关键词: 股票预测, 机器学习, 支持向量机, 深度学习, 集成学习

Abstract:

It has always been regarded as the emphasis of research to reveal the operation law of stock market. In recent years, machine learning method has made good progress in stock forecasting, and it has shown unique advantages over traditional methods such as fundamental analysis and technical analysis. This paper focuses on collecting the key references in the field of stock prediction that uses machine learning methods in recent years, and analyzing as well as summarizing feature engineering, the application of machine learning algorithms and the main problems in stock prediction research. The characteristics and shortcomings of each algorithm in application are reviewed, and future development direction of this field is made a thorough analysis and forecasted from the aspects of transfer learning, feature engineering and deep learning model fusion.

Key words: stock forecast, machine learning, support vector machine, deep learning, intergrated learning