Research on financial time series forecasting based on SVM
Yujun Yang, Yang Yimei, Li Jianping · 2016
The support vector machine (SVM) is a machine learning method developed based on statistical learning theory. The SVM is widely used in classification and prediction. Since the financial time series is complex, the traditional forecasting methods are less reliable. In this paper, we research on financial time series forecasting based on the support vector machine. Although the speed of prediction process is slow, it can improve the prediction accuracy of the financial time series. The experimental results show the prediction accuracy of this approach based on the support vector machine.