Intelligent Prediction Model of Shanghai Composite Index Based on Technical Indicators and Big Data Analysis

Abstract

Technical indicators provide useful information for investors to study the stock market. Based on the Shanghai Composite index from November 1994 to March 2022, we construct 20 technical indicators based on the moving-average (MA) rules, momentum (MOM) rules and volume on balance (VOL) rules, and model and analyze through ordinary least squares and extracted principal components. We found that the technical indicators provide effective information for the forecasting of the excess return rate of the Shanghai Composite index both in- and out-of sample, and the model has more superior forecasting performance in the decline period of the business cycle. In addition, this paper finds that the information provided by the technical indicators can better predict the rise of the peak front and the trough front of the business cycle. Finally, this paper studies the economic significance of the yield forecasting using technical indicators, and finds that the information in technical indicators can help investors to obtain better investment returns without transaction fees.