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Regression and Forecasting of U.S. Stock Returns Based on LSTM

3 February 2025
Shicheng Zhou
Zizhou Zhang
Rong Zhang
Yuchen Yin
Chia Hong Chang
Qinyan Shen
    AI4TS
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Abstract

This paper analyses the investment returns of three stock sectors, Manuf, Hitec, and Other, in the U.S. stock market, based on the Fama-French three-factor model, the Carhart four-factor model, and the Fama-French five-factor model, in order to test the validity of the Fama-French three-factor model, the Carhart four-factor model, and the Fama-French five-factor model for the three sectors of the market. French five-factor model for the three sectors of the market. Also, the LSTM model is used to explore the additional factors affecting stock returns. The empirical results show that the Fama-French five-factor model has better validity for the three segments of the market under study, and the LSTM model has the ability to capture the factors affecting the returns of certain industries, and can better regress and predict the stock returns of the relevant industries. Keywords- Fama-French model; Carhart model; Factor model; LSTM model.

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@article{zhou2025_2502.05210,
  title={ Regression and Forecasting of U.S. Stock Returns Based on LSTM },
  author={ Shicheng Zhou and Zizhou Zhang and Rong Zhang and Yuchen Yin and Chia Hong Chang and Qinyan Shen },
  journal={arXiv preprint arXiv:2502.05210},
  year={ 2025 }
}
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