论文部分内容阅读
在交易过程中,作为智能A gen t的交易者不但学习他人的交易策略,而且会“创新”性地提出自己的交易策略,从而在引发股票市场上不同程度的波动与羊群行为。本文首先将交易者与股票的“多对多”关系等价转换为“一对多”关系,构建了由股票和交易者组成的二分网络市场模型,并给出了交易与定价规则;然后,利用计算实验的方法对模型进行仿真实验,得到了与真实股价相似的时间序列以及不同“创新”概率下的持股分布;通过理论推导,我们发现了三种不同的持股分布:具有指数截断的幂律分布、二项分布和脉冲分布。最后,给出了研究结论与启示。将计算实验与复杂网络应用于行为金融研究具有较强的理论价值,同时对于投资者和监管方来说都有一定的借鉴和参考意义。
In the course of the transaction, a trader who is a smart A gen t not only learns the trading strategies of others, but also “innovates” his own trading strategies, thereby triggering different degrees of volatility and herding in the stock market. This paper first transforms the “many-to-many ” relationship between traders and stocks into “one-to-many ” relationship, constructs a dichotomized network market model composed of stocks and traders and gives the trade and pricing Then we use the method of calculation experiment to simulate the model and obtain the time series similar to the real stock price and the distribution of shares under different “innovation” probabilities. According to the theoretical deduction, we find three different models Unit Distribution: Power-law distribution, binomial distribution and pulse distribution with exponential truncation. Finally, the research conclusions and enlightenments are given. It has strong theoretical value to apply computational experiments and complex networks to behavioral finance research, meanwhile, it has some reference and reference significance for investors and regulators.