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Bitcoin Price Prediction Using Machine Learning and Technical Indicators

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Distributed Computing and Artificial Intelligence, 20th International Conference (DCAI 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 740))

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Abstract

With the rise of Blockchain technology, the cryptocurrency market has been gaining significant interest. In particular, the number of cryptocurrency traders and market capitalization has grown tremendously. However, predicting cryptocurrency prices is very challenging and difficult due to the high price volatility. In this paper, we propose a classification machine learning approach in order to predict the direction of the market (i.e., if the market is going up or down). We identify key features such as Relative Strength Index (RSI) and Moving Average Convergence Divergence (MACD) to feed the machine learning model. We illustrate our approach through the analysis of Bitcoin’s close price. We evaluate the proposed approach via different simulations. Particularly, we provide a backtesting strategy. The evaluation results show that the proposed machine learning approach provides buy and sell signals with more than 86% accuracy.

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Author information

Authors and Affiliations

  1. University of Ottawa, Ottawa, ON, K1N 6N5, Canada

    Abdelatif Hafid & Dimitrios Makrakis

  2. University of Montreal, Montreal, QC, H3T 1J4, Canada

    Abdelhakim Senhaji Hafid

Authors
  1. Abdelatif Hafid
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  2. Abdelhakim Senhaji Hafid
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  3. Dimitrios Makrakis
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Corresponding author

Correspondence to Abdelatif Hafid .

Editor information

Editors and Affiliations

  1. ETSII / CETINIA, Universidad Rey Juan Carlos, Madrid, Madrid, Spain

    Sascha Ossowski

  2. Politechnika Śląska Kielce, Kielce University of Technology, Santa Cruz, Poland

    Pawel Sitek

  3. Department of Informatics, Engineering School, University of Minho, Braga, Portugal

    Cesar Analide

  4. Departamento de Engenharia Informática, Polytechnic Institute of Porto, Porto, Portugal

    Goreti Marreiros

  5. BISITE, University of Salamanca, Salamanca, Salamanca, Spain

    Pablo Chamoso

  6. BISITE, University of Salamanca, Salamanca, Salamanca, Spain

    Sara Rodríguez

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Hafid, A., Hafid, A.S., Makrakis, D. (2023). Bitcoin Price Prediction Using Machine Learning and Technical Indicators. In: Ossowski, S., Sitek, P., Analide, C., Marreiros, G., Chamoso, P., Rodríguez, S. (eds) Distributed Computing and Artificial Intelligence, 20th International Conference. DCAI 2023. Lecture Notes in Networks and Systems, vol 740. Springer, Cham. https://doi.org/10.1007/978-3-031-38333-5_28

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