Improved Accuracy Stock Price Change Prediction Model Using Trading Volume

  • Zhen Wei
  • Chao Wu
  • Yike GuoEmail author
  • Zhongwei Yao
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 886)


This research aims to model the relationship between the change in stock price and the volume. Linear regression has been applied to the model at daily and at minute time scales; then Random Forest and Lasso regression have been applied to the model. The results show that the larger the data, the better fit the model is, and Random forest has better prediction accuracy than the linear model.


Equity trading Finance Machine learning Volume 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Data Science InstituteImperial College LondonLondonUK

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