Relational Analysis Between Stocks Based On The Lead-Lag Effect In Stock Market

The volatile stock market not only brings huge gains to the investors, but also makes them face enormous risk. Analyzing and predicting the tendency of stock price is not only of great significance to investors, but also conducive for government to formulate a macroeconomic control policy. This research applies the method of grey system model to analyze the correlation between stocks based on the lead-lag effect exists in the stock market. According to the relationship between stock price and trading volume, the paper studies the time delay effect between stocks so as to realize the short-term forecast of stock price. It has important guidance effect for investors to buy and sell stocks at the right moment, and provides an important thought for future research. The main content is as follows:In chapter1, it mainly summarizes the related research conclusions from the perspectives of the lead-lag effect, association analysis methods and the application of grey model in the stock market.In chapter2, this part firstly explains that the stock market is a frictional market with information collection cost and noise trading from the aspects of the efficient market hypothesis and market friction theory. The main reason for the lead-lag effect is that stocks have different reaction rates to information. And then discusses the Chinese stock market reaction mode on information and herd behavior, which shows that the lead-lag effect exists in the Chinese stock market.In chapter3, this part mainly studies the time delay effect between stocks from the aspects of stock price. The paper puts forward a new grey relational analysis based on the function information, which satisfies the grey relational analysis axioms. When the function is unknown, a piecewise quadratic interpolation method is used to find the approximation function replacing the original one, and then the information difference between different functions can obtained by means of integral formulas. Putting the information difference into the time lag grey relational model, the lag period between stocks can be found finally. Through the empirical research on bank stocks, the results of quantitative analysis are consistent with the qualitative results about K line charts, which show that the time lag grey relational analysis based on the function information has a certain validity and feasibility. In chapter4, we discusse the relationship between stock price and trading volume, and point out that stock trading volume can explain the volatility of the stock well, which can not be neglected. In order to take both stock price and trading volume into consideration, the paper establishes the matrix time delay grey relational analysis based on the function information by combining the matrix grey correlation model. The range of research is expanded from two-dimensional plane to three-dimensional space, and it also satisfies the matrix grey relational analysis axioms.The empirical analysis shows that considering stock price and trading volume together is better than only considering stock price, which offers more valuable reference information to investors.In chapter5, this part introduces the main research contents, research results and innovation points, also discussing the future research work.