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Academic Journal of Business & Management, 2021, 3(4); doi: 10.25236/AJBM.2021.030407.

Review on the Application of Machine Learning in Stock Forecasting


Shengyin Luo

Corresponding Author:
Shengyin Luo

School of Information, Southwest Petroleum University, Nanchong, Sichuan 637001, China


With the improvement of people's awareness of financial management, more and more people put their surplus assets into the stock market. In the dynamic and complex stock system, the future rise and fall of each stock are unknown to a certain extent. This unknown has caused discussion among investors and related scholars, and thus stock forecasting has become a hot topic in the research field. By combing the relevant work of literature in the recent three years, we can find that the research topic of stock forecasting is mainly in the field of machine learning, and its research scope is mainly deep learning and data mining. In the process of applying machine learning to stock forecasting, the influencing factors mainly include stock data collection and preprocessing machine learning model, and machine learning algorithm. After analysis, it is found that the final prediction result of the stock is mainly related to stock data and the machine learning model. Aiming at the deficiency of prediction, the summary and prospect of applying machine learning in stock prediction are discussed at the end of this paper.


machine learning, stock forecasting, deep learning, data mining

Cite This Paper

Shengyin Luo. Review on the Application of Machine Learning in Stock Forecasting. Academic Journal of Business & Management (2021) Vol. 3, Issue 4: 27-30. https://doi.org/10.25236/AJBM.2021.030407.


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