CONSTRUCTION ELEMENTS OF BANKRUPTCY PREDICTION MODELS IN MULTI–DIMENSIONAL EARLY WARNING SYSTEMS

Jaroslaw Kaczmarek

Polish Journal of Management Studies, 2012, vol. 5, issue 1, 136-149

Abstract: A consequence of the inevitability of the occurrence of internal crises in companies is the taking of preventive action in place of purely remedial measures. In this respect a significant role is played by Early Warning Systems (EWS), which provide early warning information and financial threat assessments relating to the continuation of operations and bankruptcy not only for individual companies as such but also for companies as a whole. The limitations of existing models used for EWS purposes have led to the elaboration of new models, estimated on one of the largest hitherto drawn up teaching sets, constituting more than five hundred bankrupt companies. These models also distinguish themselves through the application of innovative methods and precise instruments; the structural concept of these models for multi–dimensional EWS purposes, accompanied by elements used for predicting, is presented in this article.

Keywords: bankruptcy; bankruptcy prediction; early warning system; logistic regression model (search for similar items in EconPapers)
JEL-codes: G33 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://pjms.zim.pcz.pl/PDF/PJMS5/CONSTRUCTIONELEME ... rmat:Application/pdf
http://pjms.zim.pcz.pl/construction-elements-of-ba ... ile-Format:text/html

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:pcz:journl:v:5:y:2012:i:1:p:136-149

Access Statistics for this article

More articles in Polish Journal of Management Studies from Czestochowa Technical University, Department of Management Contact information at EDIRC.
Bibliographic data for series maintained by Paula Bajdor ().