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Herding intensity and volatility in cryptocurrency markets during the COVID-19

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  • Evrim Mandaci, Pinar
  • Cagli, Efe Caglar

Abstract

This paper investigates whether herding is present before and during the COVID-19 pandemic, analyzing intraday data of Bitcoin and eight altcoins. The herding intensity measure of Patterson and Sharma (2006) is calculated for the first time for cryptocurrency markets. Furthermore, we employed a novel Granger causality methodology with a Fourier approximation to determine the relationship between herding and volatility, considering the structural breaks. Our results indicate a significant herding behavior, concentrating during the COVID-19 outbreak. The causality test results show that herding has a significant effect on market volatility. Our results do not support the efficient market hypothesis.

Suggested Citation

  • Evrim Mandaci, Pinar & Cagli, Efe Caglar, 2022. "Herding intensity and volatility in cryptocurrency markets during the COVID-19," Finance Research Letters, Elsevier, vol. 46(PB).
    • Handle: RePEc:eee:finlet:v:46:y:2022:i:pb:s1544612321003846
    DOI: 10.1016/j.frl.2021.102382
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    Cited by:

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    2. Mohamad, Azhar & Stavroyiannis, Stavros, 2022. "Do birds of a feather flock together? Evidence from time-varying herding behaviour of bitcoin and foreign exchange majors during Covid-19," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    3. Chowdhury, Mohammad Ashraful Ferdous & Abdullah, Mohammad & Masih, Mansur, 2022. "COVID-19 government interventions and cryptocurrency market: Is there any optimum portfolio diversification?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    4. Zhao, Yuan & Liu, Nan & Li, Wanpeng, 2022. "Industry herding in crypto assets," International Review of Financial Analysis, Elsevier, vol. 84(C).
    5. Ren, Boru & Lucey, Brian, 2023. "Herding in the Chinese renewable energy market: Evidence from a bootstrapping time-varying coefficient autoregressive model," Energy Economics, Elsevier, vol. 119(C).
    6. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2023. "Cryptocurrencies Are Becoming Part of the World Global Financial Market," Papers 2303.00495, arXiv.org.
    7. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2022. "Multifractal cross-correlations of bitcoin and ether trading characteristics in the post-COVID-19 time," Papers 2208.01445, arXiv.org.

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    More about this item

    Keywords

    Herding; Bitcoin; Cryptocurrencies; Behavioral finance; COVID-19;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G40 - Financial Economics - - Behavioral Finance - - - General

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