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Predicting the Price of Bitcoin Using Hybrid ARIMA and Machine Learning

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Future Data and Security Engineering (FDSE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11814))

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Abstract

Bitcoin is one of the most popular cryptocurrencies in the world, has attracted broad interests from researchers in recent years. In this work, Autoregressive Integrate Moving Average (ARIMA) model and machine learning algorithms will be implemented to predict the closing price of Bitcoin the next day. After that, we present hybrid methods between ARIMA and machine learning to improve prediction of Bitcoin price. Experiment results showed that hybrid methods have improved accuracy of predicting through RMSE and MAPE.

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Author information

Authors and Affiliations

  1. University of Information Technology, VNU-HCM, Ho Chi Minh City, Vietnam

    Dinh-Thuan Nguyen & Huu-Vinh Le

Authors
  1. Dinh-Thuan Nguyen
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  2. Huu-Vinh Le
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Corresponding author

Correspondence to Dinh-Thuan Nguyen .

Editor information

Editors and Affiliations

  1. Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler Universität Linz, Linz, Austria

    Josef Küng

  3. Hosei University, Tokyo, Japan

    Makoto Takizawa

  4. Telecommunications University, Nha Trang City, Vietnam

    Son Ha Bui

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Nguyen, DT., Le, HV. (2019). Predicting the Price of Bitcoin Using Hybrid ARIMA and Machine Learning. In: Dang, T., Küng, J., Takizawa, M., Bui, S. (eds) Future Data and Security Engineering. FDSE 2019. Lecture Notes in Computer Science(), vol 11814. Springer, Cham. https://doi.org/10.1007/978-3-030-35653-8_49

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  • DOI: https://doi.org/10.1007/978-3-030-35653-8_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-35652-1

  • Online ISBN: 978-3-030-35653-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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