IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v61y2023i4d10.1007_s10614-022-10262-6.html
   My bibliography  Save this article

Bitcoin Price Prediction: A Machine Learning Sample Dimension Approach

Author

Listed:
  • Sumit Ranjan

    (Madras School of Economics)

  • Parthajit Kayal

    (Madras School of Economics)

  • Malvika Saraf

    (Madras School of Economics)

Abstract

The purpose of the paper is to predict Bitcoin prices using various machine learning techniques. Due to its high volatility attribute, accurate price prediction is the need of the hour for sound investment decision-making. At the offset, this study categorizes Bitcoin price by daily and high-frequency price (5-min interval price). For its daily and 5-min interval price prediction, a set of high-dimensional features and fundamental trading features are employed, respectively. Thereafter, we find that statistical methods like Logistic Regression predict daily price with 64.84% accuracy while complex machine learning algorithms like XGBoost predict 5-min interval price with an accuracy level of 59.4%. This work on Bitcoin price prediction recognizes the significance of sample dimensions in machine learning algorithms.

Suggested Citation

  • Sumit Ranjan & Parthajit Kayal & Malvika Saraf, 2023. "Bitcoin Price Prediction: A Machine Learning Sample Dimension Approach," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1617-1636, April.
    • Handle: RePEc:kap:compec:v:61:y:2023:i:4:d:10.1007_s10614-022-10262-6
    DOI: 10.1007/s10614-022-10262-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-022-10262-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-022-10262-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The economics of BitCoin price formation," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1799-1815, April.
    2. Adam Hayes, 2014. "What Factors Give Cryptocurrencies Their Value: An Empirical Analysis," Working Papers 1406, New School for Social Research, Department of Economics, revised Mar 2015.
    3. Barro, Robert J, 1979. "Money and the Price Level under the Gold Standard," Economic Journal, Royal Economic Society, vol. 89(353), pages 13-33, March.
    4. repec:men:wpaper:58_2015 is not listed on IDEAS
    5. Jaroslav Bukovina & Matus Marticek, 2016. "Sentiment and Bitcoin Volatility," MENDELU Working Papers in Business and Economics 2016-58, Mendel University in Brno, Faculty of Business and Economics.
    6. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Riaz Ud Din & Salman Ahmed & Saddam Hussain Khan, 2024. "A Novel Decision Ensemble Framework: Customized Attention-BiLSTM and XGBoost for Speculative Stock Price Forecasting," Papers 2401.11621, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Merediz-Solà, Ignasi & Bariviera, Aurelio F., 2019. "A bibliometric analysis of bitcoin scientific production," Research in International Business and Finance, Elsevier, vol. 50(C), pages 294-305.
    2. Panagiotidis, Theodore & Stengos, Thanasis & Vravosinos, Orestis, 2019. "The effects of markets, uncertainty and search intensity on bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 220-242.
    3. Damian Zięba & Katarzyna Śledziewska, 2018. "Are demand shocks in Bitcoin contagious?," Working Papers 2018-17, Faculty of Economic Sciences, University of Warsaw.
    4. Zięba, Damian & Kokoszczyński, Ryszard & Śledziewska, Katarzyna, 2019. "Shock transmission in the cryptocurrency market. Is Bitcoin the most influential?," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 102-125.
    5. Gianna Figá-Talamanca & Marco Patacca, 2019. "Does market attention affect Bitcoin returns and volatility?," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 135-155, June.
    6. Parthajit Kayal & Purnima Rohilla, 2021. "Bitcoin in the economics and finance literature: a survey," SN Business & Economics, Springer, vol. 1(7), pages 1-21, July.
    7. Bouri, Elie & Gupta, Rangan & Lahiani, Amine & Shahbaz, Muhammad, 2018. "Testing for asymmetric nonlinear short- and long-run relationships between bitcoin, aggregate commodity and gold prices," Resources Policy, Elsevier, vol. 57(C), pages 224-235.
    8. Obryan Poyser, 2017. "Exploring the determinants of Bitcoin's price: an application of Bayesian Structural Time Series," Papers 1706.01437, arXiv.org.
    9. Bouri, Elie & Gupta, Rangan & Tiwari, Aviral Kumar & Roubaud, David, 2017. "Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions," Finance Research Letters, Elsevier, vol. 23(C), pages 87-95.
    10. Rehman, Mobeen Ur, 2020. "Do bitcoin and precious metals do any good together? An extreme dependence and risk spillover analysis," Resources Policy, Elsevier, vol. 68(C).
    11. Kajtazi, Anton & Moro, Andrea, 2019. "The role of bitcoin in well diversified portfolios: A comparative global study," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 143-157.
    12. Pedro Bação & António Portugal Duarte & Helder Sebastião & Srdjan Redzepagic, 2018. "Information Transmission Between Cryptocurrencies: Does Bitcoin Rule the Cryptocurrency World?," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 65(2), pages 97-117, June.
    13. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    14. Milunovich, George & Lee, Seung Ah, 2022. "Measuring the impact of digital exchange cyberattacks on Bitcoin Returns," Economics Letters, Elsevier, vol. 221(C).
    15. Choi, Sangyup & Shin, Junhyeok, 2022. "Bitcoin: An inflation hedge but not a safe haven," Finance Research Letters, Elsevier, vol. 46(PB).
    16. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Predictability of crypto returns: The impact of trading behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    17. Zhou, Siwen, 2018. "Exploring the Driving Forces of the Bitcoin Exchange Rate Dynamics: An EGARCH Approach," MPRA Paper 89445, University Library of Munich, Germany.
    18. Ji Ho Kwon, 2021. "On the factors of Bitcoin’s value at risk," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    19. Tiwari, Aviral Kumar & Adewuyi, Adeolu O. & Albulescu, Claudiu T. & Wohar, Mark E., 2020. "Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    20. Figà-Talamanca, Gianna & Focardi, Sergio & Patacca, Marco, 2021. "Regime switches and commonalities of the cryptocurrencies asset class," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:61:y:2023:i:4:d:10.1007_s10614-022-10262-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.