基于小波协方差的中国股市波动序列相关性的实证分析  

An Empirical Analysis of China's Stock Market Serial Correlation of Volatility Based on Wavelet Covariance

作　　者：吴礼斌[1] 崔岩岩[1] 

机构地区：[1]安徽财经大学统计与应用数学学院,安徽蚌埠233041

出　　处：《统计与信息论坛》2010年第2期100-103,共4页Journal of Statistics and Information

基　　金：安徽省高等学校自然科学研究项目(2005kj310);安徽省高等学校人文社会科学研究项目<安徽经济可持续发展的计量分析>(2008sk215)

摘　　要：在介绍概率变化协调的相关性度量方法的同时,证明了该方法是传统方法的推广。又依据小波协方差在不同尺度下的分解理论,提出了基于小波协方差的相关性度量方法,并对沪深股市波动序列之间的相关性进行了实证分析。结果表明:沪深股市波动序列在整体上具有正相关性,但在不同尺度下沪深股市波动序列之间的相关性不同,小尺度下相关性小。对投资者而言,最好以小尺度为基准选择分散投资策略。We describe the changes in the coordination of the probability of the correlation measurement method in this article, and proved that the method is the traditional method of promotion. This paper, on the basis of summarizing the correlation coefficient and the probability of changes in coordination with the correlation measurement methods, proposes a correlation t method based on wavelet covariance. Furthermore, the Shanghai and Shenzhen stock markets volatility series was empirical analyzed with this method. As a result, the whole correlation of Shanghai and Shenzhen stock markets volatility series has a somewhat positive correlation. There is a scale effect of correlation coefficients in the Shanghai and Shenzhen stock market volatility series. Therefore based on small - scale, portfolio investment is better used to spread the risk.

关 键 词：小波协方差 波动序列 相关性 

分 类 号：O212.1[理学—概率论与数理统计]