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Bubbles and Market Crashes

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  • Youssefmir, Michael
  • Huberman, Bernardo A
  • Hogg, Tad

Abstract

We present a dynamical theory of asset price bubbles that exhibits the appearance of bubbles and their subsequent crashes. We show that when speculative trends dominate over fundamental beliefs, bubbles form, leading to the growth of asset prices away from their fundamental value. This growth makes the system increasingly susceptible to any exogenous shock, thus eventually precipitating a crash. We also present computer experiments which in their aggregate behavior confirm the predictions of the theory. Citation Copyright 1998 by Kluwer Academic Publishers.

Suggested Citation

  • Youssefmir, Michael & Huberman, Bernardo A & Hogg, Tad, 1998. "Bubbles and Market Crashes," Computational Economics, Springer;Society for Computational Economics, vol. 12(2), pages 97-114, October.
    • Handle: RePEc:kap:compec:v:12:y:1998:i:2:p:97-114
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    Citations

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    Cited by:

    1. Helbing, Dirk & Kern, Daniel, 2000. "Non-equilibrium price theories," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(1), pages 259-268.
    2. Farmer, J. Doyne & Joshi, Shareen, 2002. "The price dynamics of common trading strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 149-171, October.
    3. Friedman, Daniel & Abraham, Ralph, 2008. "Bubblesandcrashes:Gradientdynamicsinfinancial markets," Santa Cruz Department of Economics, Working Paper Series qt3905j8kq, Department of Economics, UC Santa Cruz.
    4. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    5. Daniel Fricke & Thomas Lux, 2015. "The effects of a financial transaction tax in an artificial financial market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(1), pages 119-150, April.
    6. Feldman, Todd, 2010. "Portfolio manager behavior and global financial crises," Journal of Economic Behavior & Organization, Elsevier, vol. 75(2), pages 192-202, August.
    7. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    8. Efstathios Panayi & Gareth Peters, 2015. "Stochastic simulation framework for the Limit Order Book using liquidity motivated agents," Papers 1501.02447, arXiv.org, revised Jan 2015.
    9. Sornette, Didier & Zhou, Wei-Xing, 2006. "Importance of positive feedbacks and overconfidence in a self-fulfilling Ising model of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(2), pages 704-726.
    10. Ouyang, Min & Yu, Ming-Hui & Huang, Xiang-Zhao & Luan, En-Jie, 2008. "Emergency response to disaster-struck scale-free network with redundant systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(18), pages 4683-4691.
    11. Jason Childs, 2007. "Rate of Return Parity with Robot Asset Traders," Computational Economics, Springer;Society for Computational Economics, vol. 29(1), pages 1-12, February.
    12. Donangelo, R. & Hansen, A. & Sneppen, K. & Souza, S.R., 2000. "Physics of fashion fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 539-545.
    13. Friedman, Daniel & Abraham, Ralph, 2009. "Bubbles and crashes: Gradient dynamics in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 922-937, April.

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