复杂信息环境下投资者学习行为对其收益影响分析-管理科学与工程专业论文.docxVIP

ABSTRACT With the development of information technology, the interactive way based on information and the interaction network which individual investors among stock market faced is growing complexity. The information may come from the investors’ own experience in analyzing the market environment, or from observing the behavior of other investors, and communicating with others. By sharing and exchanging experiences, investors with poor ability tend to learn the better investors investment strategy, while the investors with high ability will improve their investment capacity based on historical data and relevant theoretical knowledge analysis. So learning behavior of investors will have a profound impact on the stock market as well as the macroeconomic, and how the investors’ learning behavior impact on the stock market will have a very useful practical significance. Based on the heterogeneity investors, combined with information asymmetry phenomenon and accumulation phenomenon of trust in stock market, we construct an information diffusion network by considering the investors as the nodes, considering the information dissemination approach as edge and the construct preferential attachment to simulate the investors’ learning process. By analyzing the structure of the information diffusion networks, we learn about the learning styles and learning time’s impact on investors’ returns, this will lead to a conclusion that which learning style investors should take and its impact on investor returns. Simulations and analysis this model, the result shows that learning cycles influence the distribution and transition of investor yield. While the structure of the network keeps constant, the increase of learning cycles will make the investor yield more decentralization so that the yield will transfer from the hub nodes to the normal nodes; the change of the scale of the network and the trust threshold will course the change of the structure of the network, by which will influen