中国股市交易量的周内效应

研究了中国股市交易量在一周里面的变化规律,采样时间跨度是从1990-12-19到2002-12-31。以市场换手率度量交易量,采用自回归广义自回归条件异方差(AR-GARCH)模型研究了中国股市交易量的时间系列。研究结果显示沪市和深市的日市场换手率不服从正态分布并且存在着自相关性和ARCH效应;AR-GARCH模型很好地拟合了日市场换手率时间系列,估计出来的参数十分显著;周一到周五的日市场换手率存在显著差异并且周一的市场换手率达到了一周的最大值。利用混合分布假说进行了解释,非交易日的信息积累可能是周一高换手率的原因。结果指出:在该研究的样本范围内,中国股市交易量存在着周内效应。

Day-of-the-week effects of trading volume in Chinese stock market

Regular changes of the trading volume of the Chinese stock market during the week were studied for the sample period from 1990-12-19 to 2002-12-31. The turnover was used to measure the trading volume which was analyzed using the Autoregressive- Generalized Autoregressive Conditional Heteroskedasticity (AR- GARCH) model. The results show that the daily turnover of the Shanghai and Shenzhen stock markets does not conform to a normal distribution with autocorrelation and ARCH effects in the daily market turnover. The AR-GARCH model accurately fits the daily market turnover time series with very significant estimated parameters. The analysis shows that the daily market turnover varies significantly from Monday to Friday with the daily market turnover significantly higher on Monday in both markets. The mixed distribution hypothesis (MDH) was employed to explain this phenomenon, with information accumulation as one potential important reason.