Bankruptcy Prediction: The Case of the Greek Market

Angeliki Papana and Anastasia Spyridou
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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

Forecasting, 2020, vol. 2, issue 4, 1-21

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.

Keywords: bankruptcy; prediction; discriminant analysis; logit; decision trees; neural networks; Greek market (search for similar items in EconPapers)
JEL-codes: A1 B4 C0 C1 C2 C3 C4 C5 C8 M0 Q2 Q3 Q4 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jforec:v:2:y:2020:i:4:p:27-525:d:455699

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