Simulation And Study On Trading Strategies In Stock Market

The appearance of Behavioral Finance and Agent-based Computational Finance provides new thoughts and methodologies for the research on the stock market. This article makes full use of theories in Behavioral Finance and Agent-based Computational Finance, trying to establish an artificial stock market on the Netlogo platform. The artificial stock market is driven by the special events and rules for market clearing and prices forming are determined by supply and demand of assets. There are two assets in the markets and several traders. Each trader will randomly choose his or her initial trading strategy. There are four kinds of strategies available to choose, which are momentum strategy, contrarian strategy, noise strategy as well as rational strategy. We aim to observe the trading behaviors of four kinds of traders and analyze the outcomes of strategy transformation in order to verify the existence of these different kinds of traders.The research shows that the number of traders in momentum strategies has a reverse changing tendency with that of traders in contrarian strategies. The number of traders in noise traders and rational traders tend to be stable and will not be driven out of the market. Heard behavior plays a key role in affecting the amount of noise traders. Traders in momentum strategy or traders in contrarian strategy will won the superior earnings; however, the volatility of profit is extremely large, which means a high investment risk for traders. As to the profit of the other traders, the noise traders will defeat the rational traders and win a good profit with small volatility. This can further verify that the noise traders will not be driven out of the market.