Agent-based Experimental Study On Trader Structure And Trade Strategy Survivability

This paper, basing complex adaptive system theory and Agent-based model approach, builds an artificial futures market in Netlogo platform. Our goal is to research the relationship between investor structure and the survivability of trade strategy. First of all, the development of system science has been described, especially the theory of complex adaptive system; After that, an detail introduction of multi-agent model method and software platform have been given in chapter three of this paper; In the chapter four, we begin the construction of artificial futures market, including the main two tasks. They are future market trading mechanism and market investors. In the process, comparing the strength of sell order and buy order to determine the transaction price is used, directly. And build three types of investors, including value trader, trend trader and noise trader in the market. Finally, the simulation was run and the change of investor's wealth was observed under the different kinds of investor structure.Some conclusions are draw through simulation: the game of trade process is very complex in the future market. It is hard to say which strategy is absolutely beautiful because it depend your opponent. A lot of interesting facts are found: The market nearly die, that is short of liquidity when there is only one type of investor; value trader play an significant role to stabilizing the market price; however, the trend investor tends to amplify the fluctuation of price; and the trend trader tend to make the price hard to forecast. Although noise traders are very important to the market liquidity, they also bring more volatility to the market; that is harmful to the market stable. The experiment result supports an appreciative routine to development of China future markets, indicating that it is necessary to implement investor education.