The Research On The Distribution Characteristics Of Daily Trading Volume In Stock Market

As an important indicator of market volatility,stock trading volume contains important information about the process of trading.The research on the trading volume not only reflects the degree of concern from investors in the stock market,but also plays an very important role in promoting the stock price rise.In this paper,the stock daily trading volume is subjected to U type distribution and verified by the high frequency trading volume data,and then we analyze the reason of the U distribution by using the method of agent-based computational finance.Based on the above analysis,we modified the traditional volume weighted average price to improve the stock return.Firstly,this paper focuses on the empirical study of the daily distribution of trading volume in C hina's A shares stock market by using the existed data and methods.The results show that according to A shares of the Shanghai stock exchange,the 5 minutes trading volume is subjected to the typical "U" type distribution: the trading volume in the opening and closing stage is significantly higher than the other stage,which is also true to single stock.In addition,the empirical results show that,the midday break also cause an increase in trading volume to a certain extent.We believe that this phenomenon is related to the microstructure of the financial market,the absorption,digestion and release of the overnight information,the accumulation of information and the needs to trade in the absence of the transaction stage.In order to verify the above conjecture,this paper constructs an artificial stock market to simulate the behavior of traders.The simulation shows that the non-informed traders can increase the profit by learning the trading opportunities to achieve concentration and coordination.Based on the above analysis,the paper proposes an improved VWAP strategy by analyzing market trading orders.We check the large cap,middle cap,small cap stocks profit respectively by the improved and standard VWAP strategy and affirm the advantage of the improved strategy: the improved strategy by integrating past transaction information can help save transaction costs and beat the market average price.