Original Research

Using fundamental, market and macroeconomic variables to predict financial distress: A study of companies listed on the Johannesburg Stock Exchange

Sibusiso W. Sabela, Leon M. Brummer, John H. Hall, Hendrik P. Wolmarans
Journal of Economic and Financial Sciences | Vol 11, No 1 | a168 | DOI: https://doi.org/10.4102/jef.v11i1.168 | © 2018 Sibusiso W. Sabela, Leon M. Brummer, John H. Hall, Hendrik P. Wolmarans | This work is licensed under CC Attribution 4.0
Submitted: 30 January 2018 | Published: 24 April 2018

About the author(s)

Sibusiso W. Sabela, Department of Financial Management, University of Pretoria, South Africa
Leon M. Brummer, Department of Financial Management, University of Pretoria, South Africa
John H. Hall, Department of Financial Management, University of Pretoria, South Africa
Hendrik P. Wolmarans, Department of Financial Management, University of Pretoria, South Africa

Abstract

This study presents a three-stage approach in determining financial distress of companies listed on the Johannesburg Stock Exchange. A novel feature of the present study is that it deviates from a binary classification of corporate distress prediction to present a multinomial outcome where the model predicts distressed, depressed and healthy companies. The research results show an improvement in the prediction accuracy rate when fundamental data is combined with market-based data. However, the further addition of macroeconomic indicators does not enhance the prediction accuracy.

Keywords

logistic regression analysis; financial distress; profitability and liquidity; corporate debt

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Crossref Citations

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