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Bubbles in hybrid markets: How expectations about algorithmic trading affect human trading

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  • Farjam, Mike
  • Kirchkamp, Oliver

Abstract

Bubbles are omnipresent in lab experiments with asset markets. Most of these experiments are conducted in environments with only human traders. Since today's markets are substantially determined by algorithmic trading, we use a laboratory experiment to measure how human trading depends on the expected presence of algorithmic traders. We find that bubbles are clearly smaller when human traders expect algorithmic traders to be present.

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  • Farjam, Mike & Kirchkamp, Oliver, 2018. "Bubbles in hybrid markets: How expectations about algorithmic trading affect human trading," Journal of Economic Behavior & Organization, Elsevier, vol. 146(C), pages 248-269.
    • Handle: RePEc:eee:jeborg:v:146:y:2018:i:c:p:248-269
    DOI: 10.1016/j.jebo.2017.11.011
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    2. Butler, David & Cheung, Stephen L., 2018. "Mind, Body, Bubble! Psychological and Biophysical Dimensions of Behavior in Experimental Asset Markets," IZA Discussion Papers 11563, Institute of Labor Economics (IZA).
    3. Chugunova, Marina & Sele, Daniela, 2022. "We and It: An interdisciplinary review of the experimental evidence on how humans interact with machines," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 99(C).
    4. Christoph March, 2019. "The Behavioral Economics of Artificial Intelligence: Lessons from Experiments with Computer Players," CESifo Working Paper Series 7926, CESifo.
    5. Farjam, Mike, 2019. "On whom would I want to depend; humans or computers?," Journal of Economic Psychology, Elsevier, vol. 72(C), pages 219-228.
    6. Normann, Hans-Theo & Sternberg, Martin, 2022. "Human-algorithm interaction: Algorithmic pricing in hybrid laboratory markets," DICE Discussion Papers 392, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    7. Qixuan Luo & Shijia Song & Handong Li, 2023. "Research on the Effects of Liquidation Strategies in the Multi-asset Artificial Market," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1721-1750, December.
    8. Normann, Hans-Theo & Sternberg, Martin, 2023. "Human-algorithm interaction: Algorithmic pricing in hybrid laboratory markets," European Economic Review, Elsevier, vol. 152(C).
    9. Owen Powell & Natalia Shestakova, 2017. "Experimental asset markets: behavior and bubbles," Chapters, in: Morris Altman (ed.), Handbook of Behavioural Economics and Smart Decision-Making, chapter 21, pages 375-391, Edward Elgar Publishing.
    10. Hans-Theo Normann & Martin Sternberg, 2021. "Human-Algorithm Interaction: Algorithmic Pricing in Hybrid Laboratory Markets," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2021_11, Max Planck Institute for Research on Collective Goods, revised 13 Apr 2022.
    11. Das, Sougata & Kadapakkam, Palani-Rajan, 2020. "Machine over Mind? Stock price clustering in the era of algorithmic trading," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    12. Kirchkamp, Oliver & Oechssler, Joerg & Sofianos, Andis, 2021. "The Binary Lottery Procedure does not induce risk neutrality in the Holt & Laury and Eckel & Grossman tasks," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 348-369.

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    More about this item

    Keywords

    Bubbles; Expectations; Experiment; Algorithmic traders;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles

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