A network analysis of the Chinese stock market

Wei-Qiang Huang, Xin-Tian Zhuang and Shuang Yao

Physica A: Statistical Mechanics and its Applications, 2009, vol. 388, issue 14, 2956-2964

Abstract: In many practical important cases, a massive dataset can be represented as a very large network with certain attributes associated with its vertices and edges. Stock markets generate huge amounts of data, which can be use for constructing the network reflecting the market’s behavior. In this paper, we use a threshold method to construct China’s stock correlation network and then study the network’s structural properties and topological stability. We conduct a statistical analysis of this network and show that it follows a power-law model. We also detect components, cliques and independent sets in this network. These analyses allows one to apply a new data mining technique of classifying financial instruments based on stock price data, which provides a deeper insight into the internal structure of the stock market. Moreover, we test the topological stability of this network and find that it displays a topological robustness against random vertex failures, but it is also fragile to intentional attacks. Such a network stability property would be also useful for portfolio investment and risk management.

Keywords: Stock correlation network; Stock price fluctuations; Complex network theory; Topology structure; Scale-free degree distribution; Clustering coefficient; Component; Clique; Independent set; Topological stability; Portfolio investment (search for similar items in EconPapers)
Date: 2009
References: View complete reference list from CitEc
Citations: View citations in EconPapers (97)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:388:y:2009:i:14:p:2956-2964

DOI: 10.1016/j.physa.2009.03.028

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