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Financial time series pattern matching with extended UCR Suite and Support Vector Machine
Xueyuan Gong; Yain-Whar Si; Simon Fong; Robert P. Biuk-Aghai
2016-08-15
Source PublicationExpert Systems with Applications
ISSN0957-4174
Volume55Pages:284-296
Abstract

Chart patterns are frequently used by financial analysts for predicting price trends in stock markets. Identifying chart patterns from historical price data can be regarded as a subsequence pattern-matching problem in financial time series data mining. A two-phase method is commonly used for subsequence pattern-matching, which includes segmentation of the time series and similarity calculation between subsequences and the template patterns. In this paper, we propose a novel approach for locating chart patterns in financial time series. In this approach, we extend the subsequence search algorithm UCR Suite with a Support Vector Machine (SVM) to train a classifier for chart pattern-matching. The experimental results show that our approach has achieved significant improvement over other methods in terms of speed and accuracy.

KeywordFinancial Time Series Perceptually Important Points Subsequence Matching Support Vector Machine Ucr Suite
DOIhttps://doi.org/10.1016/j.eswa.2016.02.017
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering ; Operations Research & Management Science
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS IDWOS:000374811000022
PublisherPERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
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被引频次[WOS]:10   [WOS记录]     [WOS相关记录]
Document TypeJournal article
专题DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorXueyuan Gong; Yain-Whar Si; Simon Fong; Robert P. Biuk-Aghai
AffiliationDepartment of Computer and Information Science, University of Macau, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
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Xueyuan Gong,Yain-Whar Si,Simon Fong,et al. Financial time series pattern matching with extended UCR Suite and Support Vector Machine[J]. Expert Systems with Applications,2016,55:284-296.
APA Xueyuan Gong,Yain-Whar Si,Simon Fong,&Robert P. Biuk-Aghai.(2016).Financial time series pattern matching with extended UCR Suite and Support Vector Machine.Expert Systems with Applications,55,284-296.
MLA Xueyuan Gong,et al."Financial time series pattern matching with extended UCR Suite and Support Vector Machine".Expert Systems with Applications 55(2016):284-296.
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