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Bankruptcy Prediction: The Case of the Greek Market

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  • Angeliki Papana

    (Department of Economics, University of Macedonia, 54636 Thessaloniki, Greece)

  • Anastasia Spyridou

    (Faculty of Management and Economics, Technological University of Gdansk, 80-233 Gdansk, Poland)

Abstract

Financial bankruptcy prediction is an essential issue in emerging economies taking into consideration the economic upheaval that can be caused by business failures. The research on bankruptcy prediction is of the utmost importance as it aims to build statistical models that can distinguish healthy firms from financially distressed ones. This paper explores the applicability of the four most used approaches to predict financial bankruptcy using data concerning the case of Greece. A comparison of linear discriminant analysis, logit, decision trees and neural networks is performed. The results show that discriminant analysis is slightly superior to the other methods.

Suggested Citation

  • Angeliki Papana & Anastasia Spyridou, 2020. "Bankruptcy Prediction: The Case of the Greek Market," Forecasting, MDPI, vol. 2(4), pages 1-21, December.
    • Handle: RePEc:gam:jforec:v:2:y:2020:i:4:p:27-525:d:455699
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    References listed on IDEAS

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    2. Rice, John & Raziq, Muhammad Mustafa & Martin, Nigel & Fieger, Peter & Rice, Bridget, 2023. "The debt crisis and the adoption of Asset-Light and Fee-Orientated (ALFO) arrangements at Marriott: 1980-1995," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 9(1), pages 58-66.
    3. Beata Gavurova & Sylvia Jencova & Radovan Bacik & Marta Miskufova & Stanislav Letkovsky, 2022. "Artificial intelligence in predicting the bankruptcy of non-financial corporations," Oeconomia Copernicana, Institute of Economic Research, vol. 13(4), pages 1215-1251, December.
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