Preliminary communication

Choosing a method for predicting economic performance of companies

J. Dvořáček ; Faculty of Mining and Geology, VŠB-Technical University of Ostrava, Czech Republic
R. Sousedíková ; Faculty of Mining and Geology, VŠB-Technical University of Ostrava, Czech Republic
M. Řepka ; Faculty of Mining and Geology, VŠB-Technical University of Ostrava, Czech Republic
L. Domaracká ; BERG Faculty, Technical University of Košice, Slovakia
P. Barták ; Kámen Ostroměř, Czech Republic
M. Bartošíková ; Faculty of Mining and Geology, VŠB-Technical University of Ostrava, Czech Republic

Abstract

This paper reports on the efforts to find a method for predicting economic results of companies. The input data files consist of 93 profitable companies and 93 bankrupt firms. From the total number of 93 firms in both categories, data of 72 firms served for establishing a classification criterion, and for the rest of 21 firms, a prognosis of their economic development was performed. The classification criterion for prognosticating the future economic development has been established by applications of discriminate analysis, logit analysis, and artificial neural network methods. The application of artificial neural networks has provided for better classification accuracies of 90,48 % for successful firms, and 100 % for bankrupt firms.

Keywords

prediction; discriminant analysis; logit analysis; artificial neural networks; classification accuracies

Hrčak ID:

82922

URI

https://hrcak.srce.hr/82922

Publication date:

1.10.2012.

Article data in other languages: croatian

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