Martina Sponerová –  Masaryk University, Faculty of Economics and Administration, Lipová 41a, 602 00 Brno, Czech Republic

 

DOI: https://doi.org/10.31410/ITEMA.S.P.2021.65

 

5th International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2021, Online/virtual, October 21, 2021, SELECTED PAPERS published by the Association of Economists and Managers of the Balkans, Belgrade; Printed by: SKRIPTA International, Belgrade, ISBN 978-86-80194-50-9, ISSN 2683-5991, DOI: https://doi.org/10.31410/ITEMA.S.P.2021

 

Abstract

A considerable number of publications accompanies the research topic of bankruptcy prediction. This has been motivated by the massive toll on SMEs caused by the global crisis of 2007-2009, the recent COVID-19 crisis and the resulting need to update indicators of SME failure. This paper focuses on the Czech and Slovak economies, specifically at small and medium-sized enterprises (SMEs).

This article aims to find if different factors could predict bankruptcy for Czech and Slovak companies. There were investigated 574 Czech companies and 889 Slovak companies for the period 2010 – 2018. The resulting findings con­firm conclusions of the last year’s literature review. It is most appropriate to construct a financial distress model for a given country or a group of coun­tries with similar characteristics or neighbouring countries. Furthermore, it is advisable to exploit common used financial indicators with a combination of modified indicators to assess the probability of bankruptcy precisely.

 

Keywords

Bankruptcy prediction; Financial distress; SME; Financial indicator; Logistic regression

 

​References

Alaka, H. A., Oyedele, L. O., Owolabi, H. A., Kumar, V., Ajayi, S. O., Akinade, O. O., & Bilal, M. (2018). Systematic review of bankruptcy prediction models: Towards a framework for tool selection. Expert Systems with Applications, 94, 164-184. https://doi.org/10.1016/j.eswa.2017.10.040

Altman, E. I., Esentato, M., & Sabato, G. (2020). Assessing the credit worthiness of Italian SMEs and mini-bond issuers. Global Finance Journal, 43, 100450. https://doi.org/10.1016/j.gf.2018.09.003

Bellovary, J. L., Giacomino, D. E., & Akers, M. D. (2007). A Review of Bankruptcy Prediction Studies: 1930 to Present. Journal of Financial Education, 33, 1–42. http://www.jstor.org/stable/41948574

Fedorova, E. A., Dovzhenko, S. E., & Fedorov, F. Y. (2016). Bankruptcy-prediction models for Russian enterprises: Specific sector-related characteristics. Studies on Russian Economic Development, 27(3), 254-261. https://doi.org/10.1134/S1075700716030060

Gupta, J., Barzotto, M., & Khorasgani, A. (2018). Does size matter in predicting SMEs failure?. International Journal of Finance & Economics, 23(4), 571-605. https://doi.org/10.1002/ijfe.1638

Hafiz, A., Lukumon, O., Muhammad, B., Olugbenga, A., Hakeem, O., & Saheed, A. (2015, March). Bankruptcy prediction of construction businesses: towards a big data analytics approach. In 2015 IEEE First International Conference on Big Data Computing Service and Applications (pp. 347-352). IEEE. https://doi.org/10.1109/BigDataService.2015.30

Karas, M., & Režňáková, M. (2017). The Potential of Dynamic Indicator in Development of the Bankruptcy Prediction Models: the Case of Construction Companies. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 65(2), 641-652. https://doi.org/10.11118/actaun201765020641

Khademolqorani, S., Zeinal Hamadani, A., & Mokhatab Rafiei, F. (2015). A hybrid analysis approach to improve financial distress forecasting: Empirical evidence from Iran. Mathe­matical Problems in Engineering, 2015. https://doi.org/10.1155/2015/178197

Kliestik, T., Valaskova, K., Lazaroiu, G., Kovacova, M., & Vrbka, J. (2020). Remaining Finan­cially Healthy and Competitive: The Role of Financial Predictors. Journal of Competitive­ness, 12(1), 74–92. https://doi.org/10.7441/joc.2020.01.05

Kovacova, M., Kliestik, T., Valaskova, K., Durana, P., & Juhaszova, Z. (2019). Systematic re­view of variables applied in bankruptcy prediction models of Visegrad group countries. Oeconomia Copernicana, 10(4), 743-772. http://dx.doi.org/10.24136/oc.2019.034

Lifschutz, S., Jacobi, A. (2010). Predicting Bankruptcy: Evidence from Israel. International Journal of Business and Management, 5(4), 133-141. https://pdfs.semanticscholar.org/9ba6/e7d44a3b6d8708b5fde7930a42d703eede2b.pdf

Neumaierová, I., & Neumaier I. (2005). Index IN05. In European financial Systems. Paper pre­sented at 2nd International Scientific Conference EUROPEAN FINANCIAL SYSTEMS 2005, Brno Masaryk University, Brno, June 2005. pp. 143-146. ISBN 80-210-3753-9

Ninh, B. P. V., Do Thanh, T., & Hong, D. V. (2018). Financial distress and bankruptcy predic­tion: An appropriate model for listed firms in Vietnam. Economic Systems, 42(4), 616-624. https://doi.org/10.1016/j.ecosys.2018.05.002

Ohlson, J. A. (1980). Financial Ratios and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Research, 18(1), 109–131. https://doi.org/10.2307/2490395

Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics (Vol. 5, pp. 481-498). Boston, MA: Pearson.

Taffler, R. J. (1982). Forecasting Company Failure in the UK Using Discriminant Analysis and Finan­cial Ratio Data. Journal of the Royal Statistical Society. Series A (General), 145(3), 342–358. https://doi.org/10.2307/2981867

Zmijewski, M. E. (1984). Methodological Issues Related to the Estimation of Financial Distress Prediction Models. Journal of Accounting Research, 22, 59–82. https://doi.org/10.2307/2490859

 

Download Full Paper

Association of Economists and Managers of the Balkans – UdEkoM Balkan
179 Ustanicka St, 11000 Belgrade, Republic of Serbia

ITEMA conference publications are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.