The Efficiency of Bankruptcy Forecast Models in the Hungarian SME Sector

Ekes, Kristof Szeverin; Koloszár, László

doi:10.7441/joc.2014.02.05

Cited by 14 publications

(7 citation statements)

References 14 publications

(13 reference statements)

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“…Pam 2013;Erdogan 2008;Lanine, Vennet 2005) or for agriculture (Rajin et al 2016;Bieliková et al 2014;Vavřina et al 2013) and increasingly developed models for Internet companies. The bankruptcy models are specifically designed also for different segment of companies (according to their type or size), with significant differences especially in different states or continents (Taffler 1984;Ékes, Koloszár 2014;Blach, Wieczorek-Kosmala 2012). The relevance of bankruptcy models is determined by constant changes in the external environment of companies, globalization processes, the extinction of old industries and the emergence of new ones, etc.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Predictive Potential and Risks of Selected Bankruptcy Prediction Models in the Slovak Business Environment

Gavurová

Packova

Mišanková

et al. 2017

Journal of Business Economics and Management

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In our study, we focused on the assessment of four bankruptcy prediction models, to figure out which model is most appropriate in the conditions of the Slovak business environment. Based on the previous research within the Slovak conditions, we set a portfolio of 4 models to be assessed: Altman model (1984), Ohlson model (1980), indexes IN01 and IN05 that were validated on the sample of 700 Slovak companies. Based on previous studies we expected that IN indexes are superior to Ohlson and Altman model. The excellency of our research lies in validation and assessing the accuracy of bankruptcy prediction models at three levels: the overall accuracy, accuracy of the bankruptcy prediction, and the non-bankruptcy prediction accuracy. This analytical structure enables to look at the topic more complexly and to increase the objectification of accuracy of analysed models. Based on the results, we showed that Ohlson model is not applicable to predict bankruptcy in the Slovak conditions as reached the lowest bankruptcy prediction ability even if has high non bankruptcy prediction ability. On the other hand, we have confirmed our expectation about the bankruptcy prediction ability of index IN05, that is proven to be superior to Ohlson and Altman model and so is the most appropriate model for Slovak business environment.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Predictive Potential and Risks of Selected Bankruptcy Prediction Models in the Slovak Business Environment

Gavurová

Packova

Mišanková

et al. 2017

Journal of Business Economics and Management

View full text Add to dashboard Cite

show abstract

“…Again, using the same dataset, Virág and Nyitrai (2014) built models using the techniques of support vector machines and the rough set theory. Ékes and Koloszár (2014) estimated models for predicting bankruptcy of Hungarian small and medium-sized companies (SMEs). They used linear discriminant analysis, logit analysis, classification trees, and artificial neural networks.…”

Section: Literature Reviewmentioning

confidence: 99%

Logit business failure prediction in V4 countries

Ďurica

Valášková

Janošková

2019

Engineering Management in Production and Services

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The paper presents the creation of the model that predicts the business failure of companies operating in V4 countries. Based on logistic regression analysis, significant predictors are identified to forecast potential business failure one year in advance. The research is based on the data set of financial indicators of more than 173 000 companies operating in V4 countries for the years 2016 and 2017. A stepwise binary logistic regression approach was used to create a prediction model. Using a classification table and ROC curve, the prediction ability of the final model was analysed. The main result is a model for business failure prediction of companies operating under the economic conditions of V4 countries. Statistically significant financial parameters were identified that reflect the impending failure situation. The developed model achieves a high prediction ability of more than 88%. The research confirms the applicability of the logistic regression approach in business failure prediction. The high predictive ability of the created model is comparable to models created by especially sophisticated artificial intelligence approaches. The created model can be applied in the economies of V4 countries for business failure prediction one year in advance, which is important for companies as well as all stakeholders.

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“…Again, using the same dataset, Virág and Nyitrai [11] built models using the techniques of support vector machines and rough set theory. In 2014, Ékes and Koloszár [12] estimated models predicting bankruptcy of Hungarian SMEs using MDA, logistic regression analysis, and classification trees. Models estimated by them were highly efficient, mainly, compared to other Hungarian and foreign (Altman, Ohlson, etc.)…”

Section: Literature Reviewmentioning

confidence: 99%

Mda Financial Distress Prediction Model for Hungarian Companies

Ďurica¹,

Švábová²

2019

International Scientific Conference ERAZ - Knowledge Based Sustainable Development

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Company financial distress prediction is one of the most discussed issues of economists around the world in recent decades. From the first attempts in the 1960s to the present, one of the most widely used method to create these models is Multiple Discriminant Analysis. In the paper, we present the prediction model for Hungarian companies created using this method based on real data from the financial statements obtained from database Amadeus. Our database contains data of more than 250,000 companies and 26 financial indicators used as predictors. There is possibility to predict the financial difficulties of companies one year in advance using this model.

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The Efficiency of Bankruptcy Forecast Models in the Hungarian SME Sector

Cited by 14 publications

References 14 publications

Predictive Potential and Risks of Selected Bankruptcy Prediction Models in the Slovak Business Environment

Predictive Potential and Risks of Selected Bankruptcy Prediction Models in the Slovak Business Environment

Logit business failure prediction in V4 countries

Mda Financial Distress Prediction Model for Hungarian Companies

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