The use of discriminatory analysis in predicting the failure of Algerian small and medium enterprises, a sample study for the period 2005-2014

Abstract

This study aims to develop a predictive model for financial failure in Algerian small and medium enterprises (SMEs) using discriminant analysis. The research utilized 63 financial ratios applied to a balanced sample of 70 enterprises (35 failed/non-active and 35 sound/active) over the period 2005-2014.

The findings yielded a robust predictive model comprising ten financial ratios with significant Distinguishing capability: working capital to turnover (TR7), total sales to operating result (EF9), net result to short-term debt (P6), short-term liabilities to total assets (FS2), non-current assets to total debt (D6), gross operating surplus to total debt (P4), equity to total debt (D3), turnover to short-term liabilities (TR4), operating cash flow to financial expenses (CFO6), and working capital requirement to total assets (FS5). The model demonstrated strong predictive capability with an overall classification accuracy of 82.3%.

This research contributes to the development of early warning systems for financial distress in the Algerian SME sector, providing stakeholders with an effective tool for risk assessment and mitigation.