Multi Factor Stock Selection Model Based on LSTM


  •  Ru Zhang    
  •  Chenyu Huang    
  •  Weijian Zhang    
  •  Shaozhen Chen    

Abstract

This paper takes CSI- 300 stock as the research object, and uses the LSTM model with memory characteristics and the traditional multi factor analysis to build an improved multi factor stock selection model. In back testing experiments, we use the trained LSTM model to forecast the stock returns and make a portfolio classification to construct the investment strategy. The result shows that the multi factor stock selection model based on LSTM has good profit forecasting ability and profitability.



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