Could the Altman Z-score model detect the financial distress in Ghana? Multivariate discriminant analysis

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Abstract

The purpose of this paper is to assess the effectiveness of the Altman Z-score model to discriminate between financially distressed and non financially distressed manufacturing firms listed on the Ghana Stock Exchange. Eleven firms consisting of two financially distressed and nine non-financially distressed manufacturing firms were analysed. Independent descriptive statistics, independent sample t-test, and multivariate discriminant analysis were the analytical tools used to analyse the hypotheses of this study. The study revealed that working capital/total assets and sales/total assets were the major discriminators of financially distressed firms on the Ghana Stock Exchange. Multivariate discriminant analysis revealed an accuracy rate of 79.9% to detect financially distressed firms in Ghana.

Keywords: Altman Z-score, Financially Distressed, Non-financially Distressed, Discriminant Analysis

Authors’ individual contribution: Conceptualization – J.M.; Methodology – J.M. and R.A.-A.; Formal Analysis – J.M. and R.A.-A.; Writing – R.A.-A.; Original Draft –J.M.; Review & Editing – J.M. and R.A.-A.; Resources – J.M. and R.A. A.; Visualization – J.M. and R.A.-A.; Supervision – J.M. and R.A.-A.

Declaration of conflicting interests: The Authors declare that there is no conflict of interest.

JEL Classification: G32, G33, M48

Received: 07.02.2020
Accepted: 23.06.2020
Published online: 24.06.2020

How to cite this paper: MacCarthy, J., & Amoasi-Andoh, R. (2020). Could the Altman Z-score model detect the financial distress in Ghana? Multivariate discriminant analysis. Corporate Governance and Sustainability Review, 4(2), 8-19. https://doi.org/10.22495/cgsrv4i2p1