Simulation And Analysis Of Artificial Stock Market Based On Agent

During the1970s, computer science and technology developed fairly fast, especially since the90’s of last century, with the mature computer application technology, Domestic and foreign scholars in the field of finance began to the explore the integration of computer and finance. They try to simulate the reality of financial markets through computer technology, and to reveal the macro-laws of market through the behavior of micro institutional investors, and this lead Agent-based Computational Financial which is a branch of finance to begin. With the continuous deepening of the study, scholars have found that a reasonable and effective classification of Agent and structures, especially an Accurate description of Agent behavior, is the most critical part of the whole study. However, as a basic ASM research the behavioral finance has not been well used. At present, our research on the artificial stock market has not yet considered much about the effect of psychological factors of investors on investment decision-making process, so putting the effect of psychological factors of investors on investment decision-making process into the artificial stock market by using the theory of behavioral finance to simulate a more realistic stock market will be a bold attempt and innovation.On the basis of previous research, the author build a simple artificial stock market and try to promote the analysis and simulation of the entire model through the analysis of the underlying. Firstly, the author divide investors into two categories of institutional investors and individual investors according to the different effects of investors on stock price behavior. In the process of institutional investors modeling, the improved genetic algorithm has been used to innovate the learning process of institutional investors according to the characteristics of the artificial stock market. In addition, prospect theory of behavioral finance has been specially introduced in the modeling of individual investors. The final analysis of the experimental results dynamically represents the impact of bank interest rate adjustments on the stock market and the stock return rate influence on investor behavior.