Empiricai Research Of Money Flow Factor Based On Citic Primary Industry

In the stock market,any rational trading behavior is driven by information,and different investors have inconsistent access to information,so their trading methods are also different.We through the Level-2 data(Level-2 data refers to the Shanghai stock exchange trading of securities products real-time trading data)obtained after the stock fund flow data through data analysis can dig out the market microstructure of trading information,reflect the strength of the stock trading power behind the rise and fall,and be able to predict the future of the stock go up drop.Apply the capital flow factor of stocks to industries to observe whether the capital flow factor of industries has a significant impact on the return rate of different industries.At present,no scholars have conducted industry-level research on this factor.This paper takes the 2010 edition of 29 CITIC first-class industries as an example.The data of stock money flow factor and industry index return rate from the beginning of 2018 to the end of 2021 are selected.By the theory of capital flow,industry rotation,classification and summary,statistical analysis and comparison,the money flow factor of A-share is integrated into the money flow factor of 29 different industries by currency value weighting.We get 85 factors of industries,and study the effectiveness of this factor by empirical research from different backtracking and trading periods.Finally,the factors with stable high return rate and small correlation were selected to synthesize factors in three ways:equal weight,rolling IC weighting and rolling ICIR weighting,which conduct empirical research and provide reference for investors.It is found that most of the money flow factors selected have stable and higher returns during the appropriate backtracking period.For example,the cumulative net value of factors could reach to 2 like Large single opening fund inflow(hand)and Opening capital inflow rate(volume)from 2018 to 2021,and the monotonicity of factors is significant.We selected 20 effective factors for correlation analysis.Finally,we select six factors to Synthesize large factors.Three synthetic factors of winning percentage were similar,but the factors synthesized by rolling IC value method and rolling ICIR method have stronger monotonicity.The annual returns of the synthetic factors were all as high as or close to 18%,and the cumulative net value was close to 2.