Economic Value Added Prediction in Selected Industrial Branches: Case of Czech Republic.
Konferenční objektStatus neznámýpeer-reviewedpostprintDatum publikování
2015
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WSEAS Press
Abstrakt
Qualitative methods determining financial health of a firm are not only time-consuming and expensive, but can also deliver distorted subjective evaluation. Quantitative methods do not include qualitative parameters, but they are usually time-saving and objective in the field of determining current financial condition. Index IN05 is a quantitative model created in 2005 as a successor of IN01 from 2001. The upgrade thus came already after four years of its existence. In 2005, IN05 was the most accurate model to predict a financial situation of a firm on the basis of EVA, but does it still apply today? The first objective was assessing current abilities of IN05 to predict financial health of a firm on the basis of achieving positive value of EVA (Economic Value Added). The second objective was to find a way how to increase the accuracy or decision making ability of the model for selected industries. The research was conducted by analysis of financial statements of more than 500 firms. All selected firms are in the field of processing industry. It was found that current accuracy of the model on the basis of EVA decreased over the time. As a result of modification of the evaluation criteria the accuracy slightly increased. The key contribution of the modification is a significant increase of decision making ability of the model.
Rozsah stran
p. 143-148
ISSN
2227-460X
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Projekt
SGSFES_2015001/Ekonomický a sociální rozvoj v soukromém a veřejném sektoru
Zdrojový dokument
Proceedings of the 4th International Conference on Economics, Political and Law Science
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4th International Conference on ECONOMICS, POLITICAL and LAW SCIENCE (07.11.2015 - 09.11.2015)
ISBN
978-1-61804-348-1
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EVA, financial performance, index IN05, financial prediction, financial health, distress, model accuracy, EVA, výkonnost podniku, index IN05, finanční zdraví, úpadek, přesnost modelu