Moving average reversion strategy for on-line portfolio selection

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	Moving average reversion strategy for on-line portfolio selection
	Li, Bin1 ; Hoi, Steven C. H.2; Sahoo, Doyen 2; Liu, Zhi-Yong3
发表期刊	ARTIFICIAL INTELLIGENCE
	2015-05-01
卷号	222 页码:104-123
文章类型	Article
摘要	On-line portfolio selection, a fundamental problem in computational finance, has attracted increasing interest from artificial intelligence and machine learning communities in recent years. Empirical evidence shows that stock's high and low prices are temporary and stock prices are likely to follow the mean reversion phenomenon. While existing mean reversion strategies are shown to achieve good empirical performance on many real datasets, they often make the single-period mean reversion assumption, which is not always satisfied, leading to poor performance in certain real datasets. To overcome this limitation, this article proposes a multiple-period mean reversion, or so-called "Moving Average Reversion" (MAR), and a new on-line portfolio selection strategy named "On-Line Moving Average Reversion" (OLMAR), which exploits MAR via efficient and scalable online machine learning techniques. From our empirical results on real markets, we found that OLMAR can overcome the drawbacks of existing mean reversion algorithms and achieve significantly better results, especially on the datasets where existing mean reversion algorithms failed. In addition to its superior empirical performance, OLMAR also runs extremely fast, further supporting its practical applicability to a wide range of applications. Finally, we have made all the datasets and source codes of this work publicly available at our, project website: http://OLPS.stevenhoi.org/. (C) 2015 Elsevier B.V. All rights reserved.
关键词	Portfolio Selection On-line Learning Mean Reversion Moving Average Reversion
WOS标题词	Science & Technology ; Technology
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000351791900004
引用统计	被引频次：79[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/8123
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
作者单位	1.Wuhan Univ, Econ & Management Sch, Wuhan 430072, Peoples R China 2.Singapore Management Univ, Sch Informat Syst, Singapore 178902, Singapore 3.Chinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Li, Bin,Hoi, Steven C. H.,Sahoo, Doyen,et al. Moving average reversion strategy for on-line portfolio selection[J]. ARTIFICIAL INTELLIGENCE,2015,222:104-123.
APA	Li, Bin,Hoi, Steven C. H.,Sahoo, Doyen,&Liu, Zhi-Yong.(2015).Moving average reversion strategy for on-line portfolio selection.ARTIFICIAL INTELLIGENCE,222,104-123.
MLA	Li, Bin,et al."Moving average reversion strategy for on-line portfolio selection".ARTIFICIAL INTELLIGENCE 222(2015):104-123.