Study On The Forecasting Model Of Shanghai Composite Index And Its Application In Investment Strategies:Based On Technical Indicators

With the development of China's securities industry,the Shanghai Composite Index(SSEC)has received attention from investors.Investors have made great effort to obtain excess returns from SSEC,and technical analysis may be suitable for the majority of investors.Although technical analysis has rich practical experience in China's securities market,it lacks theoretical guidance.Therefore,it is of great significance to study whether technical indicators have the ability to predict the trend of SSEC and how to construct investment strategies based on technical indicators.Firstly,this paper selects three technical indicator rules,namely MA rule,MOM rule and OBVMA rule,comprehensively covering the volume and price data of the historical transaction of SSEC,and constructs 24 technical indicators based on the three technical indicator rules.Then,through in-sample forecasting and out-of-sample forecasting analysis,the predictive ability of the single technical indicator and the technical indicators' principal component obtained by principal component analysis on the excess returns of the SSEC is tested.Finally,based on the results of empirical analysis,the technical indicators' principal component forecasting model is selected to design investment strategies.An untitled unscaled investment strategy,an equity-titled unscaled investment strategy,an untitled scaled investment strategy and an equity-titled scaled investment strategy are designed for risk-neutral investors,and a utility maximization investment strategy is designed for risk-averse investors.Each investment strategy is back-tested to analyze its practical value.The conclusions of this paper are as follows: First,the predictive ability of the single technical indicator on the excess return of the SSEC varies greatly among different indicators,among which OBVMA(2,5)has the best predictive ability.Secondly,the technical indicators' principal component forecasting model has significant predictive ability both in-sample and out-of-sample,and the predictive ability is robust.Thirdly,the technical indicators' principal component forecasting model is less affected by the selection of technical indicators than the single technical indicator forecasting model,so it is more suitable for practical use.Fourth,the five SSEC investment strategies based on the technical indicators' principal component forecasting model have shown good profitability in back-tested analysis,which indicates that the strategies have practical value.