Abstract
This article first introduces the relevant concepts of quantitative investment and the development history of multi-factor theory as well as the advantages of machine learning in the field of quantitative investment. After that, this article mainly establishes the quantitative stock selection model. The establishment of quantitative stock selection models mainly includes two aspects: the screening of quantitative factors and the construction of Long Short-Term Memory (LSTM) models. The screening of quantitative factors includes data preprocessing and testing the validity of single factors through the Information Coefficient (IC) method. In the establishment of the stock selection model, this article first introduces the advantages of LSTM in time series prediction, then introduces the structure of the LSTM model in detail, and then introduces the use of selected quantitative factors and the LSTM model to build the stock selection model of this article. Finally, the stock selection model constructed in this article is backtested to verify the effectiveness of the model.
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