Research On Individual Investors' Trading Behavior Based On Complex Network

In this paper,I study the theory of complex networks and investment behavior of individual investors.The research of this paper belongs to the field of behavioral finance,but there is a breakthrough in the research method.In this paper,I overcome the above difficulties,using the theory of complex networks,to study the investment behavior of individual investors.In the network,I regard all of the individual traders to simplify as a node,the behavior of the connection between the investors to form the entire network.I study the physical topology of network,such as clustering coefficient,degree distribution,average path length,and try to analyze the whole network with financial theory.At the same time,the minimum spanning tree algorithm is used to simplify the whole network of investors,which is the most valuable even street.According to the similarity of the behavior of the investors,the investors in the network can be divided into different groups,and there are some differences between the groups.After the study,the similarity of the investors in the group is higher,the higher the behavior of the investors is.In order to verify the correctness of this view,for a period of time later,I divided the investors to group again,to explore how many investors have maintained the original investment characteristics.The research significance of this paper is to quickly identify the important nodes in the network,and pay close attention to this node.At the same time,investors can be divided into different categories,and clearly distinguish the different types of investors' behavior.Identify the category of investors,strengthen communication and exchange of non investors in the group.