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沪深300股指期货收益率及波动率的长记忆性研究
引用本文:金成晓,王继莹. 沪深300股指期货收益率及波动率的长记忆性研究[J]. 北京理工大学学报(社会科学版), 2014, 16(5): 89-93,102
作者姓名:金成晓  王继莹
作者单位:吉林大学数量经济研究中心,长春130012;吉林大学商学院,长春130012
摘    要:对股指期货收益率与波动率的长记忆性进行研究,可以反映市场的运行效率。运用ADF-KPSS联合检验法、自相关系数法、R/S检验法检验了沪深300股指期货的收益率及波动率序列的长记忆性。结果显示:沪深300股指期货的收益率序列不具有显著的长记忆性,而其波动率序列具有显著的长记忆性,波动率的长记忆性暗示着市场中事件和消息对我国股指期货市场的影响不会马上消失,而可能对市场产生长期和深远的影响,也意味着我国股指期货市场的有效性有待加强,需要从信息披露、培育多元化投资主体等方面加强市场建设,以消除长记忆性对我国股指期货市场健康发展的影响。运用FIGARCH模型度量了沪深300股指期货波动率的长记忆性,为后续股指期货波动相关研究提供参考。

关 键 词:股指期货收益率  股指期货波动率  股指期货波动率长记忆性
收稿时间:2013-08-21

Research on Long Memory of Returns and Volatility of CSI 300 Index Futures
JIN Chengxiao and WANG Jiying. Research on Long Memory of Returns and Volatility of CSI 300 Index Futures[J]. Journal of Beijing Institute of Technology(Social Sciences Edition), 2014, 16(5): 89-93,102
Authors:JIN Chengxiao and WANG Jiying
Affiliation:1.Center for Quantitative Economics, Jilin University, Changchun 130012, China2.Bussiness School, Jilin University, Changchun 130012, China
Abstract:The research on the long memory of returns and volatility of stock index futures yield can reflect the efficiency of the market. This paper researched the long memory of returns and volatility of CSI 300 index futures by applying ADF-KPSS test,Autocorrelation test and R/S test method. The results showed that the returns series of CSI 300 stock index futures lack significantly long memory, but the volatility series of CSI 300 stock index have significantly long memory. The long memory of volatility implies that the impact of events and news on stock index futures market in China will not disappear immediately, and might have long-term and far-reaching influence on the market. It also means that the effectiveness of stock index futures market in China needs to be strengthened. We need to strengthen market building from the aspects of information disclosure and training diversification of investors to eliminate the impact of long memory on the healthy development of stock index futures market in China. Finally, the article used FIGARCH model to measure the long memory of volatility series to provide a reference for subsequent research on the stock index futures.
Keywords:returns of stock index futures  volatility of stock index futures  long memory of volatility series
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