Predicting Corporate Bankruptcy in JSE-AltX Listed Firms

Abstract

ABSTRACT: The objective of the study is to predict corporate bankruptcy on the JSE-AltX (Alternative Stock Exchange) listed firms by employing Discriminant Analysis (MDA). Since its inception, the JSE-AltX has listed more than 100 firms and majority of them have migrated to the JSE main board. Motivated by the increasing number of delisted firms both pre and post their migration from JSE-AltX to the JSE main board, this study seeks to investigate the financial distress in the JSE-AltX listed firms. This study use a quantitative method to predict bankruptcy for a sample of 20 JSE-AltX listed firms that belongs to a wide range of industries, over the period from 1 January 2004 until 31 December 2015. Based on the previous literature it is evident that financial ratios play a significant role in the prediction of financial distress. Employing the same set of financial ratios (extracted from annual reports mainly the audited consolidated balance sheets and income statements) that are used in bankruptcy prediction as independent variables, the empirical results show that MDA has a statistically significant power in predicting default risk on the JSE-AltX listed firms. The findings show that the discrimination function is significant at the 5% level of significance. The MDA results reveal that, 7 out of the 20 sample firms are prone to bankruptcy, while the rest are not. Furthermore, the model classifies net profit margin (short-term profitability), current ratio (liquidity) and return on capital invested as the most important financial ratios in distinguishing the successful firms from unsuccessful firms post migration from the JSE-AltX to the JSE main board. Generally, this study results have policy implications which regulatory authorities, investors, employees and lenders will find interesting. Firstly, regulatory authorities can find this research useful as it provides effective review of the firm's financial distress conditions and subsequently signals default risk to various stakeholders. Secondly, this research will not only assist in identify potential default risks, but it will also enable different stakeholders to formulate mechanisms or relevant policies and procedures that will allow them to detect and prevent financial distress.