Comparison Bankruptcy Models for Prediction of the Financial Health of Slovak Civil Engineering Companies

Authors

  • Mária Bohdalová Comenius University in Bratislava Faculty of Management Odbojárov 10 82005 Bratislava
  • Natália Klempaiová Comenius University in Bratislava Faculty of Management Odbojárov 10 82005 Bratislava

Keywords:

Altman model, Taffler model, Index IN05, Quick test, Binkert model, Credit worthiness index, building industry, bankruptcy, restructuring, models of creditworthiness

Abstract

Purpose of the article Main purpose of the paper is give new inside how to compare selected creditworthy and bankruptcy models and to determine which one model is appropriate for private building companies in Slovakia.

Methodology/methods The analysis was based on real selection of companies from static point of view (one year data) and selection of companies being actually in recession from dynamic point of view (4 years data). Static analysis was carried out for 1360 private Slovak civil engineering companies. From a dynamic point of view, we have analyzed the predictive value of the IN05 model for bankrupt companies over four full consecutive calendar years immediately prior to their bankruptcy (dynamic point of view). The number of bankrupt companies was 35. Informative value of chosen indicators is in case of dynamic analyze evaluated according to number of correct or incorrect predictions.

Scientific aim The scientific aim is to analyze selected creditworthy and bankruptcy models and to detect their informative value for private building companies in Slovakia. The paper contributes to the literature regarding the analysis of financial health of the Slovak companies. Our study expands and complements existing study which analyze the creditworthy and bankruptcy models.

Findings We found out, that the best model is index IN05. The results of our analyses have come to comparable results. Based on them index IN05 and Altman model showed up as the most reliable for building industry.

Conclusions Informative value of chosen indicators is in case of dynamic analyze evaluated according to number of correct or incorrect predictions. This method was not suitable to use for static analysis based on a real sample. The results of the static analysis were based on the comparison of the examined models in the individual categories (structure of success) and at the same time within the whole sample. Better was considered a model that had a more successful structure of success in terms of business (company). Indicators of creditworthiness and bankruptcy should be a part of a deeper analysis of the financial situation of a companies. If a company has attempted to ascertain the status only through these indicators, it should choose at least two indicators. In the case of private domestic construction companies, we would recommend the combination of the IN05 and the Altman model as they complete with each other appropriately.

 

Author Biographies

Mária Bohdalová, Comenius University in Bratislava Faculty of Management Odbojárov 10 82005 Bratislava

Department of Information Systems

Natália Klempaiová, Comenius University in Bratislava Faculty of Management Odbojárov 10 82005 Bratislava

Department of Information Systems

References

Anderson, D. R., Sweeney, D. J., Williams, T. A., Freeman, J., Shoesmith, E. (2010). Statistics for Business and Economics. Cengage Learning EMEA. Hampshire.

Brozyna, J., Mentel, G., Pisula, T. (2016). Statistical Methods of the Bankruptcy Prediction in the Logistics Sector in Poland and Slovakia. Transformations in Business & Economics, 15(1), 80-96. ISSN 1648-4460.

Diheneščíková, D., Hičák, Š. (2011). Index IN05 v priemyselných podnikoch na východnom Slovensku. Trendy v podnikání, 1(2). Available online: https://www.dfek.zcu.cz/tvp/doc/2011-2.pdf. p.40

Finstat, Ltd. (2017). The Database of financial data. Retrieved from: https://www.finstat.sk/databaza-financnych-udajov

Gulka, M. (2016). Model predikcie úpadku obchodných spoločností podnikajúcich v podmienkach SR. BIATEC, 24(6), 5-9. Retrieved from http://www.nbs.sk/_img/Documents/_PUBLIK_NBS_FSR/Biatec/Rok2016/06-2016/Biatec_6_16_03Gulka.pdf

Klempaiová, N. (2017). Use of Statistics Methods for Predicting Bankruptcy. Diploma Thesis. Comenius University, Bratislava.

Neumaierová, I., Neumaier, I. (2005). Index IN05. In Sborník příspěvků mezinárodní vědecké konference „Evropské finanční systémy“, 143-148. ISBN 80-210-3753-9.

Pervan, I., Pervan, M., Vukoja, B. (2011). Prediction of Company Bankruptcy Using Statistical Techniques – Case of Croatia. Croatian Operational Research Review (CRORR), 2(1), 158-167.

Režňáková, M., Karas, M. (2014). Bankruptcy Prediction Models: Can the prediction power of the models be improved by using dynamic indicators? Procedia economics and Finance, 12, 565-574. Doi: 10.1016/S2212-5671(14)00380-3

Růčková, P. (2015). Finanční analýza: metody, ukazatele, využití v praxi. 5th ed. Praha: Grada Publishing.

Řehák, J., Brom, O. (2015). SPSS – Praktická analýza dat. Brno: Computer Press.

Smaranda, C. (2014) Scoring functions and bankruptcy prediction models – case study for Romanian companies. Procedia Economics and Finance, 10, 217-226. Doi: 10.1016/S2212-5671(14)00296-2

The Statistical Office of the Slovak Republic. (2016). Yearbook of Construction in SR 2016. Bratislava, 11-12.

Tsai, C.-F. (2009). Feature selection in bankruptcy prediction. Knowledge-Based Systems, 22(2), 120-127. Doi: 10.1016/j.knosys.2008.08.002

Verma, J.P. (2013). Data Analysis in Management with SPSS Software. 2nd ed. Springer India.

Zalai, K., Dávid, A., Šnircová, J., Moravčíková, E., Hurtošová, J., Tučníková (Sovíková), D. (2016). Finančno-ekonomická analýza podniku. 9th ed. Bratislava: Sprint 2.

Downloads

Published

2017-10-01

Issue

Section

Finance in Digital Transformation