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Multiple-interaction kinetic modelling of a virtual-item gambling economy

Author

Listed:
  • Giuseppe Toscani
  • Andrea Tosin
  • Mattia Zanella

Abstract

In recent years, there has been a proliferation of online gambling sites, which made gambling more accessible with a consequent rise in related problems, such as addiction. Hence, the analysis of the gambling behaviour at both the individual and the aggregate levels has become the object of several investigations. In this paper, resorting to classical methods of the kinetic theory, we describe the behaviour of a multi-agent system of gamblers participating in lottery-type games on a virtual-item gambling market. The comparison with previous, often empirical, results highlights the ability of the kinetic approach to explain how the simple microscopic rules of a gambling-type game produce complex collective trends, which might be difficult to interpret precisely by looking only at the available data.

Suggested Citation

  • Giuseppe Toscani & Andrea Tosin & Mattia Zanella, 2019. "Multiple-interaction kinetic modelling of a virtual-item gambling economy," Papers 1904.07660, arXiv.org.
    • Handle: RePEc:arx:papers:1904.07660
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    References listed on IDEAS

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    1. Federico Bassetti & Giuseppe Toscani, 2010. "Explicit equilibria in a kinetic model of gambling," Papers 1002.3689, arXiv.org.
    2. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    3. Lorenzo Pareschi & Giuseppe Toscani, 2014. "Wealth distribution and collective knowledge. A Boltzmann approach," Papers 1401.4550, arXiv.org.
    4. Gualandi, Stefano & Toscani, Giuseppe, 2018. "Pareto tails in socio-economic phenomena: A kinetic description," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-17.
    5. Giuseppe Toscani, 2016. "Kinetic and mean field description of Gibrat's law," Papers 1606.04796, arXiv.org.
    6. Per Binde, 2013. "Why people gamble: a model with five motivational dimensions," International Gambling Studies, Taylor & Francis Journals, vol. 13(1), pages 81-97, April.
    7. Pareschi, Lorenzo & Toscani, Giuseppe, 2013. "Interacting Multiagent Systems: Kinetic equations and Monte Carlo methods," OUP Catalogue, Oxford University Press, number 9780199655465.
    8. Toscani, Giuseppe, 2016. "Kinetic and mean field description of Gibrat’s law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 802-811.
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    Cited by:

    1. G. Dimarco & L. Pareschi & G. Toscani & M. Zanella, 2020. "Wealth distribution under the spread of infectious diseases," Papers 2004.13620, arXiv.org.

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