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Overconfident agents and evolving financial networks

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Abstract

In this paper, we investigate the impact of agent personality on the complex dynamics taking place in financial markets. Leveraging recent findings, we model the artificial financial market as a complex evolving network: we consider discrete dynamics for the node state variables, which are updated at each trading session, while the edge state variables, which define a network of mutual influence, evolve continuously with time. This evolution depends on the way the agents rank their trading abilities in the network. By means of extensive numerical simulations in selected scenarios, we shed light on the role of overconfident agents in shaping the emerging network topology, thus impacting on the overall market dynamics.

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Acknowledgements

The authors wish to thank Prof. Franco Garofalo for the fruitful discussion and insightful suggestions.

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Authors and Affiliations

  1. Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125, Naples, Italy

    Pietro De Lellis, Anna Di Meglio & Francesco Lo Iudice

Authors
  1. Pietro De Lellis
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  2. Anna Di Meglio
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  3. Francesco Lo Iudice
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Correspondence to Anna Di Meglio.

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De Lellis, P., Di Meglio, A. & Lo Iudice, F. Overconfident agents and evolving financial networks. Nonlinear Dyn 92, 33–40 (2018). https://doi.org/10.1007/s11071-017-3780-y

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