The Research On Strategy Evolution In Stock Market Based On Cellular Automata

The traditional finance approach focuses on the overall grasp, which tends to ignore the individual behavior, especially the ignorance of interaction between the individual and the environment. As a typical complex adaptive system, financial market has features of multi-internal structure, multi-participating and complex elements, multi-variable relations, multi-internal causality and so on. Its separability (lag) on time or space and strong coupling determined that the linear view of classical financial theory and equilibrium analysis can not fully reveal the laws of the market. On this basis, the design of psychological emotional paradigm of investor in artificial stock market and the portray of wisdom degree have increasingly became hot issues, as a powerful tool to explore the complexity and complex systems, cellular automata model is being widely used in the research of stockmarket.In this dissertation, the evolutionary of investors’strategy is studied, a new model of investment strategy evolution based on cellular automata combined with the framework of traditional asset pricing model. As with the emotional paradigm of investors’psychology, its evolution and intelligence level, the innovative improvements are given by this article.Firstly, review about some stock pricing model based on complex adaptive systems is made by this dissertation, their analysis especially the design of evolutionary mechanism and the portray of wisdom degree, defects in the current research is introduced, the basis of the topics is illustrated.Secondly, basing on the classic asset pricing model and cellular automata theory,(1)Investors’strategy evolution method of "single strategy" and "mixed strategy" are designed;(2)Analysis of model’s stability and bifurcation is made by using nonlinear dynamics theory;(3)Utility function of strategy evolution and cellular genetic algorithm are introduced in cellular automata-based strategy evolution, investors’level of intelligence is improved.Thirdly, matlab is used in simulating of the upper design and analysis, experimental results are compared horizontally and vertically, influence of "single strategy" and "mixed strategy" to price, profit, proportion of strategy selection and other market characteristics are obtained.Finally, in the empirical part, the applicability of the model is further elaborated combined with the actual state and the investing public mental emotional paradigm of the real stock market.After the completion of the above four tasks, it can be included that:(1) Conformity may not necessarily result in abnormal fluctuations in market prices;(2) Technical investment strategy could easily lead to price volatility, but investors’ conversion between different strategy is also contribute to the stock market volatility;(3) The introduction of utility function of strategy evolution and cellular genetic algorithm not only guarantee the profit but also maintain the stability of the market;(4) Deliberately learning between retails will not necessarily reap excessive profit, institutions that can manipulate the stock price and reap the excessive profit are the ones who successful grasp the "mass psychology".