RESEARCH ON FINANCIAL TIME SERIES FORECASTING BASED ON SVM

被引：0

作者：

Yang Yujun ^{[1
,2
,3
]}

Yang Yimei ^{[2
]}

Li Jianping ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Engn & Comp Sci, Chengdu 611731, Sichuan, Peoples R China

[2] Huaihua Univ, Sch Engn & Comp Sci, Huaihua 418008, Peoples R China

[3] Hunan Prov Key Lab Ecol Agr Intelligent Control T, Huaihua 418008, Peoples R China

来源：

2016 13TH INTERNATIONAL COMPUTER CONFERENCE ON WAVELET ACTIVE MEDIA TECHNOLOGY AND INFORMATION PROCESSING (ICCWAMTIP) | 2016年

基金：

中国国家自然科学基金;

关键词：

SVM; Forecasting; Time series; Support vector machine;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：346 / 349

页数：4

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