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An Application of Complex Networks: Researches on Stocks Strong Correlation

机译:复杂网络的应用:股票强相关性研究

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In order to explore correlation characteristics among stocks, this article models complex network for 101 stocks in real estate sector of China Stock Market. In the model, nodes are stocks, and weighted edges are correlation coefficients of logarithm stocks returns in recently 17 years. We compute the topology parameters, and find that the network is free-scale, nodes degree distribution P(s)~|s|-δ with δ∈(0.8,1.6)for different threshold of correlation coefficients. Average cluster coefficient is 0.53. We also measure centralities of networks, seek for subgroups, and divide network into partitions. We find node 000592 and 601588 with high centrality, which influence entirety network greatly. The research shows that the method of complex network is effectual for revealing the emergence in stock markets.
机译:为了探究股票之间的相关性,本文对中国股票市场房地产行业中101只股票的复杂网络进行了建模。在模型中,节点是股票,加权边是最近17年的对数股票收益率的相关系数。通过计算拓扑参数,发现网络是自由尺度的,节点度分布P(s)〜| s |-δ为δ∈(0.8,1.6),相关系数的阈值不同。平均聚类系数为0.53。我们还测量网络的中心性,寻找子组,并将网络划分为多个分区。我们发现节点000592和601588具有较高的集中度,这对整个网络有很大的影响。研究表明,复杂网络方法对于揭示股票市场的出现是有效的。

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