Artikel
Application of discriminant models in predicting a company's risk of bankruptcy
Aim: The aim of the paper is to review Polish discriminant models and their application to predict bankruptcy on the examples of selected joint stock companies in the years 2013 - 2015.Research method: The paper was written on the basis of literature search within the scope discussed. Further, the authors carried out their own examination of certain joint stock companies listed on the Warsaw Stock Exchange (WSE). The discriminant analysis was conducted on the basis of financial statements of the selected companies using Mączynska's model, the model developed by Gajdka and Stos, Hadasik's model and the Poznański model.Findings: The analysis shows that not all discriminant models reflect changes in the financial condition of a company. Nevertheless, they are a good tool to evaluate the risk of failure, provided that more than one model are used.Originality /value of the paper /scholarly contribution: Discriminant models are universal, which means that they can be applied to any company, regardless of the industry they operate in. The results of the analysis can be used as a basis for further studies on the accurate adjustment of discriminant models to companies, depending on the type of business.
- Sprache
-
Englisch
- Erschienen in
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Journal: The Central European Review of Economics and Management (CEREM) ; ISSN: 2544-0365 ; Volume: 1 ; Year: 2017 ; Issue: 1 ; Pages: 121-134 ; Wrocław: WSB University in Wrocław
- Klassifikation
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Wirtschaft
Corporate Finance and Governance: General
- Thema
-
bankruptcy
company's bankruptcy
discriminant models
- Ereignis
-
Geistige Schöpfung
- (wer)
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Wieprow, Joanna Małgorzata
Barlik, Justyna
- Ereignis
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Veröffentlichung
- (wer)
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WSB University in Wrocław
- (wo)
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Wrocław
- (wann)
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2017
- DOI
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doi:10.29015/cerem.287
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Wieprow, Joanna Małgorzata
- Barlik, Justyna
- WSB University in Wrocław
Entstanden
- 2017
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