A-Share Quantitative Investment Strategy for Multiple Objectives Driven by Machine Learning and Deep Learning

This article uses the real market data of A-shares, selects price data, financial data and technical indicators, uses a variety of machine learning models to predict future returns, and updates the model monthly. At the same time, in order to consider different economic goals, a yield maximization strategy is set, and a risk-return equilibrium strategy based on the modified Markowitz model is set. It attempts to use stocks in the stock pool to track the market index, control risks, and set adjustable mean-variance parameters. This article aims to use advanced computer technology and quantitative methods to provide more reference value for investment groups with different needs and risk preferences.