In literature, the dynamic price-volume relation is examined by Vector Autoregression (VAR thereafter) model. In this paper, the conventional VAR approach is extended to account for the impacts of structural changes and volatility levels, which are common to China.Due to dramatic responses of China's stock market in recent years, especially two periods of considerable volatility in the years of 2007-2008 and 2014-2015, it is reasonable to conjecture that the structural changes and volatility levels could have substantial influence on the price-volume relation of Chinese stock market. The price-volume relation of the Shanghai stock market is examined with daily data from the year of 2003 to 2016, and contribution is made to the literature by estimating the price-volume relation in a VAR framework with structural breaks and volatility thresholds. As a result, more evidence and robust inferences is obtained:First, the evidence indicates that there exist significant time breaking effects. Second, the high-low volatility effects are substantially. Finally, a linear causal relation is identified from price to volume, which clearly rejects the public views.
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