中国股票市场的高阶矩波动特征研究  

Higher Moments Volatility Characteristics in Chinese Stock Market

作　　者：王鹏[1] 王建琼[1] 

机构地区：[1]西南交通大学经济管理学院,成都610031

出　　处：《管理科学》2008年第4期115-120,共6页Journal of Management Science

基　　金：国家自然科学基金(70501025;70771097)

摘　　要：最近的研究表明,除资产收益二阶矩外,高阶矩(包括三阶矩和四阶矩)同样是反映金融资产波动行为的重要方面。以中国股票市场最具代表性的两种股价指数——上证综指和深证成指10年的股价数据样本为例,通过构建可以刻画时变高阶矩的自回归条件方差-偏度-峰度模型,实证研究中国股票市场的高阶矩波动特征。研究表明,中国股票市场收益的偏度、峰度具有显著的时变性和波动聚类性;中国股市不但存在二阶矩(方差)风险,还存在显著的三阶矩(偏度)风险和四阶矩(峰度)风险,并且三阶矩风险和四阶矩风险具有同步性;将偏度方程和峰度方程引入波动模型会抵消原有方差波动的杠杆效应。初步提出将高阶矩波动模型运用于金融风险管理的思想。Recent studies have demonstrated that besides the second moment of asset returns, the time-varying characteristics of higher-moments is also the important aspect to reflect the volatility behavior. This paper researches the higher-moments volatility characteristics of ten years of Shanghai synthesis index returns and Shenzhen composition index returns by use of NAGARCHSK model. The result show that the variance, skewness, kurtosis of stock market return on China have notable time-varying characteristics and volatility clustering characteristics; China＇s stock market not only exist second moment （variance） risk, and there are still significant third moment （skewness） risk and fourth moment （kurtosis） risk, and there are synchronization of third moment risk and fourth moment risk; there exist obvious lever effect in Shanghai stock market return, which is counteracted after the introduction of skewness equation and kurtosis equation to NAGARCH model. Finally, we suppose the associated research between higher-moments volatility models and risk management would be significative.

关 键 词：高阶矩 NAGARCHSK模型 GRAM Charlier展开 风险管理 

分 类 号：F830.91[经济管理—金融学]