Identifying Bankruptcy Prediction Factors in Various Environments: A Contribution to the Discussion on the Transferability of Bankruptcy Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F14%3APU109288" target="_blank" >RIV/00216305:26510/14:PU109288 - isvavai.cz</a>
Result on the web
<a href="http://www.naun.org/main/NAUN/ijmmas/2014/a042001-065.pdf" target="_blank" >http://www.naun.org/main/NAUN/ijmmas/2014/a042001-065.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Identifying Bankruptcy Prediction Factors in Various Environments: A Contribution to the Discussion on the Transferability of Bankruptcy Models
Original language description
As has been demonstrated by Beaver and subsequently Altman, financial indicators can pick up the risk of impending bankruptcy. This idea led to the construction of bankruptcy models that proved capable of identifying companies threatened with insolvency with great accuracy. A number of authors have demonstrated that the accuracy of bankruptcy models falls significantly if the given model is used in an environment other than that for which it was originally developed. The aim of this article is to identify the financial indicators that are statistically significant predictors of bankruptcy in various environments. The sample investigated is comprised of data on industrial concerns in the Visegrad Four countries for the years 2007 to 2012. A bankruptcy model based on the same set of variables was derived for each country by the method of Boosted Trees. The variables that are statistically significant in all countries and the variables that are specific for individual countries were identified by means of comparison of the significance of the variables in the models created (i.e. in different environments). Most important indicators of bankruptcy prediction can be described as indicators of company size, in our research the value of sales and total assets. Additional significant predictors are debt ratios, liquidity and profitability. However their significance for bankruptcy prediction is different, which is demonstrated by a high degree of variability of these indicators in the surveyed data sample.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50602 - Public administration
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
INTERNATIONAL JOURNAL of MATHEMATICAL MODELS AND METHODS IN APPLIED SCIENCES
ISSN
1998-0140
e-ISSN
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Volume of the periodical
8
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
6
Pages from-to
69-74
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-84902496176