Construction of artificial stock markets using ADG, automatically defined groups

摘要

With the aim of analyzing the mechanism of the stock price change, we construct an artificial stock market composed of multiple agents whose investment strategies are represented by tree-shaped programs. The market is optimized by using a Genetic Programming so that the change of its stock price resembles that of "real" stock market statistically. In order to perform an efficient optimization and to analyze agents' behavior easily, we use ADG; Automatically Defind Groups previously proposed by authors. We show experimentally that complex changes like real market appears in the proposed artificial market.