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Predictive Ability of Chosen Bankruptcy Models: A Case Study of Slovak Republic

Siekelova Anna (), Tomas Kliestik and Adamko Peter ()
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Adamko Peter: University of Zilina, Faculty of Operation and Economics of Transport and Communications, Department of Economics, Univerzitna 1, 010 26Zilina, Slovak Republic

Economics and Culture, 2018, vol. 15, issue 1, 105-114

Abstract: Bankruptcy models are used to assess credit risk and predict financial situation to indicate the probable bankruptcy of the company. Contribution deals with the application of chosen bankruptcy models in analysing and predicting the financial health of selected companies. Most of the models have been developed abroad. In case of Slovak Republic, its application and correctness of the results can be problematic; therefore, we have focused primarily on those that have emerged in countries with a similar economy. We have calculated the selected prediction models in a sample of 500 Slovak enterprises. Predictive ability lower than 64% is considered as unfavourable. As part of the contribution, based on expert literature and relevant legislation, we have defined the criteria that allow to divide businesses into two groups: prosperous and non-prosperous. In the end, we compared the results of the selected models with the inclusion of enterprises in a prosperous and non- prosperous group based on the criteria set by us. We also dealt with examining of error types I (when an enterprise in bad financial condition is included in a non-bankruptcy group) and II (when an enterprise in good financial condition is included in a bankruptcy group). The aim is to analyse the predictive ability of the selected bankruptcy models.

Keywords: Bankruptcy; bankruptcy model; prediction of financial health; predictive ability; Slovak Republic (search for similar items in EconPapers)
JEL-codes: C53 G33 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:vrs:ecocul:v:15:y:2018:i:1:p:105-114:n:12

DOI: 10.2478/jec-2018-0012

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