Author(s)

Runjia Zhang, Yazhe Wang, Jingyi Zhang, Lingzi Zhang, Jingjing Qu

Corresponding Author

Jingjing Qu

Abstract

In recent years, financial markets have adopted advanced machine learning techniques for stock price prediction. For example, deep learning models such as ANN, XGBoost, SHAP and RF, which have their own advantages and disadvantages in predicting stock prices. In this study, stock price prediction is carried out by 3 powerful machine learning models: XGBoost, ANN, RF and then their error and accuracy are analyzed.

Keywords

XGB, ANN, SHAP, RF