Artikel

Limitation of financial health prediction in companies from post-communist countries

The financial health of a company can be seen as the ability to maintain a balance against changing conditions in the environment and at the same time in relation to everyone participating in the business. In the evaluation of financial health and prediction of financial problems of the companies, various indexes are used that can serve as input for expert estimation or creation of various models using, for example, multi-dimensional statistical methods. The practical application of the proper method for evaluation of financial health has been analysed in post-communist countries, since they have common historic experiences and economic interests. During the research we followed up the following indexes: Altman model, Taffler model, Springate model, and the index IN, based on multi-dimensional discrimination analysis. From the research results there is obvious a necessity to combine available methods in post-communist countries and at least to eliminate their disadvantages partially. Experiences from prediction models have proved their relatively high prediction ability, but only in perfect conditions, which cannot be affirmed in post-communist countries. The task remains to modify existing indexes to concrete situations and problems of the individual industries in the chosen countries, which have unique conditions for business making.

Sprache
Englisch

Erschienen in
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 12 ; Year: 2019 ; Issue: 1 ; Pages: 1-14 ; Basel: MDPI

Klassifikation
Wirtschaft
Thema
managing of financial health
risk of bankruptcy
prediction methods
post-communist countries

Ereignis
Geistige Schöpfung
(wer)
Csikosova, Adriana
Janoskova, Maria
Culkova, Katarina
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2019

DOI
doi:10.3390/jrfm12010015
Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Csikosova, Adriana
  • Janoskova, Maria
  • Culkova, Katarina
  • MDPI

Entstanden

  • 2019

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