基于节点拓扑特征的中国基金公司共持网络持股行为波动相关性

选取2003—2012年期间半年度中国基金公司持上市公司股票份额面板数据为样本数据,以基金公司为节点,以同一时刻共持同一家上市公司股票关系为边,以同一时刻共持的上市公司数量为权重,构建中国基金公司共持关系结构等价加权网络(简称共持网络).结合统计物理学等方法,分析了共持网络的拓扑结构稳定性及具有不同拓扑特征值的节点随时间演变过程中与共持网络中三类节点集合持股行为波动相关性.三类节点集合分别为t-1时刻基于某一股票形成的共持关系完全连通子图节点集合(第一类节点集合)、t-1时刻共持网络中非完全连通子图的节点集合(第二类节点集合)、t时刻新进入共持网络的节点集合(第三类节点集合).分析结果显示:1)节点与第二类节点集合持股行为波动呈正相关,且相关系数随着节点集聚系数的增强而增大;2)只有当节点的度和点强度值较高时,节点与第一类和第二类节点集合的持股行为呈正相关;3)不同拓扑特征条件下的节点与第三类节点集合的持股行为均不存在波动相关性.本文提供了一个研究持股行为相关性的新思路,并为进一步研究股票市场结构等价网络及节点重要性差异提供了基础.

Correlation of the holding behaviour of the holding-based network of Chinese fund management companies based on the node topological characteristics

The data in this paper was collected from the semi-annual reports between 2003 and 2012 which disclosed the Chinese fund management companies' shareholdings in different listed companies. The holdings-based network of Chinese fund management companies is constructed by taking fund management companies as the nodes, the holding of stock of the same listed company at the same period as the edges, and the number of the listed companies holding at the same time as the weight of the edges. Based on the methods such as statistical physics, etc., the stability of the networks at different times is analyzed, and then the correlation of the holding behavior between the nodes with different topological characteristics and three different sets of nodes are calculated and analyzed. Three different sets are the set of nodes in the full graph with a given stock at t-1 (the first type of nodes), the set of nodes in the holing-based network without holding a given stock at t-1 (the second type of nodes), and the set of the new nodes which appear at t (the third type of nodes). The result shows as follows. Firstly, the correlation coefficient of the holding behavior between the node and the second type of nodes rises with the node clustering coefficient increasing; secondly, the node holding behavior is highly correlated with the second type of nodes and with the third type of nodes only when the values of the node average degree and strength are high; finally, the node holding behavior is not related to the third type of nodes at all. This paper propose a new method to study the correlation of stock market, and it is a basis for the further investigation on the structure equivalence network in stock market and also the differences of the importance between the nodes.