Article ID Journal Published Year Pages File Type
7375162 Physica A: Statistical Mechanics and its Applications 2018 9 Pages PDF
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.
Related Topics
Physical Sciences and Engineering Mathematics Mathematical Physics
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