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Abstract
This manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and multilayer artificial neural network, and decision trees. Such a research approach will answer the question of whether changes in indicators are relevant predictors of a company’s coming financial crisis because declines or increases in values do not immediately indicate that the company’s economic situation is deteriorating. The research relies on two samples of firms—the learning sample of 50 bankrupt and 50 non-bankrupt enterprises and the testing sample of 250 bankrupt and 250 non-bankrupt firms.
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- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
Journal of Risk and Financial Management
no. 12,
pages 1 - 15,
ISSN: 1911-8074 - Language:
- English
- Publication year:
- 2019
- Bibliographic description:
- Korol T.: Dynamic Bankruptcy Prediction Models for European Enterprises// Journal of Risk and Financial Management -Vol. 12,iss. 4 (2019), s.1-15
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/jrfm12040185
- Sources of funding:
- Verified by:
- Gdańsk University of Technology
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