以上证指数为例,运用MF-DFA方法对其进行多重分形消除趋势波动分析。结果发现该时序在整个标度范围上存在交叉突变现象,其交叉突变点将整个时间标度分为两个部分,每一部分具有不同的多重分形特征及标度指数。进一步地,对每一部分多重分形特征成因进行分析,发现股票市场的多重分形特征是由波动的相关性及厚尾的概率分布共同作用的,其中收益序列的波动相关性是形成多重分形特征的主要原因。最后,提出股票市场监管的几点启示。
Using MF-DFA method, an empirical research on the Shanghai stock price index is made. It is found that these time series exit crossover phenomenon. A crossover point divides the whole time scale into two different scale domains. There are different multifractal characteristics and scale exponents for these two domains. Furthermore, the sources of multifractality under different scale domains were analyzed. It is found that there are two different types of sources for the multi-fractality in time series, namely, fat-tailed probability distributions and fluctuation correlations. Most muhifraetality of the data is due to fluctuation correlations. Finally, some enlightenments are advanced.