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PREDICTION CAPABILITIES OF BANKRUPTCY MODELS IN A DIFFERENT ENVIRONMENT: AN EXAMPLE OF THE ALTMAN MODEL UNDER THE CONDITIONS IN THE VISEGRAD GROUP COUNTRIES

100%
Režňáková M., Karas M.
Ekonomický časopis (Journal of Economics)
|
2015
|
vol. 63
|
issue 6
617 – 633
EN
This paper presents the results of research into the discrimination capability of the Altman bankruptcy model. The authors are contributing in this way to discussion of the possible transferability of models that have been created in a different environment or a different time period. Efforts at model transfer are motivated by an assumption to obtain the same or similar discrimination accuracy for the given model as that declared by its creators. The tests performed have clearly shown that the discrimination accuracy of a model falls significantly when it is used in a different environment. This led in turn to an investigation of ways in which the discrimination capability of a model may be increased by means of the determination of new weightings for model variables and grey-zone boundaries. The accuracy of the original models was not attained, although an increase was seen in the discrimination accuracy of these models.
2

DETERMINANTS OF CAPITAL STRUCTURE: EMPIRICAL EVIDENCE FROM SLOVAKIA

81%
Režňáková M., Svoboda P., Polednáková A.
Ekonomický časopis (Journal of Economics)
|
2010
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vol. 58
|
issue 3
237-250
EN
The study analyses determinants of capital structure and capital structure theories - pecking order theory and trade-off theory. The main objective is to investigate which determinants influence capital structure and subsequently which model describes financing decisions in Slovak Republic better. The authors used panel data of 1,100 non-financial companies from Slovakia in the period of 6 years from 2002 to 2007. Results prove the trade-off theory to be more exact in Slovak conditions.
3

PREDICTION OF SYNERGIES IN MERGERS

81%
Režňáková M., Pěta J., Karas M.
Ekonomický časopis (Journal of Economics)
|
2020
|
vol. 68
|
issue 2
168 – 187
EN
In this paper we present a method of calculating the value of synergy resulting from mergers between private companies as well as a model for the prediction of potential synergy values in contemplated mergers (M&A deals). We first examined the process of determining the value of a synergy. Since we analysed mergers involving private mechanical engineering companies, we used the discounted capital cash flow method for the determination of the synergy value. We divided the selected mergers according to the achieved synergy value into two groups, i.e. into successful mergers and failed mergers. We then analysed the two groups in order to identify financial ratios with statistically significant differences (deviations). We then used those ratios to establish a rule for the differentiation between mergers that would increase in business value, i.e. with positive synergy, and those whose value would decrease. A decision rule was developed using the classification and regression trees method. In the research sample, the developed model distinguished successful merger from failed ones with 92% accuracy.
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