Stock market as temporal network

Longfeng Zhao, Gang-Jin Wang, Mingang Wang, Weiqi Bao, Wei Li and H. Eugene Stanley

Physica A: Statistical Mechanics and its Applications, 2018, vol. 506, issue C, 1104-1112

Abstract: 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.

Keywords: Stock market; Correlation-based network; Temporal network; Portfolio optimization (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (30)

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Working Paper: Stock market as temporal network (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:506:y:2018:i:c:p:1104-1112

DOI: 10.1016/j.physa.2018.05.039

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