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A New Approach for Stock Price Analysis and Prediction Based on SSA and SVM
Xiao, Jihong1,2; Zhu, Xuehong1,2; Huang, Chuangxia3; Yang, Xiaoguang4; Wen, Fenghua1,5,6; Zhong, Meirui1,2
2019
Source PublicationINTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
ISSN0219-6220
Volume18Issue:1Pages:287-310
AbstractStock price exhibits distinct features during different time scales due to the effects of complex factors. Analyzing these features can help delineate the mechanisms that determine the stock price and enhance the prediction accuracy of the stock price. By using singular spectrum analysis (SSA), this paper first decomposes the original price series into a trend component, a market fluctuation component and a noise component to analyze the stock price. The economic meanings of the three components are identified as a long-term trend, effects of significant events and short-term fluctuations caused by noise in the market. Then, to take into account the features of the above three components to the stock price prediction, a novel combined model that integrates SSA and support vector machine (SVM) (e.g., SSA-SVM) is proposed. Compared with SVM, adaptive network-based fuzzy inference system (ANFIS), ensemble empirical mode decomposition-ANFIS (EEMD-ANFIS), EEMD-SVM and SSA-ANFIS, SSA-SVM demonstrates the best prediction performance based on four criteria, indicating that the proposed model is a promising approach for stock price prediction.
KeywordStock price singular spectrum analysis support vector machine combined model
DOI10.1142/S021962201841002X
Language英语
Funding ProjectNational Natural Science Foundation of China[71371195] ; National Natural Science Foundation of China[71431008] ; National Natural Science Foundation of China[71471020] ; National Natural Science Foundation of China[71573282]
WOS Research AreaComputer Science ; Operations Research & Management Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications ; Operations Research & Management Science
WOS IDWOS:000457238100010
PublisherWORLD SCIENTIFIC PUBL CO PTE LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/32454
Collection系统科学研究所
Affiliation1.Cent S Univ, Sch Business, Changsha 410083, Hunan, Peoples R China
2.Inst Met Resources Strategy, Changsha 410083, Hunan, Peoples R China
3.Changsha Univ Sci & Technol, Coll Math & Comp Sci, Changsha 410004, Hunan, Peoples R China
4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
5.Univ Windsor, Fac Engn, Supply Chain & Logist Optimizat Res Ctr, Windsor, ON, Canada
6.Univ Essex, Ctr Computat Finance & Econ Agents, Colchester CO4 3SQ, Essex, England
Recommended Citation
GB/T 7714
Xiao, Jihong,Zhu, Xuehong,Huang, Chuangxia,et al. A New Approach for Stock Price Analysis and Prediction Based on SSA and SVM[J]. INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING,2019,18(1):287-310.
APA Xiao, Jihong,Zhu, Xuehong,Huang, Chuangxia,Yang, Xiaoguang,Wen, Fenghua,&Zhong, Meirui.(2019).A New Approach for Stock Price Analysis and Prediction Based on SSA and SVM.INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING,18(1),287-310.
MLA Xiao, Jihong,et al."A New Approach for Stock Price Analysis and Prediction Based on SSA and SVM".INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 18.1(2019):287-310.
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