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A theoretical framework for trading experiments

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Author Info

  • Maxence Soumare

    (JAD - Laboratoire Jean Alexandre Dieudonné - CNRS : UMR6621 - Université Nice Sophia Antipolis (UNS))

  • Jørgen Vitting Andersen

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne)

  • Francis Bouchard

    (HEC - Institute for Applied Economics - HEC MONTRÉAL)

  • Alain Elkaim

    (HEC - Institute for Applied Economics - HEC MONTRÉAL)

  • Dominique Guegan

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne)

  • Justin Leroux

    ()
    (HEC - Institute for Applied Economics - HEC MONTRÉAL)

  • Michel Miniconi

    ()
    (JAD - Laboratoire Jean Alexandre Dieudonné - CNRS : UMR6621 - Université Nice Sophia Antipolis (UNS))

  • Lars Stentoft

    (HEC - Institute for Applied Economics - HEC MONTRÉAL)

Abstract

A general framework is suggested to describe human decision making in a certain class of experiments performed in a trading laboratory. We are in particular interested in discerning between two different moods, or states of the investors, corresponding to investors using fundemental investment strategies, technical analysis investment strategies respectively. Our framework accounts for two opposite situations already encountered in experimental setups : i) the rational expectations case, and ii) the case of pure speculation. We consider new experimental conditions which allow both elements to be present in the decision making process of the traders, thereby creating a dilemma in terms of investment strategy. Our theoretical framework allows us to predict the outcome of this type of trading experiments, depending on such variables as the number of people trading, the liquidity of the market, the amount of information used in technical analysis strategies, as well as the dividends attributed to an asset. We find that it is possible to give a qualitative prediction of trading behavior depending on a ratio that quantifies the fluctuations in the model.

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Bibliographic Info

Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00768898.

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Date of creation: Nov 2012
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Handle: RePEc:hal:cesptp:halshs-00768898

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Related research

Keywords: Decision making; game theory; complex systems theory; technical analysis; rational expectations;

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