A portfolio investment strategy of financial products with statistical machine learning

Abstract

At present, portfolio investment is an investment strategy widely used in practice. Statistical machine learning has good performance and accuracy for portfolio investment return and risk calculation. Most current researches focus on the price rise and fall of a single stock or risky securities. This method uses machine learning technology to calculate the portfolio return of multiple financial products, including the portfolio return of high-risk securities, medium-risk securities and low-risk securities and the related risk degree. The simulation results show that the proposed method has good reference value.