A network analysis of the Chinese stock market
A network analysis of the Chinese stock market
复制标题
中国股市的网络分析
DOI：
10.1016/j.physa.2009.03.028
复制
发表时间：
2009-07-15
影响因子：
3.3
通讯作者：
Yao, Shuang
中科院分区：
文献类型：
--
作者：
Huang, Wei-Qiang;Zhuang, Xin-Tian;Yao, Shuang
在许多重要的实际情况下，一个庞大的数据集可以被表示为一个非常大的网络，具有与它的顶点和边缘相关的某些属性。股票市场产生大量的数据，这些数据可以用来构建反映市场行为的网络。本文采用阈值法构建了中国股票相关网络，并对网络的结构特性和拓扑稳定性进行了研究。我们对该网络进行了统计分析，并表明它遵循幂律模型。我们还检测了该网络中的分量、派系和独立集。这些分析使人们能够应用一种新的数据挖掘技术，根据股票价格数据对金融工具进行分类，从而更深入地了解股票市场的内部结构。此外，我们测试了该网络的拓扑稳定性，发现它对随机顶点故障具有拓扑鲁棒性，但对故意攻击也很脆弱。这种网络稳定性对证券投资和风险管理也很有用。(C) 2009 Elsevier B.V.版权所有
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. (C) 2009 Elsevier B.V. All rights reserved.