title: A feature fusion based forecasting model for financial time series.
abstract: Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models.
authors: Key Laboratory of Fiber Optic Sensing Technology and Information Processing, School of Information Engineering, Wuhan University of Technology, Wuhan, China.
authors: Zhiqiang
authors: Z
authors: Guo
authors: Department of Financial Math and Financial Engineering, South University of Science and Technology of China, Shenzhen, China.
authors: Huaiqing
authors: H
authors: Wang
authors: Key Laboratory of Fiber Optic Sensing Technology and Information Processing, School of Information Engineering, Wuhan University of Technology, Wuhan, China.
authors: Quan
authors: Q
authors: Liu
authors: Key Laboratory of Fiber Optic Sensing Technology and Information Processing, School of Information Engineering, Wuhan University of Technology, Wuhan, China.
authors: Jie
authors: J
authors: Yang
mesh_terms: D007449:Investments / Q000191:economics* / Q000639:trends; D018803:Models, Economic