Prediction by financial and economic analysis in the conditions of forest enterprises

Andrea Majdáková, Blanka Giertliová and Iveta Hajdúchová
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Andrea Majdáková: Department of Forest Economics and Management, Faculty of Forestry, Technical University in Zvolen Zvolen, Slovak republic
Iveta Hajdúchová: Department of Forest Economics and Management, Faculty of Forestry, Technical University in Zvolen Zvolen, Slovak republic

Journal of Forest Science, 2020, vol. 66, issue 1, 1-8

Abstract: Individual companies need to know their financial condition. They have a wide range of methods and procedures to create a system of the financial and economic analysis of a company. The analysis is focused on the evaluation of a specific group of methods for predicting the financial health of a business entity. Evaluations of the financial situation of a company are divided into point methods, mathematical and statistical methods and neural networks. The individual methods differ from each other in difficulty, in the extent of the analyzed areas and possibilities of application. The aim of this work is to assess the possibilities of using selected methods of comprehensive evaluation of companies as a tool for an analysis of the position of each company in the branch. The suitability and feasibility of each method are tested on a selected group of companies. Quick Test, Tamari Model, Beaver Model are included in this work. Based on the results, improvements and recommendations for the practical use were suggested. The results showed that the best predictive methods are Quick Test and Tamari Model, because they are quick and unequivocal when assessing the analyzed companies. An inappropriate prediction method is the Beaver model, which uses only two financial indicators to evaluate companies.

Keywords: financial and economic analysis; prediction analysis; Quick test; Tamari model; Beaver model (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnljfs:v:66:y:2020:i:1:id:84-2019-jfs

DOI: 10.17221/84/2019-JFS

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