Application of machine learning in stock selection

Abstract With the development of artificial intelligence technology, machine learning has achieved very good results in field stock selection. This paper mainly studies application linear model, clustering, support vector machine, random forest, neural network and deep methods The main contribution this is to provide a new idea for traditional quantitative investors, so that they can build more efficient selection model practical application. experimental show constructed by these six obtain higher return stability.