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Cryptocurrency Price Prediction with Neural Networks of LSTM and Bayesian Optimization

Author

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  • Ehsan Sadeghi Pour

    (Islamic Azad University, Iran)

  • Hossein Jafari

    (Allameh Amini Institute of Higher Educationm Iran)

  • Ali Lashgari

    (Kansas State University, USA)

  • Elaheh Rabiee

    (Kansas State University, USA)

  • Amin Ahmadisharaf

    (Kansas State University, USA)

Abstract

In this paper we present a price prediction for Bitcoin prices. The methodology used is a hybrid artificial neural network model of Long Short-Term Memory and Bayesian Optimization. This is a complex model with a high prediction power, which to our knowledge has not been applied to prediction of cryptocurrency prices to date. Following Charandabi and Kamyar (2021), we elaborate on previous methods used for prediction of cryptocurrency prices and build on their methodology. We conclude with detailed graphs and tables of optimization results.

Suggested Citation

  • Ehsan Sadeghi Pour & Hossein Jafari & Ali Lashgari & Elaheh Rabiee & Amin Ahmadisharaf, 2022. "Cryptocurrency Price Prediction with Neural Networks of LSTM and Bayesian Optimization," European Journal of Business and Management Research, European Open Science, vol. 7(2), pages 20-27, March.
    • Handle: RePEc:epw:ejbmr0:v:7:y:2022:i:2:id:51307
    DOI: 10.24018/ejbmr.2022.7.2.1307
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