Abstract—this paper made some modifications on traditional artificial stock market. It put forward traders’ adaptive learning mechanism, enabling traders to enhance their adaptability to new stock environment by continuous learning. Furthermore, the paper started with external reasons and brought in macrocosmic analysis model, making the artificial stock market closer to the real one. At the same time, validating the characteristics of changes in stock prices, we found they meet EMH basically and the returns took on obvious heavy tail distributions. One stock was selected to be stimulated and forecasted in our artificial stock market, which gained satisfying results.
Index Terms—Artificial stock market; forecast stimulation; heavy tail distributions; macroscopic model.
F. A. Author is with the Shanghai university of finance& economics
phone:+86-15216774000; e-mail: email@example.com
F.B. Author is with the Shanghai Shanghai university of finance& economics e-mail: ZhangPeng724@gmail.com
Cite: Wang haiqi, Zhang Peng and Wu lanjie, "A Joint Model of Macro Factors and Agent Based Structure," International Journal of Trade, Economics and Finance vol. 1, no. 3, pp. 315-319, 2010.