Forecasting stock market movement direction with support vector machine

doi:10.1016/j.cor.2004.03.016

	Forecasting stock market movement direction with support vector machine
	Huang, W ; Nakamori, Y ; Wang, SY
刊名	COMPUTERS & OPERATIONS RESEARCH
	2005-10-01
卷号	32 期号:10 页码:2513-2522
关键词	support vector machine forecasting multivariate classification
ISSN号	0305-0548
DOI	10.1016/j.cor.2004.03.016
英文摘要	Support vector machine (SVM) is a very specific type of learning algorithms characterized by the capacity control of the decision function, the use of the kernel functions and the sparsity of the solution. In this paper, we investigate the predictability of financial movement direction with SVM by forecasting the weekly movement direction of NIKKEI 225 index. To evaluate the forecasting ability of SVM, we compare its performance with those of Linear Discriminant Analysis, Quadratic Discriminant Analysis and Elman Backpropagation Neural Networks. The experiment results show that SVM outperforms the other classification methods. Further, we propose a combining model by integrating SVM with the other classification methods. The combining model performs best among all the forecasting methods. (c) 2004 Elsevier Ltd. All rights reserved.
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
语种	英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号	WOS:000228207700003
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/2300]
专题	中国科学院数学与系统科学研究院
通讯作者	Wang, SY
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Beijing 100080, Peoples R China 2.Japan Adv Inst Sci & Technol, Sch Knowledge Sci, Tatsunokuchi, Ishikawa 9231292, Japan
推荐引用方式 GB/T 7714	Huang, W,Nakamori, Y,Wang, SY. Forecasting stock market movement direction with support vector machine[J]. COMPUTERS & OPERATIONS RESEARCH,2005,32(10):2513-2522.
APA	Huang, W,Nakamori, Y,&Wang, SY.(2005).Forecasting stock market movement direction with support vector machine.COMPUTERS & OPERATIONS RESEARCH,32(10),2513-2522.
MLA	Huang, W,et al."Forecasting stock market movement direction with support vector machine".COMPUTERS & OPERATIONS RESEARCH 32.10(2005):2513-2522.