Bankruptcy Modelling: Factors Influencing Models Predictability

D 2021

Bankruptcy Modelling: Factors Influencing Models Predictability

SPONEROVÁ, Martina

Základní údaje

Originální název

Bankruptcy Modelling: Factors Influencing Models Predictability

Autoři

SPONEROVÁ, Martina (203 Česká republika, garant, domácí)

Vydání

Vol.3 No.1. Zagreb, Proceedings of FEB Zagreb 12th International Odyssey Conference on Economics and Business, od s. 743 - 753, 11 s. 2021

Nakladatel

University of Zagreb

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

50206 Finance

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

Odyssey Conference

Kód RIV

RIV/00216224:14560/21:00122171

Organizační jednotka

Ekonomicko-správní fakulta

ISSN

DOI

http://dx.doi.org/10.22598/odyssey/2021.3

UT WoS

001230124200051

Klíčová slova anglicky

credit risk; bankruptcy prediction; SME; financial indicator

Změněno: 8. 7. 2024 14:52, Mgr. Michal Petr

Anotace

V originále

Many authors during the last fifty years have examined several possibilities to predict business failure. They have studied bankruptcy prediction models under different perspectives but still could not indicate the most reliable model. The aim of this article is finding a direction on how to build bankruptcy prediction models. We want to see if the companies' segmentation according to different criteria and using so-called standard financial indicators means better explanatory power while predicting bankruptcy. Considering the research objective, the following hypotheses were set: H1: The usually used financial indicators in financial analysis are the most important for bankruptcy prediction.; H2: The application of a model based on different segmentation criteria improves the reliability of bankruptcy prediction. This paper focuses on the Czech economy, specifically at small and medium-sized enterprises (SMEs). It is the ongoing research about the value of several popular bankruptcy models that are often applied, namely the Altman Z-score, the Ohlson O-score, the Zmijewski's model, the Taffler's model, and the IN05 model. We have used logistic regression and investigated around 2 800 companies, of which 642 failed during 2010 – 2017. Our findings confirm hypothesis H2 and reject hypothesis H1. Some suggestion arises from it. When we develop a bankruptcy model, it is necessary to sort companies according to different criteria. It also confirms findings of the last years literature review the closer the similarity of businesses, the greater accuracy of bankruptcy models. Further, it is required to exploit common used financial indicators with a combination of modified indicators to assess the probability of bankruptcy precisely.

Návaznosti

MUNI/A/1219/2020, interní kód MU

Název: Kryptoaktiva ve finančních výkazech obchodních společností (Akronym: CAST)

Investor: Masarykova univerzita, Kryptoaktiva ve finančních výkazech obchodních společností

Citovat

SPONEROVÁ, Martina. Bankruptcy Modelling: Factors Influencing Models Predictability. Online. In Braje I.N., Jaković B., Hodak D.F.,. Proceedings of FEB Zagreb 12th International Odyssey Conference on Economics and Business. Vol.3 No.1. Zagreb: University of Zagreb, 2021, s. 743 - 753. ISSN 2671-132X. Dostupné z: https://dx.doi.org/10.22598/odyssey/2021.3.

@inproceedings{1787919,
   author = {Sponerová, Martina},
   address = {Zagreb},
   booktitle = {Proceedings of FEB Zagreb 12th International Odyssey Conference on Economics and Business},
   doi = {http://dx.doi.org/10.22598/odyssey/2021.3},
   edition = {Vol.3 No.1},
   editor = {Braje I.N., Jaković B., Hodak D.F.,},
   keywords = {credit risk; bankruptcy prediction; SME; financial indicator},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Zagreb},
   pages = {743 - 753},
   publisher = {University of Zagreb},
   title = {Bankruptcy Modelling: Factors Influencing Models Predictability},
   url = {https://odyssey.net.efzg.hr/conference-proceedings/proceedings-of-feb-zagreb},
   year = {2021}
}

TY  - JOUR
ID  - 1787919
AU  - Sponerová, Martina
PY  - 2021
TI  - Bankruptcy Modelling: Factors Influencing Models Predictability
PB  - University of Zagreb
CY  - Zagreb
KW  - credit risk
KW  - bankruptcy prediction
KW  - SME
KW  - financial indicator
UR  - https://odyssey.net.efzg.hr/conference-proceedings/proceedings-of-feb-zagreb
N2  - Many authors during the last fifty years have examined several possibilities to predict business failure. They have studied bankruptcy prediction models under different perspectives but still could not indicate the most reliable model. The aim of this article is finding a direction on how to build bankruptcy prediction models. We want to see if the companies' segmentation according to different criteria and using so-called standard financial indicators means better explanatory power while predicting bankruptcy. Considering the research objective, the following hypotheses were set: H1: The usually used financial indicators in financial analysis are the most important for bankruptcy prediction.; H2: The application of a model based on different segmentation criteria improves the reliability of bankruptcy prediction. This paper focuses on the Czech economy, specifically at small and medium-sized enterprises (SMEs). It is the ongoing research about the value of several popular bankruptcy models that are often applied, namely the Altman Z-score, the Ohlson O-score, the Zmijewski's model, the Taffler's model, and the IN05 model. We have used logistic regression and investigated around 2 800 companies, of which 642 failed during 2010 – 2017. Our findings confirm hypothesis H2 and reject hypothesis H1. Some suggestion arises from it. When we develop a bankruptcy model, it is necessary to sort companies according to different criteria. It also confirms findings of the last years literature review the closer the similarity of businesses, the greater accuracy of bankruptcy models. Further, it is required to exploit common used financial indicators with a combination of modified indicators to assess the probability of bankruptcy precisely.
ER  -

SPONEROVÁ, Martina. Bankruptcy Modelling: Factors Influencing Models Predictability. Online. In Braje I.N., Jakovi\'c B., Hodak D.F.,. \textit{Proceedings of FEB Zagreb 12th International Odyssey Conference on Economics and Business}. Vol.3 No.1. Zagreb: University of Zagreb, 2021, s.~743 - 753. ISSN~2671-132X. Dostupné z: https://dx.doi.org/10.22598/odyssey/2021.3.

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