Financial Distress Prediction of China Listed Companies Based on SD Model and LSSVM

摘要

Financial distress prediction has drown a lot ofresearch interests in previous literature, and many studies haveshown that artificial intelligence techniques achieve betterperformance than traditional statistical ones. In this paper, weuse Least Squares Support Vector Machine (LSSVM) to carrythrough empirical study for financial distress prediction of Chinalisted companies. The independent variables as input to LSSVMclassifier are deduced by Higgins's sustainable Development (SD)model. Result shows that the combination of SD model andLSSVM has good classification abilities.