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Herding, contrarianism and delay in financial market trading

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  • Park, Andreas
  • Sgroi, Daniel

Abstract

Herding and contrarian behaviour are often-cited features of real-world financial markets. Theoretical models of continuous trading that study herding and contrarianism, however, usually do not allow traders to choose when to trade or to trade more than once. We present a large-scale experiment to explore these features within a tightly controlled laboratory environment. Herding and contrarianism are more pronounced than in comparable studies that do not allow traders to time their decisions. Traders with extreme information tend to trade earliest, followed by those with information conducive to contrarianism, while those with the theoretical potential to herd delay the most. A sizeable fraction of trades is clustered in time.

Suggested Citation

  • Park, Andreas & Sgroi, Daniel, 2012. "Herding, contrarianism and delay in financial market trading," European Economic Review, Elsevier, vol. 56(6), pages 1020-1037.
    • Handle: RePEc:eee:eecrev:v:56:y:2012:i:6:p:1020-1037
    DOI: 10.1016/j.euroecorev.2012.04.006
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    Cited by:

    1. Allen, Franklin & Haas, Marlene D. & Nowak, Eric & Tengulov, Angel, 2021. "Market efficiency and limits to arbitrage: Evidence from the Volkswagen short squeeze," Journal of Financial Economics, Elsevier, vol. 142(1), pages 166-194.
    2. Jason Shachat & Anand Srinivasan, 2022. "Informational Price Cascades and Non-Aggregation of Asymmetric Information in Experimental Asset Markets," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(4), pages 388-407, November.
    3. Park, A. & Sgroi, D., 2009. "Herding and Contrarian Behavior in Financial Markets: An Experimental Analysis," Cambridge Working Papers in Economics 0938, Faculty of Economics, University of Cambridge.
    4. Christopher Boortz & Simon Jurkatis & Stephanie Kremer & Dieter Nautz, 2013. "Institutional Herding in Financial Markets: New Evidence through the Lens of a Simulated Model," Discussion Papers of DIW Berlin 1336, DIW Berlin, German Institute for Economic Research.
    5. Dieter Nautz, "undated". "Herding in financial markets: Bridging the gap between theory and evidence," BDPEMS Working Papers 2013002, Berlin School of Economics.
    6. Puput Tri Komalasari & Marwan Asri & Bernardinus M. Purwanto & Bowo Setiyono, 2022. "Herding behaviour in the capital market: What do we know and what is next?," Management Review Quarterly, Springer, vol. 72(3), pages 745-787, September.
    7. Youzong Xu & Bo Li, 2017. "Behavioral heterogeneity and financial markets: Locked/crossed quotes under informationally efficient pricing," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1384524-138, January.
    8. Meneguzzer, Claudio, 2022. "Day-to-day dynamics in a simple traffic network with mixed direct and contrarian route choice behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    9. Boortz, Christopher & Kremer, Stephanie & Jurkatis, Simon & Nautz, Dieter, 2014. "Information risk, market stress and institutional herding in financial markets: New evidence through the lens of a simulated model," SFB 649 Discussion Papers 2014-029, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Christopher M Wray & Steven R Bishop, 2016. "A Financial Market Model Incorporating Herd Behaviour," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-28, March.
    11. Jing Zhang & Wei Zhang & Yuelei Li & Shuxing Yin, 2021. "Seeking excess returns under a posted price mechanism: Evidence from a peer‐to‐peer lending market," Manchester School, University of Manchester, vol. 89(5), pages 486-506, September.
    12. Lukas Meub & Till Proeger & Hendrik Hüning, 2017. "A comparison of endogenous and exogenous timing in a social learning experiment," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(1), pages 143-166, April.
    13. Proto, Eugenio & Sgroi, Daniel, 2017. "Biased beliefs and imperfect information," Journal of Economic Behavior & Organization, Elsevier, vol. 136(C), pages 186-202.
    14. Ivanov, Asen & Levin, Dan & Peck, James, 2013. "Behavioral biases in endogenous-timing herding games: An experimental study," Journal of Economic Behavior & Organization, Elsevier, vol. 87(C), pages 25-34.
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    More about this item

    Keywords

    Herding; Contrarianism; Endogenous-time trading; Experiments;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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