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Super-Exponential Endogenous Bubbles in an Equilibrium Model of Fundamentalist and Chartist Traders

Author

Listed:
  • Taisei KAIZOJI

    (International Christian University)

  • Matthias LEISS

    (ETH Zurich)

  • Alexander I. SAICHEV

    (ETH Zurich and Nizhni Novgorod State University)

  • Didier SORNETTE

    (Swiss Finance Institute and ETH Zürich)

Abstract

We introduce a model of super-exponential financial bubbles with two assets (risky and risk-free), in which fundamentalist and chartist traders co-exist. Fundamentalists form expectations on the return and risk of a risky asset and maximize their constant relative risk aversion expected utility with respect to their allocation on the risky asset versus the risk-free asset. Chartists are subjected to social imitation and follow momentum trading. Allowing for random time-varying herding propensity, we are able to reproduce several well-known stylized facts of financial markets such as a fat-tail distribution of returns and volatility clustering. In particular, we observe transient faster-than-exponential bubble growth with approximate log-periodic behavior and give analytical arguments why this follows from our framework. The model accounts well for the behavior of traders and for the price dynamics that developed during the dotcom bubble in 1995-2000. Momentum strategies are shown to be transiently profitable, supporting these strategies as enhancing herding behavior.

Suggested Citation

  • Taisei KAIZOJI & Matthias LEISS & Alexander I. SAICHEV & Didier SORNETTE, 2015. "Super-Exponential Endogenous Bubbles in an Equilibrium Model of Fundamentalist and Chartist Traders," Swiss Finance Institute Research Paper Series 15-07, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp1507
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    Cited by:

    1. T. T. Chen & B. Zheng & Y. Li & X. F. Jiang, 2017. "New approaches in agent-based modeling of complex financial systems," Papers 1703.06840, arXiv.org.
    2. Ardila-Alvarez, Diego & Forro, Zalan & Sornette, Didier, 2021. "The acceleration effect and Gamma factor in asset pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    3. Li Lin & Didier Sornette, 2023. "The inverse Cox-Ingersoll-Ross process for parsimonious financial price modeling," Papers 2302.11423, arXiv.org, revised Jun 2023.
    4. Andreas Hefti & Steve Heinke & Frédéric Schneider, 2016. "Mental capabilities, trading styles, and asset market bubbles: theory and experiment," ECON - Working Papers 234, Department of Economics - University of Zurich.
    5. Rebecca Westphal & Didier Sornette, 2020. "How market intervention can prevent bubbles and crashes," Swiss Finance Institute Research Paper Series 20-74, Swiss Finance Institute.
    6. Kononovicius, Aleksejus & Ruseckas, Julius, 2019. "Order book model with herd behavior exhibiting long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 171-191.
    7. Antoine Kopp & Rebecca Westphal & Didier Sornette, 2022. "Agent-based model generating stylized facts of fixed income markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(4), pages 947-992, October.
    8. Aleksejus Kononovicius & Vygintas Gontis, 2019. "Approximation of the first passage time distribution for the birth-death processes," Papers 1902.00924, arXiv.org.
    9. Rebecca Westphal & Didier Sornette, 2019. "Market Impact and Performance of Arbitrageurs of Financial Bubbles in An Agent-Based Model," Swiss Finance Institute Research Paper Series 19-29, Swiss Finance Institute.
    10. Rebecca Westphal & Didier Sornette, 2024. "How Market Intervention can Prevent Bubbles and Crashes: An Agent Based Modelling Approach," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1315-1356, September.
    11. Li, Zhuolei & Diao, Xundi & Wu, Chongfeng, 2022. "The influence of mobile trading on return dispersion and herding behavior," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    12. Cafferata, Alessia & Tramontana, Fabio, 2022. "Disposition Effect and its outcome on endogenous price fluctuations," MPRA Paper 113904, University Library of Munich, Germany.
    13. Rytis Kazakeviv{c}ius & Aleksejus Kononovicius, 2023. "Anomalous diffusion and long-range memory in the scaled voter model," Papers 2301.08088, arXiv.org, revised Feb 2023.
    14. Li Lin & Didier Sornette, 2015. ""Speculative Influence Network" during financial bubbles: application to Chinese Stock Markets," Papers 1510.08162, arXiv.org.
    15. Westphal, Rebecca & Sornette, Didier, 2020. "Market impact and performance of arbitrageurs of financial bubbles in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 1-23.
    16. Chen, Ting-Ting & Zheng, Bo & Li, Yan & Jiang, Xiong-Fei, 2018. "Information driving force and its application in agent-based modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 593-601.

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    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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