The Study Of Relationship Between Volume-Price Based On High-Frequency Data In Shanghai And Shenzhen Stock Market

The stock market was born from the development of the socio-economic. Today, the stock market as an important part of the capital market, and it can reflect the Macrocconomic changes. Therefore it was given the title of macro-economic barometer. In the stock market, stock price and trading volume are the two changing variables and the two intuitive indicators. The drop in prices often accompanied by a decline in volume, and the rise of price also enlarge the volume. So this article will study the relationship between the two variables.The relationship of volume and price has profound theoretical significance and application value. Firstly, the relationship of the volume and price based on the high-frequency data will allow us to study the microscopic structure of financial markets. The volatility of the stock market tells us that the fluctuations in the prices of financial assets will be subject to the influence of external information. Changes in trading volume partly reflects the impact of the information on the stock market. So it can be used as an alternative of the information variables to explain the price fluctuations better. Secondly, the study of the relationship between volume and price has a high application value for the investors and in futures investment.Articles will study the relationship between volume and price on China’s Shanghai and Shenzhen stock market from both static and dynamic analysis. Articles use the more traditional statistical analysis methods to study the static relationship between volume and price, such as the basic descriptive statistics, unit root test, auto-correlation test Granger non-causality test.And summarize the similarities and differences between the high-frequency data and low-frequency data. Articles will use ARMA (p, q) model to regress trading volume and decompose the expected trading volume and non-expected trading volume. The study of the dynamic relationship use Quantile regression model and VAR model to research. Quantile regression model describes the relationship between volume and price from different quantile point. VAR model describes the relationship between original trading volume、expected,unexpected trading volume and rate of return and its volatility sequence, and by doing pulse response to analyze the impact between the variables.The innovation of the article as followed:Firstly, the article selected high-frequency time series data using Quantile Regression model to study the relationship between volume and price, and can be better to excavated the relationship between volume and price than the low frequency data; Secondly, the article using your own words made a comparative analysis of high-frequency data and low-frequency on characteristics of data, and summarize these studies on the relationship between volume and price and provides convenience for later researchers.