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Moving average reversion strategy for on-line portfolio selection | |
Li, Bin1; Hoi, Steven C. H.2; Sahoo, Doyen2; 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 | |
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. |
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