摘要
我国股票市场波动表现出随时间变化的动态特征。文章采用多重消除趋势波动分析法(MFDFA),对沪深股市四个主要指数的日波动率时间序列进行了分析。结果表明,沪深股市四个主要指数的日波动率时间序列均表现出多重分形特征,且上证指数和中证500指数日波动率序列相对于其他两个指数日波动率序列表现出更强的多重分形特征。各指数日波动率时间序列的多重分形特征均是自身的长程相关性和波动的厚尾分布共同作用的结果,且波动的厚尾分布对原始序列的多重分形特征的影响比长程相关性大。
The volatility of China’s stock market shows the dynamic characteristics of changing with time.This paper analyzes the daily volatility of the four main indexes in Shanghai and Shenzhen stock market by use of multi-fractal detrended fluctuation analysis(MF-DFA).The results show that the time series of daily volatility of the main indexes of Shanghai and Shenzhen stock market exhibit multi-fractal properties,and that compared with the other two indices,the daily volatility sequences of SSE index and China Securities 500 index show stronger multi-fractal characteristics among the four indices;the multi-fractal properties of the volatility time series of each index are caused by their own long-range correlation and the non-Gaussian thick-tailed distributions.In particular,the latter plays a more vital role in the multi-fractal properties of the four volatility series than the former.
作者
韩晨宇
王一鸣
Han Chenyu;Wang Yiming(School of Economics,Peking University,Beijing 100871,China)
出处
《统计与决策》
CSSCI
北大核心
2020年第1期136-140,共5页
Statistics & Decision