester School of Economic & Social Studies, University of Manchester, vol. 64(2), pages 170-188, June.
    12. Riyaz Sikora & Michael Shaw, 1994. "A Double-Layered Learning Approach to Acquiring Rules for Classification: Integrating Genetic Algorithms with Similarity-Based Learning," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 174-187, May.
    13. de Andres, Javier & Landajo, Manuel & Lorca, Pedro, 2005. "Forecasting business profitability by using classification techniques: A comparative analysis based on a Spanish case," European Journal of Operational Research, Elsevier, vol. 167(2), pages 518-542, December.
    14. Thomas E. McKee, 2003. "Rough sets bankruptcy prediction models versus auditor signalling rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(8), pages 569-586.
    15. Chris Charalambous & Andreas Charitou & Froso Kaourou, 2000. "Comparative Analysis of Artificial Neural Network Models: Application in Bankruptcy Prediction," Annals of Operations Research, Springer, vol. 99(1), pages 403-425, December.
    16. Edward I Altman & Tara K N Baidya & Luis Manoel Ribeiro Dias, 1979. "Assessing Potential Financial Problems for Firms in Brazil," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 10(2), pages 9-24, June.
    17. Lacher, R. C. & Coats, Pamela K. & Sharma, Shanker C. & Fant, L. Franklin, 1995. "A neural network for classifying the financial health of a firm," European Journal of Operational Research, Elsevier, vol. 85(1), pages 53-65, August.
    18. P. Du Jardin & E. Séverin, 2012. "Forecasting financial failure using a Kohonen map: a comparative study to improve bankruptcy model over time," Post-Print hal-00801853, HAL.
    19. Selwyn Piramuthu & Harish Ragavan & Michael J. Shaw, 1998. "Using Feature Construction to Improve the Performance of Neural Networks," Management Science, INFORMS, vol. 44(3), pages 416-430, March.
    20. Wu, Desheng Dash & Zhang, Yidong & Wu, Dexiang & Olson, David L., 2010. "Fuzzy multi-objective programming for supplier selection and risk modeling: A possibility approach," European Journal of Operational Research, Elsevier, vol. 200(3), pages 774-787, February.
    21. Arindam Bandyopadhyay, 2006. "Predicting probability of default of Indian corporate bonds: logistic and Z-score model approaches," Journal of Risk Finance, Emerald Group Publishing, vol. 7(3), pages 255-272, May.
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    Cited by:

    1. Sebastian Klaudiusz Tomczak, 2023. "General bankruptcy prediction models for the Visegrád Group. The stability over time," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(4), pages 171-187.
    2. Katarina Valaskova & Dominika Gajdosikova & Jaroslav Belas, 2023. "Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 253-293, March.
    3. Tomasz Korol & Anestis K. Fotiadis, 2022. "Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan," Oeconomia Copernicana, Institute of Economic Research, vol. 13(2), pages 407-438, June.

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