Bankruptcy Practice in Countries of Visegrad Four

Numerous economists and analysts from all over the world have been trying to find an appropriate method to assess company health and to predict its eventual financial distress for many years. No economy is a small isolated subject, and the bankruptcy of a company can cause through its stakeholders′...

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Veröffentlicht in:Economics and Culture 2017-06, Vol.14 (1), p.108-118
Hauptverfasser: Misankova, Maria, Zvarikova, Katarina, Kliestikova, Jana
Format: Artikel
Sprache:eng
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Zusammenfassung:Numerous economists and analysts from all over the world have been trying to find an appropriate method to assess company health and to predict its eventual financial distress for many years. No economy is a small isolated subject, and the bankruptcy of a company can cause through its stakeholders′ significant impact on the sustainable economic development. Otherwise, companies are very complicated entities, and it is not a simple task to estimate company’s future development. Together with the best-known Z-Score model of bankruptcy prediction developed by Altman, numerous models worldwide that are based on different methodologies have been developed. We assume that individual state’s economy has major influence on the final form of these models as well as there are several common characteristics between Slovak economy and economy of countries of Visegrad Four. Therefore, we applied chosen bankruptcy prediction models developed in countries of Visegrad Four on the set of Slovak companies and validated their prediction ability in specific condition of the Slovak economy. On the basis of the provided calculations, we compared gained results with the prediction capability of other popular prediction models also applied on the data set of Slovak companies. Through this, we pointed out the importance of the development of unique bankruptcy prediction model, which will be constructed in the specific condition of individual countries, and highlighted the weak forecasting ability of foreign models.
ISSN:2256-0173
2255-7563
2256-0173
DOI:10.1515/jec-2017-0010