Research On Quantitative Investment Strategy Based On Grey Relational Degree Analysis

With the continuous development of China's financial economy,the stock market situation has become more complex,the traditional investment methods can no longer meet the growing demand for investment.Quantitative investment is one of the popular trends in the research of stock investment in recent years,that is to say,analyzing the massive historical data,we can get a kind of investment strategy which can obtain stable excess return.In this paper,a new quantitative investment strategy is put forward based on the empirical analysis of a large number of historical data by using the improved grey relational degree analysis method,taking the stock technical index as the object of study.Firstly,in order to study the correlation degree among the technical indexes of stock,the correlation analysis and cluster analysis are incorporated into the traditional grey correlation degree analysis,and then the improved grey correlation degree analysis method is obtained.Then,applying the improved grey relational analysis method to study the common stock technical indexes,we get some stock technical indexes,which are called "quantitative index combination",through the parameter selection of the quantitative index combination,Trading rules and stock buying and selling points Finally,the paper selects the historical data of A-share in Shanghai stock market for several periods to carry on the empirical analysis to the quantitative investment strategy,and verifies the feasibility and effectiveness of the strategy.In this paper,the improved grey relational analysis method is used to study the technical indexes of stock,and the combination of quantitative indexes is obtained,then the quantitative investment strategy is constructed,and the feasibility and effectiveness of the quantitative investment strategy are empirically analyzed.The results show that the quantitative investment strategy constructed in this paper has certain practical significance and practical value for the research of stock investment.