摘要
本文旨在应用高频数据估计中国股市的已实现波动率。我们发现股票指数与个股的高频交易数据中的微观摩擦影响正好相反 ,使用极高频的数据会大大增加个股的波动率估计值 ,相反却会大大降低指数的波动率估计值。在计算各种频率的已实现波动率的基础上 ,本文构造了一种较为精确的估计波动率的方法 ,可以更好地平衡测量误差与微观结构误差。基于已实现波动率 。
This paper utilizes high-frequency data to estimate the realized volatility in Chinese stock market.We found that the microstructure bias of single stock is opposite to that of stock index.By employing data with very high-frequency,the realized volatility of single stock would be much higher,whereas that of stock index would be much lower.Based on the realized volatilities estimated with different frequencies,we develop a more accurate estimate method,which effectively balances the microstructure error and usual estimate error.With the realized volatility,we investigate some style facts of the volatility for stock indexes,such as the leverage effect and the long memory effect.
出处
《经济研究》
CSSCI
北大核心
2003年第2期75-82,共8页
Economic Research Journal
基金
国家自然科学基金课题 ( 7980 0 0 10
70 0 42 0 0 5 )
上交所2002年联合研究计划课题
教育部社科"十五"课题( 0 1jb790 0 2 6)
2002年厦门大学校级课题成果之一
