Financial distress prediction based on SVM and MDA methods: the case of Chinese listed companies

How to accurately predict financial distress is an important issue for enterprise managers, investors, creditors and supervisors. In this paper we develop SVM models (Support Vector Machine) and MDA (Multivariate Discriminant Analysis) models, using Chinese listed companies as our sample. The empirical results show that the prediction ability of SVM models outperforms the MDA models. Additionally, internal governance and external market variables, as well as macroeconomic variables are added as the predictive variables. The results indicate that these variables have theoretical and empirical linkage with the financial distress of Chinese listed companies.