IDEAS home Printed from https://ideas.repec.org/a/wly/quante/v14y2023i2p753-798.html
   My bibliography  Save this article

Risk aversion and information aggregation in binary‐asset markets

Author

Listed:
  • Antonio Filippin
  • Marco Mantovani

Abstract

We investigate how risk aversion (RA) shapes the informative content of prices in an experimental asset market, where traders are sorted according to their RA. RA should induce steeper individual demands and, under its most common parametrizations, drive equilibrium prices closer to revealing the state. Results support the prediction on individual demands, but not the prediction on prices, which do not vary with RA and are close to the risk‐neutral benchmark. This purported conflict is due to traders, particularly the more risk‐averse ones, conveying into prices only part of their information.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:quante:v:14:y:2023:i:2:p:753-798
    DOI: 10.3982/QE1981
    as

    Download full text from publisher

    File URL: https://doi.org/10.3982/QE1981
    Download Restriction: no

    File URL: https://libkey.io/10.3982/QE1981?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Manski, Charles F., 2006. "Interpreting the predictions of prediction markets," Economics Letters, Elsevier, vol. 91(3), pages 425-429, June.
    2. Plott, Charles R & Sunder, Shyam, 1982. "Efficiency of Experimental Security Markets with Insider Information: An Application of Rational-Expectations Models," Journal of Political Economy, University of Chicago Press, vol. 90(4), pages 663-698, August.
    3. Benjamin Enke & Thomas Graeber, 2019. "Cognitive Uncertainty," NBER Working Papers 26518, National Bureau of Economic Research, Inc.
    4. Uri Gneezy & Jan Potters, 1997. "An Experiment on Risk Taking and Evaluation Periods," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(2), pages 631-645.
    5. Erik Snowberg & Justin Wolfers, 2010. "Explaining the Favorite-Long Shot Bias: Is it Risk-Love or Misperceptions?," Journal of Political Economy, University of Chicago Press, vol. 118(4), pages 723-746, August.
    6. Plott, Charles R & Sunder, Shyam, 1988. "Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Econometrica, Econometric Society, vol. 56(5), pages 1085-1118, September.
    7. Paolo Crosetto & Antonio Filippin, 2016. "A theoretical and experimental appraisal of four risk elicitation methods," Experimental Economics, Springer;Economic Science Association, vol. 19(3), pages 613-641, September.
    8. Fellner, Gerlinde & Maciejovsky, Boris, 2007. "Risk attitude and market behavior: Evidence from experimental asset markets," Journal of Economic Psychology, Elsevier, vol. 28(3), pages 338-350, June.
    9. John Fountain & Glenn Harrison, 2011. "What do prediction markets predict?," Applied Economics Letters, Taylor & Francis Journals, vol. 18(3), pages 267-272.
    10. Deck, Cary & Lee, Jungmin & Reyes, Javier A. & Rosen, Christopher C., 2013. "A failed attempt to explain within subject variation in risk taking behavior using domain specific risk attitudes," Journal of Economic Behavior & Organization, Elsevier, vol. 87(C), pages 1-24.
    11. Elena Asparouhova & Peter Bossaerts & Jon Eguia & William Zame, 2015. "Asset Pricing and Asymmetric Reasoning," Journal of Political Economy, University of Chicago Press, vol. 123(1), pages 66-122.
    12. Hellwig, Martin F., 1980. "On the aggregation of information in competitive markets," Journal of Economic Theory, Elsevier, vol. 22(3), pages 477-498, June.
    13. Milgrom, Paul & Stokey, Nancy, 1982. "Information, trade and common knowledge," Journal of Economic Theory, Elsevier, vol. 26(1), pages 17-27, February.
    14. 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.
    15. Lionel Page & Christoph Siemroth, 2021. "How Much Information Is Incorporated into Financial Asset Prices? Experimental Evidence," The Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4412-4449.
    16. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
    17. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    18. Stephen G. Dimmock & Roy Kouwenberg & Peter P. Wakker, 2016. "Ambiguity Attitudes in a Large Representative Sample," Management Science, INFORMS, vol. 62(5), pages 1363-1380, May.
    19. Easley, David & Kiefer, Nicholas M & O'Hara, Maureen, 1997. "One Day in the Life of a Very Common Stock," The Review of Financial Studies, Society for Financial Studies, vol. 10(3), pages 805-835.
    20. Chen, Kay-Yut & Plott, Charles R., 2008. "Markets and Information Aggregation Mechanisms," Handbook of Experimental Economics Results, in: Charles R. Plott & Vernon L. Smith (ed.), Handbook of Experimental Economics Results, edition 1, volume 1, chapter 40, pages 344-352, Elsevier.
    21. Sean Crockett & Daniel Friedman & Ryan Oprea, 2021. "Naturally Occurring Preferences And General Equilibrium: A Laboratory Study," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 831-859, May.
    22. Felix Holzmeister & Matthias Stefan, 2021. "The risk elicitation puzzle revisited: Across-methods (in)consistency?," Experimental Economics, Springer;Economic Science Association, vol. 24(2), pages 593-616, June.
    23. Roland G. Fryer, Jr, 2013. "Information and Student Achievement: Evidence from a Cellular Phone Experiment," NBER Working Papers 19113, National Bureau of Economic Research, Inc.
    24. Kagel, John H. & Levin, Dan, 1986. "The Winner's Curse and Public Information in Common Value Auctions," American Economic Review, American Economic Association, vol. 76(5), pages 894-920, December.
    25. Isaac, R Mark & James, Duncan, 2000. "Just Who Are You Calling Risk Averse?," Journal of Risk and Uncertainty, Springer, vol. 20(2), pages 177-187, March.
    26. Friedman, Daniel & Isaac, R. Mark & James, Duncan & Sunder, Shyam, 2014. "Risky Curves: On the Empirical Failure of Expected Utility," Santa Cruz Department of Economics, Working Paper Series qt87v8k86z, Department of Economics, UC Santa Cruz.
    27. Serena Guarnaschelli & Anthony M. Kwasnica & Charles R. Plott, 2003. "Information Aggregation in Double Auctions: Rational Expectations and the Winner's Curse," Information Systems Frontiers, Springer, vol. 5(1), pages 63-77, January.
    28. Robert R. Bliss & Nikolaos Panigirtzoglou, 2004. "Option-Implied Risk Aversion Estimates," Journal of Finance, American Finance Association, vol. 59(1), pages 407-446, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Marco Mantovani & Antonio Filippin, 2024. "When do prediction markets return average beliefs? Experimental evidence," Working Papers 532, University of Milano-Bicocca, Department of Economics.
    3. Friedman, Daniel & Habib, Sameh & James, Duncan & Williams, Brett, 2022. "Varieties of risk preference elicitation," Games and Economic Behavior, Elsevier, vol. 133(C), pages 58-76.
    4. Ranganathan, Kavitha & Lejarraga, Tomás, 2021. "Elicitation of risk preferences through satisficing," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    5. Brice Corgnet & Cary Deck & Mark DeSantis & Kyle Hampton & Erik O. Kimbrough, 2023. "When Do Security Markets Aggregate Dispersed Information?," Management Science, INFORMS, vol. 69(6), pages 3697-3729, June.
    6. Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2022. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Management Science, INFORMS, vol. 68(7), pages 5216-5232, July.
    7. Gary Charness & Thomas Garcia & Theo Offerman & Marie Claire Villeval, 2020. "Do measures of risk attitude in the laboratory predict behavior under risk in and outside of the laboratory?," Journal of Risk and Uncertainty, Springer, vol. 60(2), pages 99-123, April.
    8. Menkhoff, Lukas & Sakha, Sahra, 2017. "Estimating risky behavior with multiple-item risk measures," Journal of Economic Psychology, Elsevier, vol. 59(C), pages 59-86.
    9. Crosetto, P. & Filippin, A., 2017. "Safe options induce gender differences in risk attitudes," Working Papers 2017-05, Grenoble Applied Economics Laboratory (GAEL).
    10. Paolo Crosetto & Antonio Filippin, 2023. "Safe options and gender differences in risk attitudes," Journal of Risk and Uncertainty, Springer, vol. 66(1), pages 19-46, February.
    11. Wenting Zhou & John Hey, 2018. "Context matters," Experimental Economics, Springer;Economic Science Association, vol. 21(4), pages 723-756, December.
    12. Fairley, Kim & Parelman, Jacob M. & Jones, Matt & Carter, R. McKell, 2019. "Risky health choices and the Balloon Economic Risk Protocol," Journal of Economic Psychology, Elsevier, vol. 73(C), pages 15-33.
    13. Christoph Huber & Christian König-Kersting, 2022. "Experimenting with Financial Professionals," Working Papers 2022-07, Faculty of Economics and Statistics, Universität Innsbruck.
    14. Fidanoski, Filip & Johnson, Timothy, 2023. "A z-Tree implementation of the Dynamic Experiments for Estimating Preferences [DEEP] method," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    15. Angelini, Giovanni & De Angelis, Luca & Singleton, Carl, 2022. "Informational efficiency and behaviour within in-play prediction markets," International Journal of Forecasting, Elsevier, vol. 38(1), pages 282-299.
    16. Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2013. "Prediction Markets for Economic Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 657-687, Elsevier.
    17. Michele Garagnani, 2023. "The predictive power of risk elicitation tasks," Journal of Risk and Uncertainty, Springer, vol. 67(2), pages 165-192, October.
    18. Lunawat, Radhika, 2021. "Learning from trading activity in laboratory security markets with higher-order uncertainty," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).
    19. Brice Corgnet & Camille Cornand & Nobuyuki Hanaki, 2020. "Negative Tail Events, Emotions & Risk Taking," Working Papers 2016, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    20. Edward Halim & Yohanes E. Riyanto & Nilanjan Roy, 2019. "Costly Information Acquisition, Social Networks, and Asset Prices: Experimental Evidence," Journal of Finance, American Finance Association, vol. 74(4), pages 1975-2010, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:quante:v:14:y:2023:i:2:p:753-798. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.