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Price overreactions in the cryptocurrency market

Author

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  • Guglielmo Maria Caporale
  • Alex Plastun

Abstract

Purpose - The purpose of this paper is to examine price overreactions in the case of the following cryptocurrencies: bitcoin, litecoin, ripple and dash. Design/methodology/approach - A number of parametric (t-test, ANOVA, regression analysis with dummy variables) and non-parametric (Mann–WhitneyU-test) tests confirm the presence of price patterns after overreactions: the next day price changes in both directions are bigger than after “normal” days. A trading robot approach is then used to establish whether these statistical anomalies can be exploited to generate profits. Findings - The results suggest that a strategy based on counter-movements after overreactions is not profitable, whilst one based on inertia appears to be profitable but produces outcomes not statistically different from the random ones. Therefore, the overreactions detected in the cryptocurrency market do not give rise to exploitable profit opportunities (possibly because of transaction costs) and cannot be seen as evidence against the efficient market hypothesis (EMH). Originality/value - The overreactions detected in the cryptocurrency market do not give rise to exploitable profit opportunities (possibly because of transaction costs) and cannot be seen as evidence against the EMH.

Suggested Citation

  • Guglielmo Maria Caporale & Alex Plastun, 2019. "Price overreactions in the cryptocurrency market," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(5), pages 1137-1155, August.
    • Handle: RePEc:eme:jespps:jes-09-2018-0310
    DOI: 10.1108/JES-09-2018-0310
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    Cited by:

    1. AlKhazali, Osamah & Kirimhan, Destan & Rabbani, Mustafa Raza & Billah, Syed Mabruk & Shaik, Muneer, 2025. "Cryptocurrencies and alternative bonds: Novel evidence on co-movement and risk sharing," Global Finance Journal, Elsevier, vol. 67(C).
    2. Zaremba, Adam & Bilgin, Mehmet Huseyin & Long, Huaigang & Mercik, Aleksander & Szczygielski, Jan J., 2021. "Up or down? Short-term reversal, momentum, and liquidity effects in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 78(C).
    3. Dima Cristina & Dobrea Catalin Razvan & Moncea Madalina Ioana & Ion Eduard Laurentiu, 2025. "Cryptocurrency Management from the Beginning to the Present," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 19(1), pages 331-340.
    4. Borgards, Oliver & Czudaj, Robert L., 2020. "The prevalence of price overreactions in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    5. Plastun, Alex & Bouri, Elie & Gupta, Rangan & Ji, Qiang, 2022. "Price effects after one-day abnormal returns in developed and emerging markets: ESG versus traditional indices," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    6. Tomas Pečiulis & Nisar Ahmad & Angeliki N. Menegaki & Aqsa Bibi, 2024. "Forecasting of cryptocurrencies: Mapping trends, influential sources, and research themes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1880-1901, September.
    7. Guglielmo Maria Caporale & Alex Plastun & Viktor Oliinyk, 2019. "Bitcoin fluctuations and the frequency of price overreactions," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 109-131, June.
    8. Parul Bhatia & Lipika Jain, 2025. "Lawful Sequence of Events and Cryptocurrency Anomalies: An Empirical Investigation," FIIB Business Review, , vol. 14(1), pages 71-88, January.
    9. Xin, Ling, 2024. "Short-term contrarian in the carbon emission market," Energy Economics, Elsevier, vol. 139(C).
    10. Guglielmo Maria Caporale & Alex Plastun, 2021. "Gold and oil prices: abnormal returns, momentum and contrarian effects," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 353-368, September.
    11. Borgards, Oliver & Czudaj, Robert L., 2021. "Features of overreactions in the cryptocurrency market," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 31-48.
    12. Plastun, Alex & Sibande, Xolani & Gupta, Rangan & Ji, Qiang, 2024. "Price effects after one-day abnormal returns and crises in the stock markets," Research in International Business and Finance, Elsevier, vol. 70(PA).
    13. Plastun, Alex & Sibande, Xolani & Gupta, Rangan & Wohar, Mark E., 2021. "Evolution of price effects after one-day abnormal returns in the US stock market," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    14. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    15. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & Lingbo Li & David Martinez-Regoband & Fan Wu, 2020. "Cryptocurrency Trading: A Comprehensive Survey," Papers 2003.11352, arXiv.org, revised Jan 2022.
    16. Guglielmo Maria Caporale & Alex Plastun, 2020. "Momentum effects in the cryptocurrency market after one-day abnormal returns," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 251-266, September.
    17. Khuntia, Sashikanta & Pattanayak, J.K., 2018. "Adaptive market hypothesis and evolving predictability of bitcoin," Economics Letters, Elsevier, vol. 167(C), pages 26-28.
    18. Caporale, Guglielmo Maria & Kang, Woo-Young & Spagnolo, Fabio & Spagnolo, Nicola, 2021. "Cyber-attacks, spillovers and contagion in the cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).

    More about this item

    Keywords

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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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