Early warning models against bankruptcy risk for Central European and Latin American enterprises

Tomasz Korol

Economic Modelling, 2013, vol. 31, issue C, 22-30

Abstract: This article is devoted to the issue of forecasting the bankruptcy risk of enterprises in Latin America and Central Europe. The author has used statistical and soft computing methods to program the prediction models. It compares the effectiveness of twelve different early warning models for forecasting the bankruptcy risk of companies. In the research conducted, the author used data on 185 companies listed on the Warsaw Stock Exchange and 60 companies listed on Stock Exchange markets in Mexico, Argentina, Peru, Brazil and Chile. This population of firms was divided into learning and testing setdata. Each company was analyzed using the absolute values of 14 financial ratios and the dynamics of change of these ratios.

Keywords: Bankruptcy prediction; Early warning model; Financial crisis; Artificial intelligence (search for similar items in EconPapers)
JEL-codes: F37 G33 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0264999312003732
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:31:y:2013:i:c:p:22-30

DOI: 10.1016/j.econmod.2012.11.017

Access Statistics for this article

Economic Modelling is currently edited by S. Hall and P. Pauly

More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().