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Phase coexistence in a forecasting game

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  • Philippe Curty
  • Matteo Marsili

Abstract

Individual choices are either based on personal experience or on information provided by peers. The latter case, causes individuals to conform to the majority in their neighborhood. Such herding behavior may be very efficient in aggregating disperse private information, thereby revealing the optimal choice. However if the majority relies on herding, this mechanism may dramatically fail to aggregate correctly the information, causing the majority adopting the wrong choice. We address these issues in a simple model of interacting agents who aim at giving a correct forecast of a public variable, either seeking private information or resorting to herding. As the fraction of herders increases, the model features a phase transition beyond which a state where most agents make the correct forecast coexists with one where most of them are wrong. Simple strategic considerations suggest that indeed such a system of agents self-organizes deep in the coexistence region. There, agents tend to agree much more among themselves than with what they aim at forecasting, as found in recent empirical studies.

Suggested Citation

  • Philippe Curty & Matteo Marsili, 2005. "Phase coexistence in a forecasting game," Papers physics/0506151, arXiv.org, revised Feb 2006.
    • Handle: RePEc:arx:papers:physics/0506151
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    Cited by:

    1. Sungmin Lee & Verónica C Ramenzoni & Petter Holme, 2010. "Emergence of Collective Memories," PLOS ONE, Public Library of Science, vol. 5(9), pages 1-7, September.
    2. Christian Borghesi & Jean-Philippe Bouchaud, 2007. "Of songs and men: a model for multiple choice with herding," Quality & Quantity: International Journal of Methodology, Springer, vol. 41(4), pages 557-568, August.
    3. Jacopo Rocchi & Enoch Yan Lok Tsui & David Saad, 2017. "Emerging interdependence between stock values during financial crashes," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-15, May.
    4. Jean-Philippe Bouchaud & J. Doyne Farmer & Fabrizio Lillo, 2008. "How markets slowly digest changes in supply and demand," Papers 0809.0822, arXiv.org.
    5. Pietro DeLellis & Anna DiMeglio & Franco Garofalo & Francesco Lo Iudice, 2017. "The evolving cobweb of relations among partially rational investors," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-21, February.
    6. Jean-Philippe Bouchaud, 2012. "Crises and collective socio-economic phenomena: simple models and challenges," Papers 1209.0453, arXiv.org, revised Dec 2012.
    7. Veglio, A. & Marsili, M., 2007. "Stochastic analysis of an agent-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 631-636.

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