An Agent-Based Model of Artificial Stock Market by Using GNP
基于GNP的多Agent人工股市模型

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