Research on the Application of Machine Learning Technology in Intelligent Stock Selection

Hongtao Chen

doi:10.54097/hbem.v9i.7763

Authors

Hongtao Chen

DOI:

https://doi.org/10.54097/hbem.v9i.7763

Keywords:

Machine Learning Technology; Smart Stock Selection; Application Research.

Abstract

With the development of big data era and artificial intelligence, intelligent investment has gradually replaced artificial investment consultants for consulting and financial services. Robo-advisor can also be called robot investment, intelligent financial management, automated financial management and so on. The traditional quantitative investment model mostly depends on the indicators designed by the financial knowledge and experience of the researchers and cooperates with the economic model or strategy. Financial knowledge and experience play a major role in the construction of the quantitative investment model, so the efficiency of model development and updating is low and the human influence factors are large. The quantitative model is established through big data and intelligent algorithms, and the market is judged according to the risk preference of investors, intelligent allocation and investment of assets are carried out, and automatic strategic trading services are implemented. Based on machine learning theory, this paper studies the two types of investment in quantitative investment: quantitative timing and quantitative stock selection, and puts forward corresponding quantitative investment models. Through testing the models, it is verified that they have good profitability and risk control ability, which is a quantitative investment model that can provide guidance for investors.

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