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Fleeting extinction? Unraveling the persistence of noise traders in financial markets with learning and replacement

Author

Listed:
  • Luca Gerotto

    (Università Cattolica del Sacro Cuore)

  • Paolo Pellizzari

    (Ca’ Foscari University of Venice)

  • Marco Tolotti

    (Ca’ Foscari University of Venice)

Abstract

We describe an agent-based model of a financial market where agents can learn whether to buy costly information on returns, to use noise as if it were information, or to disregard any signals. We show that while learning alone drives all noise traders to extinction in stationary populations, allowing for small rates of replacement of existing agents with new ones suffices to generate substantial levels of persistent noise trading, with the equilibrium share of agents using irrelevant news reaching double digits. Remarkably, the presence of noise traders, when replacement is realistically considered, inflates the share of agents who use costly information relative to the benchmark scenario without replacement.

Suggested Citation

  • Luca Gerotto & Paolo Pellizzari & Marco Tolotti, 2025. "Fleeting extinction? Unraveling the persistence of noise traders in financial markets with learning and replacement," Journal of Evolutionary Economics, Springer, vol. 35(2), pages 355-379, April.
    • Handle: RePEc:spr:joevec:v:35:y:2025:i:2:d:10.1007_s00191-025-00892-y
    DOI: 10.1007/s00191-025-00892-y
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    More about this item

    Keywords

    Agent-based modeling; Asymmetric information; Bounded rationality; Information aggregation; Learning;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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