Study On The Methods Of Modeling An Artificial Stock Market And Experimenting And Controlling Chaos

Most of researchers have accepted that financial market is essentially a huge open and complicated system. Chaos theory is one of the three complexity theories. Chaos theory even substituted complexity theory when Santa Fe Institution (SFI) was established. Although many researchers knew that there were lots of limits to using methods based on traditional finance theories and directed by reductionism or holism to resolve complexity questions in financial markets. They still build models from up to down and through deductive approaches and they tried to explain why financial markets will be chaotic by analyzing these models. But these models ignore relations between factors and their evolution process in financial markets, so they are incapable to discover essential rules hidden in chaotic dynamical characteristics. Hence neither the government nor investors can obtain any exercisable and valuable revelation from these studies.Both the financial market and the ecosystem are complex adaptive systems. Investors, as agents in the market, have to learn to adapt themselves to changes of the market and avoid to be washed out. The financial market is a complicated whole and its chaotic dynamical characteristics and its function rely on the interaction effects between different parts of the system. With the rapid development of computer technology, it is possible to emulate a financial market. This artificial financial market can exhibit rich chaotic dynamical characteristics that emerge with the interaction between parts of the financial market. At the same time it demonstrates how investors'knowledge of the financial market evolutes. The artificial financial market includes necessary parameters that are interdependent to implement functions. In this way we can study mechanism of a financial market to come into being chaos and find out key factors that lead to chaos. This computational experimental finance will provide a valuable theory support and a feasible method for finance researchers and risk managers. Setting about complex adaptive theory of system science, this paper builds computer models of Chinese financial market from down to up and through induction approaches. And then we study chaotic dynamical characteristics and intrinsic rules of Chinese financial market by experimenting.Firstly, we introduce computational finance and chaos theories, and analyze limitations of traditional modeling and controlling methods. This paper analyzes the complex adaptive theory, the intelligent artificial stock market method based and the chaos controlling method based on an artificial stock market. And take the Duffing-Holms model for example, we point out the limitations of mathematic chaotic models and controlling methods applying in financial markets. Besides, we find a order parameter of the Duffing-Holms model——outside force frequency parameter, and present existence conditions of period solution of the model.Secondly, we analyze roundly the chaotic dynamical characteristics of Chinese stock market. We have tested the chaotic characteristics by using correlation dimension test, Lyapunov exponent test, BDS test and close return (CR) test. The conclusion indicates that Chinese stock market is chaotic. This conclusion is a precondition to find intrinsic factors of chaotic dynamical characteristics of Chinese stock market in the following text.Thirdly, we create an artificial stock market with Chinese characteristics. Computer models are built in light of characteristics of investors'types, pricing mechanism, dividend and policies of Chinese stock markets. We simulate Chinese stock market with these models and genetic arithmetic. Price time series and return time series of the artificial stock market have been gained.With foregoing work, we test chaotic dynamical characteristics of the artificial stock market and find that it possesses dynamical characteristics just as real Chinese stock market. Through experimental methods, we study the key factors that lead to chaos of the stock market and discover that policy factors, noise traders, the evolution speed of traders'knowledge, the number of forecasting rules in investors'forecasting rules sets and liquidity are the order parameters of a stock market. Changes of these order parameters will cause the change of chaotic dynamical characteristics of a stock market. We also raise some suggestions to contol chaos.Finally, this paper demonstrates different evolvement trends of price series emerged from the stock market respectively in a close artificial stock market and an open artificial stock market. This paper also points out the wealth accumulation evolvement paths of different traders'respectively in these two kinds of markets. In this part, we find out key factors that determine the amount of traders'wealth. Besides, we find that dividend can't transfer information of listed companies in double auction markets. These conclusions provide scientific suggestions for traders to win more wealth and invest reasonably.