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Multi Factor Stock Selection Model Based on LSTM

Author

Listed:
  • 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.

Suggested Citation

  • Ru Zhang & Chenyu Huang & Weijian Zhang & Shaozhen Chen, 2018. "Multi Factor Stock Selection Model Based on LSTM," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(8), pages 1-36, August.
    • Handle: RePEc:ibn:ijefaa:v:10:y:2018:i:8:p:36
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    References listed on IDEAS

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    1. Rajagopal, 2015. "Market Trend Analysis," Palgrave Macmillan Books, in: The Butterfly Effect in Competitive Markets, chapter 4, pages 95-118, Palgrave Macmillan.
    2. Chen, Nai-fu & Zhang, Feng, 1998. "Risk and Return of Value Stocks," The Journal of Business, University of Chicago Press, vol. 71(4), pages 501-535, October.
    3. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
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    Citations

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    Cited by:

    1. Ganggang Guo & Yulei Rao & Feida Zhu & Fang Xu, 2020. "Innovative deep matching algorithm for stock portfolio selection using deep stock profiles," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-31, November.
    2. Shuang Zhang & Xingdong Feng, 2022. "Distributed identification of heterogeneous treatment effects," Computational Statistics, Springer, vol. 37(1), pages 57-89, March.
    3. Zeynep Cipiloglu Yildiz & Selim Baha Yildiz, 2022. "A portfolio construction framework using LSTM‐based stock markets forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2356-2366, April.
    4. Jujie Wang & Zhenzhen Zhuang & Liu Feng, 2022. "Intelligent Optimization Based Multi-Factor Deep Learning Stock Selection Model and Quantitative Trading Strategy," Mathematics, MDPI, vol. 10(4), pages 1-19, February.

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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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