基于少数者博弈模型的人工股票市场仿真研究
首发时间:2019-11-08
摘要:依照基于Ag基于少数者博弈模型的人工股票市场仿真研究ent的计算实验金融学的研究框架,在对人工股票市场和少数者博弈模型进行分析后,构建了一个应用于股票市场的演化少数者博弈(SW-EMG)模型,该模型中包括三类具有行为模仿机制的投资方式不同的投资者,投资者之间可以通过股票价格变动完成信息交换。借助该模型进行计算机仿真实验,得到并分析了股票价格时间序列的仿真数据,研究得出:股票市场监管者不应片面地抹除市场中的噪音投资者,应把重点转移到如何有效控制各类投资者的比例上;监管者还应设置相应的等级考试,对投资水平不同的投资者,设定不同的继续教育政策,将各投资者能够采取的策略数控制在一定范围内;同时,研究还得出T+0交易机制显著优于T+1交易机制的结论。
关键词: 人工股票市场 演化少数者博弈模型 行为模仿机制 有效性
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Artificial Stock Market Simulation Based on Minority Game Model
Abstract:According to the research framework of Agent-based computational experimental finance, we have formed an evolutionary minority game (SW-EMG) applied to the stock market after analyzing the artificial stock market and the minority game mode. There are three types of investors with different investment methods and behavioral imitation mechanism in this model. Investors can complete information exchange through stock price changes. We have obtained and analyzed the simulation data of stock price time series by using the model to carry out computer simulation experiments. It is concluded that stock market regulators should not unilaterally erase noise investors in the market, and should focus on how to effectively control each Proportion of class investors. Regulators should also set up corresponding grade examinations to set different continuing education policies for investors with different investment skills, Artificial Stock Market Simulation Based on Minority Game Modeland control the number of strategies that each investor can adopt within a certain range. At the same time, our study also concluded that the T+0 trading mechanism is significantly better than the T+1 trading mechanism.
Keywords: Artificial stock market evolutionary minority game model behavioral imitation mechanism effectiveness
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