摘要
以非参数化方法为理论基础,利用沪深300指数2006年至2008年的一分钟高频数据,分离出已实现波动率中的连续性波动和跳跃性波动的时间序列,进而检验了两种不同波动成分在股市不同周期内的统计性质,以及收益率对各种波动成分是否存在规模效应和杠杆效应.结论表明:股票指数的运行过程存在明显的跳跃聚集现象;我国A股市场的连续性波动与跳跃性波动比美国市场具有更为长期的滞后相关性;杠杆效应在各个考察时期内均不具有显著性,规模效应在大部分时间内具有显著性,表明收益率取值的大小较取值的正负更能对各种波动成分造成影响,这种影响在牛市中更为明显.
Based on the non-parametric approach, we decompose the realized volatility into the continuous volatility and the jump volatility with the high-frequency data of Hushen 300 index, investigate the statistic characteristics of these two different volatility components, together with the check of size effect and leverage effect of the return. We find that： jump-cluster phenomena exist in the process of stock market index; China＇s A-share stock market has longer lagged autocorrelations than the US market; the leverage effect is not significant in all sample period but the size effect is significant in most of the sample period, which means the size of the returns has more influence then the sign of the returns, especially in bull market.
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2010年第9期1554-1562,共9页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(71071132)
教育部人文社科项目(08JA790109)
福建省社科规划项目(2008B045)
关键词
跳跃行为
非参数方法
连续性波动
跳跃性波动
jump behavior
non-parametric approach
continuous volatility
jump volatility
