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Stock Market Trend Analysis Using Hidden Markov Model and Long Short Term Memory

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  • Mingwen Liu
  • Junbang Huo
  • Yulin Wu
  • Jinge Wu

Abstract

This paper intends to apply the Hidden Markov Model into stock market and and make predictions. Moreover, four different methods of improvement, which are GMM-HMM, XGB-HMM, GMM-HMM+LSTM and XGB-HMM+LSTM, will be discussed later with the results of experiment respectively. After that we will analyze the pros and cons of different models. And finally, one of the best will be used into stock market for timing strategy.

Suggested Citation

  • Mingwen Liu & Junbang Huo & Yulin Wu & Jinge Wu, 2021. "Stock Market Trend Analysis Using Hidden Markov Model and Long Short Term Memory," Papers 2104.09700, arXiv.org.
    • Handle: RePEc:arx:papers:2104.09700
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    File URL: http://arxiv.org/pdf/2104.09700
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    Cited by:

    1. Lolea Iulian Cornel & Stamule Simona, 2021. "Trading using Hidden Markov Models during COVID-19 turbulences," Management & Marketing, Sciendo, vol. 16(4), pages 334-351, December.

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