Comparing Mixed and Simple Models in Predicting Financial Distress in Firms Listed in Tehran Stock Exchange Fallahpour Saeed*, Sheshmani Majid**, Khorram Mehdi** *Assistant professor, Department of Finance and Insurance, School of Management, Tehran University, Tehran, Iran **MA of, Financial Management at School of Management, Tehran University, Tehran, Iran Online published on 6 February, 2016. Abstract The firm financial distress and bankruptcy will result in the waste resources and investment opportunities. In this study, a sample of 210 firms operating in different studies was surveyed. Of 28 indices under study, 11 indices with the highest impact on the firm financial distress were identified using Partial Least Squares (PLS). These indices were current assets/current liabilities, current assets/total assets, working capital/sales, sales/inventory, sales/receivables, net income/liabilities, receivables/liabilities, net income/sales, total liabilities/total assets, total liabilities/equities, and current liabilities/equities. It was also shown that all independent variables had a significant relationship with the financial distress. In addition, the firm financial distress was predicted using the mixed method of Support Vector Machines (SVM) and the simple method (simple SVM). The results of the paired samples t-test suggested that the mixed SVM is more accurate than the simple SVM in predicting the possibility of the financial distress. It was also noted that the mixed SVM is not only more accurate but also has more generalizability power than the simple SVM. Top Keywords Financial distress, partial least squares (PLS), support vector machines (SVM). Top |