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Herding, social network and volatility

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  • Wang, Guocheng
  • Wang, Yanyi

Abstract

Investors' expectations are highly influenced by their surroundings' opinions, especially from those who are believed as gurus. These opinion leaders (i.e., gurus) may manipulate the information when the information is disseminated to their followers. It is unclear whether herding behaviors will still emerge in this situation and if so, how these behaviors would influence the market volatility. In this paper, we model agents who choose either to follow the gurus with different precisions of information, or to be a chartist based on evolutionary considerations. Numerical simulations show that increasing the quality of gurus' private information would lead to more intensive herding behavior of followers and produce a U-shaped effect on the market volatility. Besides, increasing the proportion of gurus in the market would lead to more intensive herding but would decrease the market volatility. Interestingly, the market environment also affects investors' choices. Investors are more willing to herd on gurus in boom times or in depression. This paper sheds light on how informed gurus affect investors' behavior and market volatility through direct communication.

Suggested Citation

  • Wang, Guocheng & Wang, Yanyi, 2018. "Herding, social network and volatility," Economic Modelling, Elsevier, vol. 68(C), pages 74-81.
    • Handle: RePEc:eee:ecmode:v:68:y:2018:i:c:p:74-81
    DOI: 10.1016/j.econmod.2017.04.018
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    Cited by:

    1. Goldbaum, David, 2021. "The origins of influence," Economic Modelling, Elsevier, vol. 97(C), pages 380-396.
    2. Thomas Dierckx & Jesse Davis & Wim Schoutens, 2022. "Nowcasting Stock Implied Volatility with Twitter," Papers 2301.00248, arXiv.org.
    3. Nicolas, Maxime L.D., 2022. "Estimating a model of herding behavior on social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    4. Fei, Tianlun & Liu, Xiaoquan, 2021. "Herding and market volatility," International Review of Financial Analysis, Elsevier, vol. 78(C).
    5. Ooi Kok Loang & Zamri Ahmad, 2024. "Does Volatility Cause Herding in Malaysian Stock Market? Evidence from Quantile Regression Analysis," Millennial Asia, , vol. 15(2), pages 197-215, June.
    6. Huang, Chuangxia & Cai, Yaqian & Yang, Xiaoguang & Deng, Yanchen & Yang, Xin, 2023. "Laplacian-energy-like measure: Does it improve the Cross-Sectional Absolute Deviation herding model?," Economic Modelling, Elsevier, vol. 127(C).
    7. Boto-García, David & Leoni, Veronica, 2024. "Noisy signals: Does rating volatility depend on the length of the consumption span?," Economic Modelling, Elsevier, vol. 139(C).
    8. Gong, Qingbin & Diao, Xundi, 2023. "The impacts of investor network and herd behavior on market stability: Social learning, network structure, and heterogeneity," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1388-1398.

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    More about this item

    Keywords

    Heterogeneous beliefs; Herding; Social networks; Guru; Adaptive beliefs system; Market volatility.;
    All these keywords.

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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