The effect of investment intent on stock market - - an analysis based on cellular automaton

A typical work in the field of complexity in the stock market is the agent-based model for Artificial Stock Market (ASM). This model can be classified as an adaptive nonlinear network. The modeling method based on interactions among agents by cellular automaton (CA) was suggested first by von Neumann and S.Wolfram. In fact, the agent-based model can become the CA model when some assumptions are made, and its final product is a series of computer programs. CA has appeared as an effective tool for simulating a complex system, and has been used widely. From the view point of a complex adaptive system, an economy system includes not only physical elements such as the technical experts, all kinds of behaviors, markets, financial companies and factories, but also the psychological factors which is invisible but interact with the physical elements. In fact, the psychological factors impact the macro-economy behavior and introduce the emergency in finance market. Hence, studies into the investors’ psychology as a key factor for the emergency of the stock market have become a focus problem in the present research of economics. It has been shown that the stock market could collapse in some cases and can show the GARCH behavior, which does not exist in equilibrium theory, that is, the continue turndown aberrance will appear as continue upswing aberrance ending. However, all those results are obtained by the qualitative analysis for the emergence curve, and there is no quantitative index to describe the characteristics of stock market behaviors.