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What is Predicting Financial Distress in SMEs about?

This paper investigates financial distress prediction for French small and medium-sized firms using various models, including Logit, Artificial Neural Networks, and Support Vector Machines. The results show that Support Vector Machines are the most accurate one year prior to distress, while a hybrid model is superior two years prior, achieving an accuracy of 94.28%. The findings offer valuable insights for managers, investors, and creditors to identify and mitigate financial distress risks.

Author

Tama SN

Language

EN