Study Of The Social Learning Effect Of Heterogeneous Investors In The Artificial Stock Market

It is often assumed that investors are completely rational and homogeneous under traditional financial theory. But more and more anomalies in security market doubt the assumption that investors are perfect rationality. The investor's heterogeneity and bounded rationality is an indisputable fact. Bounded rationality and dynamic learning of investors the stock market change adaptation will often produce a lot of impact.Financial system is a complex adaptive system. There are a number of different heterogeneous investors in the stock market. The habit of thinking, subjective preferences and behavior way of investors are different. And these features of investors are constantly changing. In this ongoing process of continuous interactive learning and learning by experience, the individual in stock market changes his own structure and behavior. Underlying interaction of each individual emerged new structures and more complex behavior in the overall level. This article examines the impact of social learning in the financial market based on this idea of complex adaptive system.With the development of computer technology and finance theory agent-based computational finance becomes a new research field of finance. It is based on theories including the finance market microstructure, behavioral finance and complex systems theory. Study on financial issues makes use of emergence methods of complex systems. In this paper, a new artificial stock market (ASM) in which investors have the ability of social learning is built, based on Santa Fe Institute artificial stock market. In this artificial stock market, the heterogeneous investors evolve and adapt to the environment through social learning. Public rule set is composed of the transaction rule of each investor. And the public rule set evolves by genetic algorithm. This paper analyzes and researches the impact of social learning in the different learning speeds on financial market and micro-level investor. In this paper the following conclusions are obtained. Social learning is one of the reasons of the stock price volatility. Stock price in the artificial stock market can't converge to the theoretical price under the efficient market hypothesis. And the artificial stock market simulates some typical characteristics of the real stock market. These typical characteristics include the spike and fat tail of stock price, and volatility clustering of stock price. And stock holdings and wealth levels of investors are analyzed in the micro-level.