股市演化的遗传元胞自动机模型

Genetic Cellular Automata Model of Evolving Stock Market

以复杂性科学的理论方法为指导,运用元胞自动机、遗传算法、系统仿真、分类器系统等研究工具,结合投资分析技术,在形成演化规则库的基础上,构建了股市系统演化的遗传元胞自动机模型。其中,分类器系统被用来学习演化模型的参数,它使演化市场的复杂性特征充分逼近现实市场。通过对兖州煤业的实证分析,表明该演化模型可以模拟现实市场的复杂性,可以通过具有学习功能的演化模型进一步分析股票市场,为股市的监管和调控提供依据。

Guided by the theory of complexity sciences,this paper formulates a genetic cellular automa model of stock market using several research tools including cellular automata,genetic algorithm and simulation,and techniques of investment analysis is involved as well.During the modeling,the reservoir of evolving rules is used to conduct the stock market simulation,whereas classifier system is used to training the model′s parameters so that the evolving model is as close to real market as possible.The application to YZMY stock market implies that the intelligent evolving model can simulate the real market on complexity characteristics,and can provide scientific basis for stock market administration and regulation after further studies.