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Asset price bubbles and crashes with near-zero-intelligence traders

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Author Info

  • John Duffy
  • M. Ünver

Abstract

We examine whether a simple agent-based model can generate asset price bubbles and crashes of the type observed in a series of laboratory asset market experiments beginning with the work of Smith, Suchanek and Williams (1988). We follow the methodology of Gode and Sunder (1993, 1997) and examine the outcomes that obtain when populations of zero-intelligence (ZI) budget constrained, artificial agents are placed in the various laboratory market environments that have given rise to price bubbles. We have to put more structure on the behavior of the ZI-agents in order to address features of the laboratory asset bubble environment. We show that our model of “near-zero-intelligence” traders, operating in the same double auction environments used in several different laboratory studies, generates asset price bubbles and crashes comparable to those observed in laboratory experiments and can also match other, more subtle features of the experimental data. Copyright Springer-Verlag Berlin/Heidelberg 2006

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File URL: http://hdl.handle.net/10.1007/s00199-004-0570-9
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Bibliographic Info

Article provided by Springer in its journal Economic Theory.

Volume (Year): 27 (2006)
Issue (Month): 3 (04)
Pages: 537-563

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Handle: RePEc:spr:joecth:v:27:y:2006:i:3:p:537-563

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Web page: http://link.springer.de/link/service/journals/00199/index.htm

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Related research

Keywords: Bubbles; Zero-intelligence traders; Double auction; Agent-based models; Experimental economics.;

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Cited by:
  1. Ross M. Miller, 2003. "Don't Let Your Robots Grow Up To Be Traders: Artificial Intelligence, Human Intelligence, and Asset-Market Bubbles," Experimental 0306001, EconWPA.
  2. Dan Ladley & Klaus Reiner Schenk-Hoppe, 2007. "Do Stylised Facts of Order Book Markets Need Strategic Behaviour?," Swiss Finance Institute Research Paper Series 07-20, Swiss Finance Institute.
  3. Jakob Grazzini, 2013. "Information dissemination in an experimentally based agent-based stock market," Journal of Economic Interaction and Coordination, Springer, vol. 8(1), pages 179-209, April.
  4. John Duffy, 2004. "Agent-Based Models and Human Subject Experiments," Computational Economics 0412001, EconWPA.
  5. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
  6. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
  7. Giusti, Giovanni & Jiang, Janet Hua & Xu, Yiping, 2012. "Eliminating Laboratory Asset Bubbles by Paying Interest on Cash," MPRA Paper 37321, University Library of Munich, Germany.
  8. Feldman, Todd & Friedman, Daniel, 2008. "Humans, Robots and Market Crashes: A Laboratory Study ∗," Santa Cruz Department of Economics, Working Paper Series qt4kf382p6, Department of Economics, UC Santa Cruz.

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