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Learning from Unrealized versus Realized Prices

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  • M. Kathleen Ngangoué
  • Georg Weizsäcker

Abstract

Our experiments investigate the extent to which traders learn from the price, differentiating between situations where orders are submitted before versus after the price has realized. In simultaneous markets with bids that are conditional on the price, traders neglect the information conveyed by the hypothetical value of the price. In sequential markets where the price is known prior to the bid submission, traders react to price to an extent that is roughly consistent with the benchmark theory. The difference's robustness to a number of variations provides insights about the drivers of this effect.

Suggested Citation

  • M. Kathleen Ngangoué & Georg Weizsäcker, 2021. "Learning from Unrealized versus Realized Prices," American Economic Journal: Microeconomics, American Economic Association, vol. 13(2), pages 174-201, May.
    • Handle: RePEc:aea:aejmic:v:13:y:2021:i:2:p:174-201
    DOI: 10.1257/mic.20180268
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    Cited by:

    1. Theo Offerman & Giorgia Romagnoli & Andreas Ziegler, 2022. "Why are open ascending auctions popular? The role of information aggregation and behavioral biases," Quantitative Economics, Econometric Society, vol. 13(2), pages 787-823, May.
    2. Koch, Christian & Penczynski, Stefan P., 2018. "The winner's curse: Conditional reasoning and belief formation," Journal of Economic Theory, Elsevier, vol. 174(C), pages 57-102.
    3. Marco Mantovani & Antonio Filippin, 2024. "When do prediction markets return average beliefs? Experimental evidence," Working Papers 532, University of Milano-Bicocca, Department of Economics.
    4. Hubert Janos Kiss & Ismael Rodriguez-Lara & Alfonso Rosa-Garcia, 2019. "Does response time predict withdrawal decisions? Lessons from a bank-run experiment," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 12(3), pages 200-222, November.
    5. Louis Golowich & Shengwu Li, 2021. "On the Computational Properties of Obviously Strategy-Proof Mechanisms," Papers 2101.05149, arXiv.org, revised Oct 2022.
    6. André Schmelzer, 2018. "Strategy-Proofness of Stochastic Assignment Mechanisms," The Journal of Mechanism and Institution Design, Society for the Promotion of Mechanism and Institution Design, University of York, vol. 3(1), pages 17-50, December.
    7. Kai Barron & Steffen Huck & Philippe Jehiel, 2024. "Everyday Econometricians: Selection Neglect and Overoptimism When Learning from Others," American Economic Journal: Microeconomics, American Economic Association, vol. 16(3), pages 162-198, August.
    8. Darius Schlangenotto & Wendelin Schnedler & Radovan Vadovič, 2020. "Against All Odds: Tentative Steps toward Efficient Information Sharing in Groups," Games, MDPI, vol. 11(3), pages 1-24, August.
    9. Moser, Johannes, 2017. "Hypothetical thinking and the winner's curse: An experimental investigation," University of Regensburg Working Papers in Business, Economics and Management Information Systems 36304, University of Regensburg, Department of Economics.
    10. Hitoshi Matsushima, 2017. "Framing Game Theory," CIRJE F-Series CIRJE-F-1072, CIRJE, Faculty of Economics, University of Tokyo.
    11. Evan M. Calford & Timothy N. Cason, 2024. "Contingent Reasoning and Dynamic Public Goods Provision," American Economic Journal: Microeconomics, American Economic Association, vol. 16(2), pages 236-266, May.
    12. Anderson, David M. & Hoagland, Alex & Zhu, Ed, 2024. "Medical bill shock and imperfect moral hazard," Journal of Public Economics, Elsevier, vol. 236(C).
    13. Shengwu Li, 2017. "Obviously Strategy-Proof Mechanisms," American Economic Review, American Economic Association, vol. 107(11), pages 3257-3287, November.
    14. Moser, Johannes, 2018. "Hypothetical thinking and the winner's curse: An experimental investigation," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181506, Verein für Socialpolitik / German Economic Association.
    15. Esponda, Ignacio & Vespa, Emanuel & Yuksel, Sevgi, 2024. "Mental Models and Learning: The Case of Base-Rate Neglect," University of California at San Diego, Economics Working Paper Series qt8cb387t8, Department of Economics, UC San Diego.
    16. Wenner, Lukas M., 2018. "Do sellers exploit biased beliefs of buyers? An experiment," Games and Economic Behavior, Elsevier, vol. 110(C), pages 194-215.
    17. Niederle, Muriel & Vespa, Emanuel, 2023. "Cognitive Limitations: Failures of Contingent Thinking," University of California at San Diego, Economics Working Paper Series qt5q14p1np, Department of Economics, UC San Diego.
    18. Johannes Moser, 2017. "Hypothetical thinking and the winner's curse: An experimental investigation," Working Papers 176, Bavarian Graduate Program in Economics (BGPE).
    19. Antonio Filippin & Marco Mantovani, 2023. "Risk aversion and information aggregation in binary‐asset markets," Quantitative Economics, Econometric Society, vol. 14(2), pages 753-798, May.
    20. Antonio, Filippin & Marco, Mantovani, 2019. "Risk Aversion and Information Aggregation in Asset Markets," Working Papers 404, University of Milano-Bicocca, Department of Economics, revised Apr 2019.

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    More about this item

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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