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Impact of Liquidity and Investors Sentiment on Herd Behavior in Cryptocurrency Market

Author

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  • Siniša Bogdan

    (Faculty of Tourism and Hospitality Management, University of Rijeka, 51000 Rijeka, Croatia)

  • Natali Brmalj

    (Faculty of Tourism and Hospitality Management, University of Rijeka, 51000 Rijeka, Croatia)

  • Elvis Mujačević

    (Faculty of Tourism and Hospitality Management, University of Rijeka, 51000 Rijeka, Croatia)

Abstract

This research addresses the impact of individual investors on the cryptocurrency market, focusing specifically on the development of herd behavior. Although the phenomenon of herd behavior has been studied extensively in the stock market, it has received limited research in the context of cryptocurrencies. This study aims to fill this research gap by examining the impact of liquidity and sentiment on herd behavior using the CSAD model, considering small, medium, and large cryptocurrencies. The results show different outcomes for cryptocurrencies of different sizes, consistently demonstrating that the herding effect is more pronounced under conditions of lower liquidity, as determined by the turnover volume and liquidity ratio of cryptocurrencies. Proxy measures such as the Twitter Hedonometer and CBOE VIX were used to measure investor sentiment and show the prevalence of herding behavior in optimistic times for all cryptocurrencies, regardless of their market capitalization. Consequently, this study provides valuable insights into the manifestation of herd behavior in the cryptocurrency market and highlights the importance of liquidity and sentiment as influencing factors. These findings improve our understanding of investor behavior and provide guidance to market participants and policymakers on how to effectively manage the risks associated with herd effects.

Suggested Citation

  • Siniša Bogdan & Natali Brmalj & Elvis Mujačević, 2023. "Impact of Liquidity and Investors Sentiment on Herd Behavior in Cryptocurrency Market," IJFS, MDPI, vol. 11(3), pages 1-17, July.
  • Handle: RePEc:gam:jijfss:v:11:y:2023:i:3:p:97-:d:1207442
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    References listed on IDEAS

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    1. Chang, Eric C. & Cheng, Joseph W. & Khorana, Ajay, 2000. "An examination of herd behavior in equity markets: An international perspective," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1651-1679, October.
    2. Elie Bouri & Riza Demirer & Rangan Gupta & Jacobus Nel, 2021. "COVID-19 Pandemic and Investor Herding in International Stock Markets," Risks, MDPI, vol. 9(9), pages 1-11, September.
    3. Ah Mand, Abdollah & Sifat, Imtiaz, 2021. "Static and regime-dependent herding behavior: An emerging market case study," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    4. Fu, Jingxue & Wu, Lan, 2021. "Regime-switching herd behavior: Novel evidence from the Chinese A-share market," Finance Research Letters, Elsevier, vol. 39(C).
    5. Ki-Hong Choi & Seong-Min Yoon, 2020. "Investor Sentiment and Herding Behavior in the Korean Stock Market," IJFS, MDPI, vol. 8(2), pages 1-14, June.
    6. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    7. Obryan Poyser, 2018. "Herding behavior in cryptocurrency markets," Papers 1806.11348, arXiv.org, revised Nov 2018.
    8. Natividad Blasco & Pilar Corredor & Elena Ferrer, 2018. "Analysts herding: when does sentiment matter?," Applied Economics, Taylor & Francis Journals, vol. 50(51), pages 5495-5509, November.
    9. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    10. Stavroyiannis, Stavros & Babalos, Vassilios, 2019. "Herding behavior in cryptocurrencies revisited: Novel evidence from a TVP model," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 57-63.
    11. Syed Jawad Hussain Shahzad & Elie Bouri & Jose Arreola-Hernandez & David Roubaud & Stelios Bekiros, 2019. "Spillover across Eurozone credit market sectors and determinants," Applied Economics, Taylor & Francis Journals, vol. 51(59), pages 6333-6349, December.
    12. Angerer, Martin & Hoffmann, Christian Hugo & Neitzert, Florian & Kraus, Sascha, 2021. "Objective and subjective risks of investing into cryptocurrencies," Finance Research Letters, Elsevier, vol. 40(C).
    13. El Mehdi Ferrouhi, 2021. "Herding Behavior in the Moroccan Stock Exchange," Journal of African Business, Taylor & Francis Journals, vol. 22(3), pages 309-319, July.
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