Identifying Bankruptcy Prediction Factors in Various Environments: A Contribution to the Discussion on the Transferability of Bankruptcy Models

Kód výsledku v 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>

Výsledek na webu

<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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Jazyk výsledku

angličtina

Název v původním jazyce

Identifying Bankruptcy Prediction Factors in Various Environments: A Contribution to the Discussion on the Transferability of Bankruptcy Models

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Identifying Bankruptcy Prediction Factors in Various Environments: A Contribution to the Discussion on the Transferability of Bankruptcy Models

Popis výsledku anglicky

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.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

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OECD FORD obor

50602 - Public administration

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

INTERNATIONAL JOURNAL of MATHEMATICAL MODELS AND METHODS IN APPLIED SCIENCES

ISSN

1998-0140

e-ISSN

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Svazek periodika

8

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

6

Strana od-do

69-74

Kód UT WoS článku

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EID výsledku v databázi Scopus

2-s2.0-84902496176