标题:Stock market as temporal network
作者:Zhao, Longfeng; Wang, Gang-Jin; Wang, Mingang; Bao, Weiqi; Li, Wei; Stanley, H. Eugene
作者机构:[Zhao, Longfeng; Li, Wei] Cent China Normal Univ, MOE, Key Lab Quark & Lepton Phys, Wuhan 430079, Hubei, Peoples R China.; [Zhao, Longfeng; Li, Wei] 更多
通讯作者:Zhao, Longfeng
通讯作者地址:[Zhao, LF; Li, W]Cent China Normal Univ, MOE, Key Lab Quark & Lepton Phys, Wuhan 430079, Hubei, Peoples R China;[Zhao, LF; Li, W]Cent China Normal Uni 更多
来源:PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
出版年:2018
卷:506
页码:1104-1112
DOI:10.1016/j.physa.2018.05.039
关键词:Stock market; Correlation-based network; Temporal network; Portfolio; optimization
摘要:Financial networks have become extremely useful in characterizing the structures of complex financial systems. Meanwhile, the time evolution property of the stock markets can be described by temporal networks. We utilize the temporal network framework to characterize the time-evolving correlation-based networks of stock markets. The market instability can be detected by the evolution of the topology structure of the financial networks. We then employ the temporal centrality as a portfolio selection tool. Those portfolios, which are composed of peripheral stocks with low temporal centrality scores, have consistently better performance under different portfolio optimization frameworks, suggesting that the temporal centrality measure can be used as new portfolio optimization and risk management tool. Our results reveal the importance of the temporal attributes of the stock markets, which should be taken serious consideration in real life applications. (C) 2018 Elsevier B.V. All rights reserved.
收录类别:EI;SCOPUS;SCIE;SSCI
Scopus被引频次:1
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047272045&doi=10.1016%2fj.physa.2018.05.039&partnerID=40&md5=9d8ee7ea5865f1c3db95ba884598d09f
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