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Heuristics in experiments with infinitely large strategy spaces

Author

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  • Jørgen Vitting Andersen

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Philippe de Peretti

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

We introduce a new methodology that enables detection of the onset of convergence towards Nash equilibria in simple repeated games with infinitely large strategy spaces, thereby revealing the heuristics used in decision-making. The method works by constraining on a special finite subset of strategies, called decoupled strategies. We show how the technique can be applied to understand price formation in financial market experiments by introducing a predictive measure ΔD: tthe different between positive decoupled strategies (recommending to buy) and negative decoupled strategies (recommending to sell). Using ΔD we illustrate how the method can predict (at certain special times) participants' actions with a high success rate in a series of experiments.

Suggested Citation

  • Jørgen Vitting Andersen & Philippe de Peretti, 2020. "Heuristics in experiments with infinitely large strategy spaces," Post-Print hal-02435934, HAL.
    • Handle: RePEc:hal:journl:hal-02435934
    DOI: 10.1016/j.jbusres.2019.12.034
    Note: View the original document on HAL open archive server: https://hal.science/hal-02435934
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