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The bankruptcy prediction approach: An empirical study of comparison between the emerging market score model and bankruptcy prediction indicators approach in the Johannesburg Stock Exchange

Authors :
Ronel J. Cassim
Matthys Johannes Swanepoel
Source :
Journal of Economic and Financial Sciences, Vol 14, Iss 1, Pp e1-e8 (2021)
Publication Year :
2021
Publisher :
AOSIS, 2021.

Abstract

Orientation: The effective and timely bankruptcy prediction is crucial to the survival of companies. In order to attain a desired result an effective bankruptcy prediction tool needs to be applied within a South African context. Research purpose: The aim of this study was to determine whether bankruptcy could have been predicted within the 5 years prior to failure for the study period between 2016 and 2018. Motivation for the study: Most of the bankruptcy prediction studies in South Africa are industry- or sector-based, not many studies are found to be generic, easy to use and apply, and thus one model is applied for different industries or sectors. Research approach/design and method: From the population, the total sample consists of five companies within four different sectors, such as industrial, construction, retail, and personal and household sectors. Financial indicators (financial ratios) were obtained for both the BPIA and EMS from the INET (a South African supplier of quality financial data) McGregor BFA database, a JSE portal. A mixed-method research approach was applied by making use of a qualitative and quantitative methodology. Main findings: The findings revealed that the BPIA is an effective and reliable analytical tool to predict or detect the bankruptcy of South African companies. Practical/managerial implications: Based on the finding of the study companies within diverse industries should apply the BPIA regularly and take remedial action significantly to improve their financial well-being. Contribution/value add: The study has identified the BPIA has a better prediction accuracy than the renowned EMS model in South African context.

Details

ISSN :
23122803 and 19957076
Volume :
14
Database :
OpenAIRE
Journal :
Journal of Economic and Financial Sciences
Accession number :
edsair.doi.dedup.....161c957041018476d673eaef039539f9
Full Text :
https://doi.org/10.4102/jef.v14i1.539