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Speculative Attacks: A Laboratory Study in Continuous Time

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  • Yin-Wong Cheung
  • Daniel Friedman

Abstract

We examine speculative attacks in a controlled laboratory environment featuring continuous time, size asymmetries, and varying amounts of public information. Attacks succeeded in 233 of 344 possible cases. When speculators have symmetric size and access to information: (a) weaker fundamentals increase the likelihood of successful speculative attacks and hasten their onset, and (b) contrary to some theory, success is enhanced by public access to information about either the net speculative position or the fundamentals. The presence of a larger speculator further enhances success, and experience with large speculators increases small speculators’ response to the public information. However, giving the large speculator increased size or better information does not significantly strengthen his impact.

Suggested Citation

  • Yin-Wong Cheung & Daniel Friedman, 2008. "Speculative Attacks: A Laboratory Study in Continuous Time," CESifo Working Paper Series 2420, CESifo.
  • Handle: RePEc:ces:ceswps:_2420
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    Cited by:

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    2. Bosch-Rosa, Ciril, 2018. "That's how we roll: An experiment on rollover risk," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 495-510.
    3. Tasneem, Dina & Engle-Warnick, Jim & Benchekroun, Hassan, 2017. "An experimental study of a common property renewable resource game in continuous time," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 91-119.
    4. Farshid Pourshahabi & Nazar Dahmardeh, 2015. "Economic Sanctions, Speculative Attacks and Currency Crisis," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 5(2), pages 340-355, February.
    5. von Hagen, Jürgen & Kube, Sebastian & Selten, Reinhard & Pope, Robin, 2006. "Experimental Evidence on the Benefits of Eliminating Exchange Rate Uncertainties and Why Expected Utility Theory causes Economists to Miss Them," Bonn Econ Discussion Papers 28/2006, University of Bonn, Bonn Graduate School of Economics (BGSE).
    6. Taketa, Kenshi & Suzuki-Löffelholz, Kumi & Arikawa, Yasuhiro, 2009. "Experimental analysis on the role of a large speculator in currency crises," Journal of Economic Behavior & Organization, Elsevier, vol. 72(1), pages 602-617, October.
    7. John Duffy, 2009. "Equilibrium Selection in Static and Dynamic Entry Games," Working Paper 376, Department of Economics, University of Pittsburgh, revised Dec 2011.
    8. Olga Shurchkov, 2013. "Coordination and learning in dynamic global games: experimental evidence," Experimental Economics, Springer;Economic Science Association, vol. 16(3), pages 313-334, September.
    9. Jacopo Magnani & David Munro, 2020. "Dynamic runs and circuit breakers: an experiment," Experimental Economics, Springer;Economic Science Association, vol. 23(1), pages 127-153, March.
    10. Schotter, Andrew & Yorulmazer, Tanju, 2009. "On the dynamics and severity of bank runs: An experimental study," Journal of Financial Intermediation, Elsevier, vol. 18(2), pages 217-241, April.
    11. Makoto Nirei & Theodoros Stamatiou & Vladyslav Sushko, 2012. "Stochastic Herding in Financial Markets Evidence from Institutional Investor Equity Portfolios," BIS Working Papers 371, Bank for International Settlements.
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    More about this item

    Keywords

    currency crisis; speculative attack; laboratory experiment; coordination game; pre-emption; large player;
    All these keywords.

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • F30 - International Economics - - International Finance - - - General

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