Genetic Network Programming for Artificial Stock Market

摘要：

Combined with the idea of Austrian school of economics, this paper proposes a new multi-agent model for artificial stock market based on Genetic Network Programming. It focuses on applying the GNP approach to emulate investment behavior of agents and evolve their trading rules. Simultaneously, this model enhances the heterogeneity of agents, and searches for an optimal combination of parameter values based on GA. Simulation results confirm the effectiveness of this GNP-ASM model through comparison with empirical statistics.

作者: Yang Cheng Sun Shixin Xie Zhilong

作者单位: School of Computer Science and Engineering University of Electronic Science and Technology of China School of Electronical Commerce Southwestern University of Finance and Economics Chengdu, P.R. China

会议类型: 国际会议

会议名称: 2006 International Conference on Communications,Circuits and Systems(第四届国际通信、电路与系统学术会议)

会议地点: 广西桂林

会议语种:英文

页码: 2079-2083

在线出版日期: 2006-06-25（万方平台首次上网日期，不代表论文的发表时间）