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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。
The variation of trading volume in China’s stock market within a week has been studied. The sampling time span is from 1990-12-19 to 2002-12-31. Using the market turnover ratio to measure the trading volume, the time series of trading volume in China’s stock market was studied by the AR-GARCH model. The results show that the daily turnover of Shanghai and Shenzhen markets does not obey the normal distribution and there is autocorrelation and ARCH effect; AR-GARCH model well fit the time series of daily market turnover rate, estimated The parameters are significant; there is a significant difference in day-market turnover between Monday and Friday and the market turnover rate on Monday reached a one-week high. Explained using the mixed distribution hypothesis, the accumulation of information on non-trading days may be the reason for the high turnover rate on Monday. The results indicate that there is a week-long effect on the trading volume of China’s stock markets within the sample size of the study.