Information interaction, behavioral synchronization and asset market volatility

Abstract

This paper focuses on the synchronization of trading behavior caused by interactions among traders. The study begins with an agent-based model in which most agents make investment decisions based on three types of information (neighbor, public and private information) according to their heterogeneous personal preferences. Considering the influence of the social relationship network in reality, traders in our model are connected by a complex network. We use four different types of networks. The simulated results of this model reproduce several stylized facts about the asset market. Simulated results show that when preference of traders for neighbor information increases, the level of trust among traders will gradually increase and then there will be a “leap” at a certain point. The mutual trust among traders is achieved through coupling effect in the network. Moreover, with the frequent synchronization of traders’ behavior, extreme phenomena in financial markets will emerge. In addition, our numerical simulations show that when the average degree of network is higher, behavioral synchronization will emerge at a lower level of dependence on neighbor information. The degree distribution of the network will also have a significant influence on the convergence processes of behavioral synchronization. The more heterogeneous the degree distribution is, the easier the behavioral synchronization process will occur. In our simulations, the mode of agent behavior expectation will also enhance the effect of network structure to behavioral synchronization. Finally, this paper affirms the important role of public information and learning mechanism (expectation formation mode) in the process of behavioral synchronization.