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Volatility clustering and herding agents: does it matter what they observe?

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  • Ryuichi Yamamoto

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  • Ryuichi Yamamoto, 2011. "Volatility clustering and herding agents: does it matter what they observe?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(1), pages 41-59, May.
    • Handle: RePEc:spr:jeicoo:v:6:y:2011:i:1:p:41-59
    DOI: 10.1007/s11403-010-0075-5
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    21. Routledge, Bryan R, 1999. "Adaptive Learning in Financial Markets," The Review of Financial Studies, Society for Financial Studies, vol. 12(5), pages 1165-1202.
    22. Brenner, Thomas, 2006. "Agent Learning Representation: Advice on Modelling Economic Learning," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 18, pages 895-947, Elsevier.
    23. Pingle, Mark & Day, Richard H., 1996. "Modes of economizing behavior: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 29(2), pages 191-209, March.
    24. Blake LeBaron & Ryuichi Yamamoto, 2008. "The Impact of Imitation on Long Memory in an Order-Driven Market," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 34(4), pages 504-517.
    25. LeBaron, Blake & Yamamoto, Ryuichi, 2007. "Long-memory in an order-driven market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 85-89.
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    Cited by:

    1. Sunyoung Lee & Keun Lee, 2021. "3% rules the market: herding behavior of a group of investors, asset market volatility, and return to the group in an agent-based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 359-380, April.
    2. Lu, Jingen & Chen, Xiaohong & Liu, Xiaoxing, 2018. "Stock market information flow: Explanations from market status and information-related behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 837-848.
    3. Pengfei Wang & Wei Zhang & Xiao Li & Dehua Shen, 2019. "Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 377-418, June.

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    More about this item

    Keywords

    Agent-based; Learning; Volatility clustering; Herding; G12; G14; D83;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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