Marek Durica – University of Zilina, Faculty of Operation and Economics of Transport and Communications, Department
of Quantitative Methods and Economic Informatics, Univerzitna 1, 010 26 Zilina, Slovak Republic
Lucia Svabova – University of Zilina, Faculty of Operation and Economics of Transport and Communications, Department
of Economics, Univerzitna 1, 010 26 Zilina, Slovak Republic
DOI: https://doi.org/10.31410/ERAZ.S.P.2019.199
5th International Conference – ERAZ 2019 – KNOWLEDGE BASED SUSTAINABLE DEVELOPMENT, Budapest – Hungary, May 23, 2019, SELECTED PAPERS
Published by: Association of Economists and Managers of the Balkans – Belgrade, Serbia
Conference partners: Faculty of Economics and Business, Mediterranean University, Montenegro; University of National and World Economy – Sofia, Bulgaria; Faculty of Commercial and Business Studies – Celje, Slovenia; Faculty of Applied Management, Economics and Finance โ Belgrade, Serbia;
ISBN 978-86-80194-21-9, ISSN 2683-5568, DOI: https://doi.org/10.31410/ERAZ.S.P.2019
Abstract
Company financial distress prediction is one of the most discussed issues of economists
around the world in recent decades. From the first attempts in the 1960s to the present,
one of the most widely used method to create these models is Multiple Discriminant Analysis.
In the paper, we present the prediction model for Hungarian companies created using this
method based on real data from the financial statements obtained from database Amadeus.
Our database contains data of more than 250,000 companies and 26 financial indicators used
as predictors. There is possibility to predict the financial difficulties of companies one year in
advance using this model.
Key words
Prediction model, Multidimensional Discrimination Analysis, Financial distress, Financial
ratios, Prediction ability.
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