论文部分内容阅读
采用Andersen和Bollerslev(1997)的FFF回归方法,对上证综合指数高频数据中的周期性进行了分析,并分析了剔除周期后的绝对收益的长记忆性.结果表明:日内收益的周期性相对来说不如日内绝对收益明显;FFF回归可以较好的确定日内绝对收益的周期性;与使用日收益数据的结果相比,利用高频数据更好揭示了股市中更强的长记忆性.
Using the FFF regression method of Andersen and Bollerslev (1997), we analyze the periodicity in the high frequency data of the Shanghai Composite Index and analyze the long memory of the absolute return after the elimination cycle. The results show that the periodicity of the daily return is relatively The FFF regression can better determine the periodicity of the absolute return in the day. Compared with the result of using the daily return data, the use of high frequency data can better reveal the stronger long-term memory in the stock market.