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How to grow a bubble: A model of myopic adapting agents

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  • Harras, Georges
  • Sornette, Didier

Abstract

We present a simple agent-based model to study the development of a bubble and the consequential crash and investigate how their proximate triggering factor might relate to their fundamental mechanism, and vice versa. Our agents invest according to their opinion on future price movements, which is based on three sources of information, (i) public information, i.e. news, (ii) information from their “friendship” network and (iii) private information. Our bounded rational agents continuously adapt their trading strategy to the current market regime by weighting each of these sources of information in their trading decision according to its recent predicting performance. We find that bubbles originate from a random lucky streak of positive news, which, due to a feedback mechanism of these news on the agents’ strategies develop into a transient collective herding regime. After this self-amplified exuberance, the price has reached an unsustainable high value, being corrected by a crash, which brings the price even below its fundamental value. These ingredients provide a simple mechanism for the excess volatility documented in financial markets. Paradoxically, it is the attempt for investors to adapt to the current market regime which leads to a dramatic amplification of the price volatility. A positive feedback loop is created by the two dominating mechanisms (adaptation and imitation) which, by reinforcing each other, result in bubbles and crashes. The model offers a simple reconciliation of the two opposite (herding versus fundamental) proposals for the origin of crashes within a single framework and justifies the existence of two populations in the distribution of returns, exemplifying the concept that crashes are qualitatively different from the rest of the price moves.

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  • Harras, Georges & Sornette, Didier, 2011. "How to grow a bubble: A model of myopic adapting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 80(1), pages 137-152.
  • Handle: RePEc:eee:jeborg:v:80:y:2011:i:1:p:137-152
    DOI: 10.1016/j.jebo.2011.03.003
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    Cited by:

    1. 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.
    2. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    3. Krause, Sebastian M. & Bornholdt, Stefan, 2013. "Spin models as microfoundation of macroscopic market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4048-4054.
    4. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2015. "Markets, herding and response to external information," Papers 1506.03708, arXiv.org, revised Jun 2015.
    5. 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.
    6. Егорова Людмила Геннадьевна, 2014. "Эффективность Торговых Стратегий Мелких Трейдеров," Проблемы управления, CyberLeninka;Общество с ограниченной ответственностью "СенСиДат-Контрол", issue 5, pages 34-41.
    7. Mark Setterfield & Bill Gibson, 2013. "Real and financial crises: A multi-agent approach," Working Papers 1309, Trinity College, Department of Economics, revised Jul 2014.
    8. 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.
    9. repec:eee:jeborg:v:137:y:2017:i:c:p:232-258 is not listed on IDEAS
    10. repec:gam:jrisks:v:5:y:2017:i:3:p:37-:d:105098 is not listed on IDEAS
    11. Torsten Trimborn & Philipp Otte & Simon Cramer & Max Beikirch & Emma Pabich & Martin Frank, 2018. "SABCEMM-A Simulation Framework for Agent-Based Computational Economic Market Models," Papers 1801.01811, arXiv.org.
    12. Jean-Philippe Bouchaud, 2012. "Crises and collective socio-economic phenomena: simple models and challenges," Papers 1209.0453, arXiv.org, revised Dec 2012.
    13. repec:kap:compec:v:51:y:2018:i:4:d:10.1007_s10614-017-9655-y is not listed on IDEAS
    14. Vivien Lespagnol & Juliette Rouchier, 2014. "Trading volume and market efficiency: an Agent Based Model with heterogenous knowledge about fundamentals," AMSE Working Papers 1419, Aix-Marseille School of Economics, Marseille, France, revised May 2014.
    15. Liudmila G. Egorova, 2014. "The Effectiveness Of Different Trading Strategies For Price-Takers," HSE Working papers WP BRP 29/FE/2014, National Research University Higher School of Economics.
    16. Alexey Vasilenko, 2017. "Should Monetary Authorities Prick Asset Price Bubbles? Evidence from a New Keynesian Model with an Agent-Based Financial Market," HSE Working papers WP BRP 182/EC/2017, National Research University Higher School of Economics.
    17. Yuri Biondi & Simone Righi, 2015. "Much ado about making money:The impact of disclosure, news and rumors over the formation of security market prices over time," Department of Economics 0075, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    18. Litimi, Houda & BenSaïda, Ahmed & Bouraoui, Omar, 2016. "Herding and excessive risk in the American stock market: A sectoral analysis," Research in International Business and Finance, Elsevier, vol. 38(C), pages 6-21.

    More about this item

    Keywords

    Stock market; Crash; Bubble; Herding; Adaptation; Agent-based model;

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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