Biclustering Learning of Trading Rules

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	Biclustering Learning of Trading Rules
	Huang, Qinghua 1; Wang, Ting 1; Tao, Dacheng2 ; Li, Xuelong3
刊名	ieee transactions on cybernetics
	2015-10-01
卷号	45 期号:10 页码:2287-2298
关键词	Biclustering machine learning technical analysis trading rules
英文摘要	technical analysis with numerous indicators and patterns has been regarded as important evidence for making trading decisions in financial markets. however, it is extremely difficult for investors to find useful trading rules based on numerous technical indicators. this paper innovatively proposes the use of biclustering mining to discover effective technical trading patterns that contain a combination of indicators from historical financial data series. this is the first attempt to use biclustering algorithm on trading data. the mined patterns are regarded as trading rules and can be classified as three trading actions (i.e., the buy, the sell, and no-action signals) with respect to the maximum support. a modified k nearest neighborhood (k-nn) method is applied to classification of trading days in the testing period. the proposed method [called biclustering algorithm and the k nearest neighbor (bic-k-nn)] was implemented on four historical datasets and the average performance was compared with the conventional buy-and-hold strategy and three previously reported intelligent trading systems. experimental results demonstrate that the proposed trading system outperforms its counterparts and will be useful for investment in various financial markets.
WOS标题词	science & technology ; technology
类目[WOS]	computer science, artificial intelligence ; computer science, cybernetics
研究领域[WOS]	computer science
关键词[WOS]	technical analysis ; feature-selection ; neural-network ; stock markets ; discovery ; system ; classification ; representation ; matrix
收录类别	SCI ; SSCI ; EI
语种	英语
WOS记录号	WOS:000361751900023
公开日期	2015-11-03
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/25400]
专题	西安光学精密机械研究所_光学影像学习与分析中心
作者单位	1.S China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510641, Guangdong, Peoples R China 2.Univ Technol Sydney, Ctr Quantum Computat & Informat Syst, Fac Engn & Informat Technol, Ultimo, NSW 2007, Australia 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr Opt Imagery Anal & Learning, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China
推荐引用方式 GB/T 7714	Huang, Qinghua,Wang, Ting,Tao, Dacheng,et al. Biclustering Learning of Trading Rules[J]. ieee transactions on cybernetics,2015,45(10):2287-2298.
APA	Huang, Qinghua,Wang, Ting,Tao, Dacheng,&Li, Xuelong.(2015).Biclustering Learning of Trading Rules.ieee transactions on cybernetics,45(10),2287-2298.
MLA	Huang, Qinghua,et al."Biclustering Learning of Trading Rules".ieee transactions on cybernetics 45.10(2015):2287-2298.