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Imitation and contrarian behavior : hyperbolic bubbles, crashes and chaos

Author

Listed:
  • Anne Corcos

    (CRIISEA - Centre de Recherche sur les Institutions, l'Industrie et les Systèmes Économiques d'Amiens - UR UPJV 3908 - UPJV - Université de Picardie Jules Verne)

  • J.P. Eckmann
  • A. Malaspinas
  • Yannick Malevergne

    (LPMC - Laboratoire de physique de la matière condensée - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique, LSAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)

  • Didier Sornette

Abstract

Imitative and contrarian behaviours are the two typical opposite attitudes of investors in stock markets. We introduce a simple model to investigate their interplay in a stock market where agents can take only two states, bullish or bearish. Each bullish (bearish) agent polls m ‘friends' and changes her opinion to bearish (bullish) if (i) at least m ρ hb ( m ρ bh ) among the m agents inspected are bearish (bullish) or (ii) at least m ρ hh > m ρ hb ( m ρ bb > m ρ bh ) among the m agents inspected are bullish (bearish). The condition (i) ((ii)) corresponds to imitative (antagonistic) behaviour. In the limit where the number N of agents is infinite, the dynamics of the fraction of bullish agents is deterministic and exhibits chaotic behaviour in a significant domain of the parameter space {ρ hb ,ρ bh ,ρ hh ,ρ bb , m }. A typical chaotic trajectory is characterized by intermittent phases of chaos, quasi-periodic behaviour and super-exponentially growing bubbles followed by crashes. A typical bubble starts initially by growing at an exponential rate and then crosses over to a nonlinear power-law growth rate leading to a finite-time singularity. The reinjection mechanism provided by the contrarian behaviour introduces a finite-size effect, rounding off these singularities and leads to chaos. We document the main stylized facts of this model in the symmetric and asymmetric cases. This model is one of the rare agent-based models that give rise to interesting non-periodic complex dynamics in the ‘thermodynamic' limit (of an infinite number N of agents). We also discuss the case of a finite number of agents, which introduces an endogenous source of noise superimposed on the chaotic dynamics.

Suggested Citation

  • Anne Corcos & J.P. Eckmann & A. Malaspinas & Yannick Malevergne & Didier Sornette, 2002. "Imitation and contrarian behavior : hyperbolic bubbles, crashes and chaos," Post-Print hal-02312891, HAL.
  • Handle: RePEc:hal:journl:hal-02312891
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    Cited by:

    1. Hongler, Max-Olivier & Gallay, Olivier & Hülsmann, Michael & Cordes, Philip & Colmorn, Richard, 2010. "Centralized versus decentralized control—A solvable stylized model in transportation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(19), pages 4162-4171.
    2. Li Lin & Didier Sornette, 2009. "Diagnostics of Rational Expectation Financial Bubbles with Stochastic Mean-Reverting Termination Times," Papers 0911.1921, arXiv.org.
    3. Toth, Gabor & Galam, Serge, 2022. "Deviations from the majority: A local flip model," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    4. Егорова Людмила Геннадьевна, 2014. "Эффективность Торговых Стратегий Мелких Трейдеров," Проблемы управления, CyberLeninka;Общество с ограниченной ответственностью "СенСиДат-Контрол", issue 5, pages 34-41.
    5. Julia Gray, 2009. "International Organization as a Seal of Approval: European Union Accession and Investor Risk," American Journal of Political Science, John Wiley & Sons, vol. 53(4), pages 931-949, October.
    6. Didier Sornette & Ryan Woodard, 2009. "Financial Bubbles, Real Estate bubbles, Derivative Bubbles, and the Financial and Economic Crisis," Papers 0905.0220, arXiv.org.
    7. Lleo, Sébastien & Ziemba, William T., 2015. "Some historical perspectives on the Bond-Stock Earnings Yield Model for crash prediction around the world," International Journal of Forecasting, Elsevier, vol. 31(2), pages 399-425.
    8. Carmen Pellicer-Lostao & Ricardo Lopez-Ruiz, 2010. "Transition from Exponential to Power Law Distributions in a Chaotic Market," Papers 1011.5187, arXiv.org.
    9. BRATIAN Vasile & BUCUR Amelia, 2017. "The Development And The Current Status Of The Capital Market Hypotheses: A Few Benchmarks," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 69(1), pages 22-28, April.
    10. Shiryaev, Albert N. & Zhitlukhin, Mikhail N. & Ziemba, William T., 2014. "Land and stock bubbles, crashes and exit strategies in Japan circa 1990 and in 2013," LSE Research Online Documents on Economics 59288, London School of Economics and Political Science, LSE Library.
    11. Der Chyan Lin, 2013. "Synchrony in Broadband Fluctuation and the 2008 Financial Crisis," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-9, October.
    12. Westerhoff, Frank H., 2004. "Greed, fear and stock market dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 635-642.
    13. Deng, Lei & Liu, Yun & Xiong, Fei, 2013. "An opinion diffusion model with clustered early adopters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3546-3554.
    14. Jean-Philippe Bouchaud, 2002. "An introduction to statistical finance," Science & Finance (CFM) working paper archive 313238, Science & Finance, Capital Fund Management.
    15. Khalil, Nagi & Toral, Raúl, 2019. "The noisy voter model under the influence of contrarians," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 81-92.
    16. T. Kaizoji & M. Leiss & A. Saichev & D. Sornette, 2011. "Super-exponential endogenous bubbles in an equilibrium model of rational and noise traders," Papers 1109.4726, arXiv.org, revised Mar 2014.
    17. Kaizoji, Taisei & Leiss, Matthias & Saichev, Alexander & Sornette, Didier, 2015. "Super-exponential endogenous bubbles in an equilibrium model of fundamentalist and chartist traders," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 289-310.
    18. D. Sornette & R. Woodard, "undated". "Financial Bubbles, Real Estate bubbles, Derivative Bubbles, and the Financial and Economic Crisis," Working Papers CCSS-09-003, ETH Zurich, Chair of Systems Design.
    19. Damian Smug & Peter Ashwin & Didier Sornette, 2018. "Predicting financial market crashes using ghost singularities," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-20, March.
    20. Norman Schofield, 2015. "Climate Change, Collapse and Social Choice Theory," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 9(1), pages 007-035, October.
    21. Frederik Herzberg, 2008. "Black-Scholes theory for an underlying with multiple attractors," Quantitative Finance, Taylor & Francis Journals, vol. 8(5), pages 453-457.
    22. Patrick Bayer & Kyle Mangum & James W. Roberts, 2021. "Speculative Fever: Investor Contagion in the Housing Bubble," American Economic Review, American Economic Association, vol. 111(2), pages 609-651, February.
    23. Omurtag, Ahmet & Sirovich, Lawrence, 2006. "Modeling a large population of traders: Mimesis and stability," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 562-576, December.
    24. Lorenzo Zanello RIva, 2012. "El efecto día en cinco índices bursátiles de América Latina," Documentos Departamento de Economía 18081, Universidad del Norte.

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