Could the Coefficients Re-Estimation Solve the Industry or Time Specific Issues?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F17%3APU124413" target="_blank" >RIV/00216305:26510/17:PU124413 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.iaras.org/iaras/home/caijems/could-the-coefficients-re-estimation-solve-the-industry-or-time-specific-issues" target="_blank" >http://www.iaras.org/iaras/home/caijems/could-the-coefficients-re-estimation-solve-the-industry-or-time-specific-issues</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Could the Coefficients Re-Estimation Solve the Industry or Time Specific Issues?

Popis výsledku v původním jazyce

The aim of this paper is to examine discrimination performance of three bankruptcy prediction models in environments and periods different from the ones utilized by deriving the models. We compared selected models’ accuracy in the original setting and present conditions. Secondary aim was to examine a way of possible increasing of the discrimination performance of models by the recalculation of the classification functions. Discrimination performance of the models and financial ratios was tested on companies operating in manufacturing business. Results conclusively demonstrate that the discrimination accuracy of bankruptcy models deteriorates significantly in different environments. The classification function of each model was recalculated using the data from Czech manufacturing companies. For the adjustment of models’ coefficients the same methods, as used originally by theirs authors, were applied, i.e. the probit method, the linear discrimination analysis and the logit method. The results shown, that the re-estimation of model coefficient could lead to its higher classification accuracy in alternative conditions. We can dedicate that recalculating of the classification rules is one of the ways to increase discrimination performance of the bankruptcy prediction models in different environment.

Název v anglickém jazyce

Could the Coefficients Re-Estimation Solve the Industry or Time Specific Issues?

Popis výsledku anglicky

The aim of this paper is to examine discrimination performance of three bankruptcy prediction models in environments and periods different from the ones utilized by deriving the models. We compared selected models’ accuracy in the original setting and present conditions. Secondary aim was to examine a way of possible increasing of the discrimination performance of models by the recalculation of the classification functions. Discrimination performance of the models and financial ratios was tested on companies operating in manufacturing business. Results conclusively demonstrate that the discrimination accuracy of bankruptcy models deteriorates significantly in different environments. The classification function of each model was recalculated using the data from Czech manufacturing companies. For the adjustment of models’ coefficients the same methods, as used originally by theirs authors, were applied, i.e. the probit method, the linear discrimination analysis and the logit method. The results shown, that the re-estimation of model coefficient could lead to its higher classification accuracy in alternative conditions. We can dedicate that recalculating of the classification rules is one of the ways to increase discrimination performance of the bankruptcy prediction models in different environment.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

50204 - Business and management

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

International Journal of Economics and Management Systems

ISSN

2367-8925

e-ISSN

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Svazek periodika

2017

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CY - Kyperská republika

Počet stran výsledku

8

Strana od-do

206-213

Kód UT WoS článku

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EID výsledku v databázi Scopus

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