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Wealth distribution across communities of adaptive financial agents

Author

Listed:
  • Pietro DeLellis
  • Franco Garofalo
  • Francesco Lo Iudice
  • Elena Napoletano

Abstract

This paper studies the trading volumes and wealth distribution of a novel agent-based model of an artificial financial market. In this model, heterogeneous agents, behaving according to the Von Neumann and Morgenstern utility theory, may mutually interact. A Tobin-like tax (TT) on successful investments and a flat tax are compared to assess the effects on the agents' wealth distribution. We carry out extensive numerical simulations in two alternative scenarios: i) a reference scenario, where the agents keep their utility function fixed, and ii) a focal scenario, where the agents are adaptive and self-organize in communities, emulating their neighbours by updating their own utility function. Specifically, the interactions among the agents are modelled through a directed scale-free network to account for the presence of community leaders, and the herding-like effect is tested against the reference scenario. We observe that our model is capable of replicating the benefits and drawbacks of the two taxation systems and that the interactions among the agents strongly affect the wealth distribution across the communities. Remarkably, the communities benefit from the presence of leaders with successful trading strategies, and are more likely to increase their average wealth. Moreover, this emulation mechanism mitigates the decrease in trading volumes, which is a typical drawback of TTs.

Suggested Citation

  • Pietro DeLellis & Franco Garofalo & Francesco Lo Iudice & Elena Napoletano, 2015. "Wealth distribution across communities of adaptive financial agents," Papers 1509.01217, arXiv.org, revised Sep 2015.
  • Handle: RePEc:arx:papers:1509.01217
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    File URL: http://arxiv.org/pdf/1509.01217
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    References listed on IDEAS

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    1. N/A, 1999. "Index to International Regional Science Review," International Regional Science Review, , vol. 22(3), pages 354-355, December.
    2. Amilon, Henrik, 2008. "Estimation of an adaptive stock market model with heterogeneous agents," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 342-362, March.
    3. repec:cup:cbooks:9781107013445 is not listed on IDEAS
    4. M. Cristelli & L. Pietronero & A. Zaccaria, 2011. "Critical Overview of Agent-Based Models for Economics," Papers 1101.1847, arXiv.org.
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    Cited by:

    1. Khaldoun Khashanah & Talal Alsulaiman, 2017. "Connectivity, Information Jumps, and Market Stability: An Agent-Based Approach," Complexity, Hindawi, vol. 2017, pages 1-16, August.
    2. 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.

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