Research On Quantitative Investment Strategy Of Stock Selection Timing Based On The Correlation Of Stock Index Volatility

With the advent of the era of big data and the development of artificial intelligence,quantitative investment has gradually replaced artificial investment for consulting and financial investment services.Quantitative investment strategies can also be called robot investment consultants,smart investment financing,automated investment and wealth management.Through the big data and intelligent algorithms to establish a quantitative model,based on investor risk appetite,judge the market,intelligently configure and invest in assets,and implement automatic strategy trading services.Quantitative investment can comprehensively examine the trend of the market and accurately configure its investor wealth,including multiple asset range ratios,such as stocks,futures,funds,and insurance.Compared with traditional analysts,quantitative investment can improve the accuracy of revenue,reduce time and labor costs,and improve service efficiency when providing customers with digital asset allocation.At the same time,give analysts an excellent investment tool to provide great support for the work of analysts.This article introduces machine learning methods,adding variables and indicators to try to find strategies that can beat the market and beat some of the quantitative products on the market.After continuous trials,this paper designs a quantitative investment strategy based on support vector machine stock picking and large stock index volatility timing.In the stock picking strategy,the data factors of the Shanghai and Shenzhen 300 Index constituents are first classified into three categories:technical index factor,company fundamental class factor,and public opinion index factor,and then ranked according to the rate of return.The 50%or the last 50%sets the dependent variable of the two classifications.Finally,the model training is performed by the support vector machine,and the stock is selected.In the timing strategy,the market style is classified into reverse,trend,and shock.When the market style is attributed to "reversal" and the smooth one-way volatility is negative,the stock is held;when the market style is attributed to "trend" and the smoothed one-way volatility is positive,the stock is held;When the style of the market is attributed to "shock",it also chooses to hold stocks.The rest of the situation is the sale of stocks.Through empirical research,it is shown that the portfolio products constructed through the logic return stock selection and stock index volatility design concept are significantly better than the Shanghai and Shenzhen 300 Index in both the cumulative yield and the annualized yield.The validity of the product and the superiority of the product confirm the value of this article.From the point of view of cumulative yield,the cumulative yield of the portfolio products constructed in this paper is 25.9%,and the cumulative yield of the Shanghai and Shenzhen 300 Index in the interval is 18.0%.During the back-test period,its annual back-tested yields were all positive,and except for 2014,they all outperformed the CSI 300 index.In terms of risk control,this paper designs innovative timing indicators based on the volatility of the CSI 300 Index.Through empirical evidence,it can be found that when encountering extreme market conditions,it can effectively signal,reduce investor losses,and control the maximum backtest.At the same time,products that can be found through Brinson analysis have strong stock selection ability in the sector.Therefore,we can significantly improve the product's profitability by studying the industry's asset allocation.Through the net value regression analysis,we can find that the product style of this article has not changed during the three-year period,and keep investing in high-value and high-liquidity stocks.Quantifying products has certain practicability.With the advancement of science,the development and popularization of computer technology,the reduction of transaction costs,etc.,the market must increasingly accept quantitative investment,and find that the value of quantitative investment,quantitative investment must have a bright future.