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Price Overreactions in the Cryptocurrency Market

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  • Guglielmo Maria Caporale
  • Alex Plastun

Abstract

This paper examines price overreactions in the case of the following cryptocurrencies: BitCoin, LiteCoin, Ripple and Dash. A number of parametric (t-test, ANOVA, regression analysis with dummy variables) and non-parametric (Mann–Whitney U 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. 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).

Suggested Citation

  • Guglielmo Maria Caporale & Alex Plastun, 2018. "Price Overreactions in the Cryptocurrency Market," Discussion Papers of DIW Berlin 1718, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1718
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    References listed on IDEAS

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    1. Guglielmo Maria Caporale & Luis Gil-Alana & Alex Plastun, 2018. "Short-Term Price Overreactions: Identification, Testing, Exploitation," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 913-940, April.
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    Cited by:

    1. 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.
    2. Alex Plastun & Xolani Sibande & Rangan Gupta & Mark E. Wohar, 2020. "Evolution of Price Effects After One-Day of Abnormal Returns in the US Stock Market," Working Papers 202016, University of Pretoria, Department of Economics.
    3. Alex Plastun & Elie Bouri & Rangan Gupta, 2021. "Price Effects after One-Day Abnormal Returns in Developed and Emerging Markets: ESG versus Traditional Indices," Working Papers 202119, University of Pretoria, Department of Economics.
    4. 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).
    5. Fan Fang & Carmine Ventre & Michail Basios & Hoiliong Kong & Leslie Kanthan & Lingbo Li & David Martinez-Regoband & Fan Wu, 2020. "Cryptocurrency Trading: A Comprehensive Survey," Papers 2003.11352, arXiv.org, revised Jan 2021.
    6. 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.
    7. Khuntia, Sashikanta & Pattanayak, J.K., 2018. "Adaptive market hypothesis and evolving predictability of bitcoin," Economics Letters, Elsevier, vol. 167(C), pages 26-28.
    8. Guglielmo Maria Caporale & Woo-Young Kang & Fabio Spagnolo & Nicola Spagnolo, 2020. "Cyber Attacks, Spillovers and Contagion in the Cryptocurrency Markets," CESifo Working Paper Series 8324, CESifo.
    9. Guglielmo Maria Caporale & Alex Plastun, 2020. "Gold and Oil Prices: Abnormal Returns, Momentum and Contrarian Effects," CESifo Working Paper Series 8445, CESifo.

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    More about this item

    Keywords

    cryptocurrency market; Bitcoin; overreaction; momentum; abnormal returns; contrarian strategy; trading strategy; trading robot;
    All these keywords.

    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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