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Market Stress and Herding: A New Approach to the Cryptocurrency Market

Author

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  • Gerson de Souza Raimundo Júnior
  • Rafael Baptista Palazzi
  • Ricardo de Souza Tavares
  • Marcelo Cabus Klotzle

Abstract

Herding is a feature of investor behavior in financial markets, particularly in market stress. We apply an approach based on the cross-sectional dispersion of individual stocks' betas, which allows us to extract herding patterns, using two dynamic methodologies to measure the herding phenomenon over time with a state-space model for the Cryptocurrency Market. The results reveal that herding toward the market shows significant movement, and persistence regardless of the market condition, expressed through the market index, market volatility, and the volatility index. When analyzing path herding is possible to observe that herding was intense during the investigated period. We also identify a positive relationship between herding and market stress.

Suggested Citation

  • Gerson de Souza Raimundo Júnior & Rafael Baptista Palazzi & Ricardo de Souza Tavares & Marcelo Cabus Klotzle, 2022. "Market Stress and Herding: A New Approach to the Cryptocurrency Market," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(1), pages 43-57, January.
    • Handle: RePEc:taf:hbhfxx:v:23:y:2022:i:1:p:43-57
    DOI: 10.1080/15427560.2020.1821688
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    Citations

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    Cited by:

    1. 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).
    2. Liu, Jian & Julaiti, Jiansuer & Gou, Shangde, 2024. "Decomposing interconnectedness: A study of cryptocurrency spillover effects in global financial markets," Finance Research Letters, Elsevier, vol. 61(C).
    3. Michael Cary, 2024. "Herding and investor sentiment after the cryptocurrency crash: evidence from Twitter and natural language processing," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-23, December.
    4. Cynthia Weiyi Cai & Rui Xue & Bi Zhou, 2023. "Cryptocurrency puzzles: a comprehensive review and re-introduction," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 46(1), pages 26-50, June.
    5. Chen, Yan & Zhang, Lei & Bouri, Elie, 2024. "Can a self-exciting jump structure better capture the jump behavior of cryptocurrencies? A comparative analysis with the S&P 500," Research in International Business and Finance, Elsevier, vol. 69(C).
    6. Bouri, Elie & Jalkh, Naji, 2023. "Spillovers of joint volatility-skewness-kurtosis of major cryptocurrencies and their determinants," International Review of Financial Analysis, Elsevier, vol. 90(C).
    7. Ko, Hyungjin & Son, Bumho & Lee, Jaewook, 2024. "Portfolio insurance strategy in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 67(PA).
    8. Filip, Angela Maria & Pochea, Maria Miruna, 2023. "Intentional and spurious herding behavior: A sentiment driven analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    9. Zhang, Lei & Bouri, Elie & Chen, Yan, 2023. "Co-jump dynamicity in the cryptocurrency market: A network modelling perspective," Finance Research Letters, Elsevier, vol. 58(PB).
    10. Chowdhury, Md Iftekhar Hasan & Hasan, Mudassar & Bouri, Elie & Tang, Yayan, 2024. "Emotional spillovers in the cryptocurrency market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    11. Scharnowski, Stefan & Shi, Yanghua, 2024. "Intraday herding and attention around the clock," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).

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