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Herding, Contrarianism and Delay in Financial Market Trading

Author

Listed:
  • Park, A.
  • Sgroi, D.

Abstract

Herding and contrarian behavior 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 significantly more pronounced than in compa- rable 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.

Suggested Citation

  • Park, A. & Sgroi, D., 2009. "Herding, Contrarianism and Delay in Financial Market Trading," Cambridge Working Papers in Economics 0941, Faculty of Economics, University of Cambridge.
    • Handle: RePEc:cam:camdae:0941
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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. Park, Andreas & Sgroi, Daniel, "undated". "Herding and Contrarian Behavior in Financial Markets: An Experimental Analysis," Economic Research Papers 269716, University of Warwick - Department of Economics.
    3. 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.
    4. 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.
    5. Dieter Nautz, "undated". "Herding in financial markets: Bridging the gap between theory and evidence," BDPEMS Working Papers 2013002, Berlin School of Economics.
    6. 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.
    7. Proto, Eugenio & Sgroi, Daniel, 2017. "Biased beliefs and imperfect information," Journal of Economic Behavior & Organization, Elsevier, vol. 136(C), pages 186-202.
    8. 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.
    9. 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.
    10. 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.
    11. 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).
    12. 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.
    13. repec:hum:wpaper:sfb649dp2013-036 is not listed on IDEAS
    14. repec:hum:wpaper:sfb649dp2014-029 is not listed on IDEAS
    15. 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.
    16. 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.

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    Keywords

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    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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