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An analysis of investors’ behavior in Bitcoin market

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  • Delia-Elena Diaconaşu
  • Seyed Mehdian
  • Ovidiu Stoica

Abstract

As an emerging digital asset, Bitcoin has been traded for more than a decade, reaching an impressively high market capitalization and continuing to expand its volume of trading at a rapid pace. Many countries have legalized or are considering legalizing a trading platform for this asset, and a set of companies worldwide accept it as a medium of exchange. As a result of this expansion, many studies in finance literature have focused on studying the efficiency of this cryptocurrency. In line with this literature, this paper investigates, using the abnormal returns and abnormal trading volumes methodologies, the dynamics of investors’ reaction to the arrival of unexpected favorable and unfavorable information regarding the Bitcoin market in the context of the three famous hypotheses: the overreaction, the uncertain information, and the efficient market hypotheses. Overall, we find evidence confirming that the Bitcoin market tends to mature over time. More precisely, over the entire analyzed period, investors behave in accordance with the predictions of the uncertain information hypothesis when positive and negative events occur. However, splitting the timespan into sub-periods provides interesting insights. Remarkably in this respect is the fact that starting with the second sub-period, the response of investors in the Bitcoin market supports, in a moderate manner, the postulate of the efficient market hypothesis when favorable events are addressed. Moreover, our findings reveal that during the pandemic period, the efficiency of Bitcoin has increased, thus turning this stressful period into an advantage for this cryptocurrency. This improved market efficiency is also supported by the abnormal trading volume analysis.

Suggested Citation

  • Delia-Elena Diaconaşu & Seyed Mehdian & Ovidiu Stoica, 2022. "An analysis of investors’ behavior in Bitcoin market," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-18, March.
    • Handle: RePEc:plo:pone00:0264522
    DOI: 10.1371/journal.pone.0264522
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    References listed on IDEAS

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    1. Venelina Nikolova & Juan E. Trinidad Segovia & Manuel Fernández-Martínez & Miguel Angel Sánchez-Granero, 2020. "A Novel Methodology to Calculate the Probability of Volatility Clusters in Financial Series: An Application to Cryptocurrency Markets," Mathematics, MDPI, vol. 8(8), pages 1-15, July.
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    4. Celeste, Valerio & Corbet, Shaen & Gurdgiev, Constantin, 2020. "Fractal dynamics and wavelet analysis: Deep volatility and return properties of Bitcoin, Ethereum and Ripple," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 310-324.
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    Cited by:

    1. Ante, Lennart, 2023. "How Elon Musk's Twitter activity moves cryptocurrency markets," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    2. Naseem Al Rahahleh & Ahmed Al Qurashi, 2024. "The impact of COVID-19 on Ethereum returns and Ethereum market efficiency," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 14(3), pages 729-755, September.
    3. Hyeonoh Kim & Eojin Yi & Jooyoung Jeon & Taeyoung Park & Kwangwon Ahn, 2024. "After the Split: Market Efficiency of Bitcoin Cash," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 411-427, July.
    4. Beckmann, Joscha & Geldner, Teo & Wüstenfeld, Jan, 2024. "The relevance of media sentiment for small and large scale bitcoin investors," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    5. Ştefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2023. "Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-58, December.

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