基于模糊信息分配理论的短期股价涨跌模式识别

Pattern recognition model of short-term share price fluctuation based on fuzzy information distribution theory

基于分形市场假说的股价并不完全反映所有信息的观点,认为历史股价信息是不完备的群体型模糊信息,提出了线性信息分配条件下的信息守恒定理,建立了基于模糊信息分配理论的短期股价涨跌预测的模糊模式识别模型,通过对上证综合指数日线数据的短期预测,表明该模型具有能够动态捕捉股价短期分布特征、有效描述股价序列内蕴的短期非线性因果关系,进而具有较高的股价涨跌识别精度,并提出了金融市场收益率可能性分布的概念.

According to the fractal market hypothesis, the current share prices do not absorb all the historical market information, we think that the price series information is a sort of grouped incomplete fuzzy information. The theorem that the information volume is a constant under the linear information distribution function is proved. We set up a pattern recognition model, based on the fuzzy information distribution theory, to predict the direction of fluctuation of Shanghai stock market composite index day time series. By empirical analysis it is found that this model is very effective and can also give the possible distribution of logarithmic stock return. Finally the framework of decision support system for pattern recognition of short-term share price fluctuation is put forth.