An Empirical Analysis Of Volume-price Relation Using Data In The Chinese Stock Market

Now,the stock market has become an important part of Chinese economy.The stock market affects not only the development of the national economy,but also the vital interests of the people.By the end of 2014,a new bull market has greatly boosted the enthusiasm of market.After that,the unstable market structure leaded to the continuous fall.Stock price and trading volume is the basic performance of investors’ market behavior.They contain a large number of market information of the past and the current.This paper mainly researches on the volume and price relationship of Chinese stock market in this special period.This paper selects the Shanghai Composite Index closing price and trading volume of 1395 trading days as the study object.It uses ADF way to test the stability of the number sequences closing price and trading volume.We find that the number of price series and the number of trading volume series are non-smooth,and first-order singular.The establishment of a bivariate vector autoregression model depicts the correlation between the logarithmic price and the logarithmic trading volume.After analyzing the stability and residual of the model,we find that VAR model is reasonable.Based on VAR model,Granger causality tests are used to examine the dynamic relationship between the logarithmic price and the trading volume.The results indicate the presence of two-way causal relationship between the logarithmic price and the amount of transactions.It means that both factors’ past information has a significant impact on predicting the other’s current period value.And the impact of price on trading volume is greater than the impact of trading volume on prices.We use Johansen test to determine the cointegrating relationship between two logarithmic sequences.And we establish the error correction model based on cointegration theory.Finally,using impulse response function and variance decomposition to analysis the system variables’ response to the external shocks.Predicting the inside and outside sample.