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Risk Aversion and Information Aggregation in Asset Markets

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  • Antonio, Filippin
  • Marco, Mantovani

Abstract

The paper investigates the relation between the risk preferences of traders and the information-aggregation properties of an experimental call market. We find evidence inconsistent with the prediction that market-clearing prices are closer to full revelation of the state when traders are more risk-averse. The observed pattern of prices is close to the risk-neutral benchmark, while individuals are risk averse both in a risk elicitation task and when estimating their risk aversion from their market activity. This purported conflict is explained by an attitude to exploit only part of the information possessed that we label operational conservatism. We show that operational conservatism represents an additional, although suboptimal, way to express one’s risk aversion. A remarkably consistent picture of measured risk preferences emerges then in our data. Independently-elicited risk attitudes retain the footprint of both the standard and the suboptimal facet of risk aversion estimated from subjects’ market activity.

Suggested Citation

  • 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.
    • Handle: RePEc:mib:wpaper:404
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    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. Aydoğan Alti & Paul C. Tetlock, 2014. "Biased Beliefs, Asset Prices, and Investment: A Structural Approach," Journal of Finance, American Finance Association, vol. 69(1), pages 325-361, February.
    3. He, Xue-Zhong & Treich, Nicolas, 2012. "Heterogeneous Beliefs and Prediction Market Accuracy," IDEI Working Papers 775, Institut d'Économie Industrielle (IDEI), Toulouse.
    4. Paolo Crosetto & Antonio Filippin, 2013. "The “bomb” risk elicitation task," Journal of Risk and Uncertainty, Springer, vol. 47(1), pages 31-65, August.
    5. Tanjim Hossain & Ryo Okui, 2013. "The Binarized Scoring Rule," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(3), pages 984-1001.
    6. John Fountain & Glenn Harrison, 2011. "What do prediction markets predict?," Applied Economics Letters, Taylor & Francis Journals, vol. 18(3), pages 267-272.
    7. James Cox & Vjollca Sadiraj & Ulrich Schmidt, 2014. "Alternative Payoff Mechanisms for Choice under Risk," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 20(2), pages 239-240, May.
    8. Milgrom, Paul & Stokey, Nancy, 1982. "Information, trade and common knowledge," Journal of Economic Theory, Elsevier, vol. 26(1), pages 17-27, February.
    9. 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.
    10. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
    11. 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.
    12. Lawrence Choo & Todd R. Kaplan & Ro’i Zultan, 2019. "Information aggregation in Arrow–Debreu markets: an experiment," Experimental Economics, Springer;Economic Science Association, vol. 22(3), pages 625-652, September.
    13. 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.
    14. 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.
    15. 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.
    16. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Biais, Bruno & Mariotti, Thomas & Moinas, Sophie & Pouget, Sébastien, 2017. "Asset Pricing and Risk Sharing in Complete Markets: An Experimental Investigation," TSE Working Papers 17-798, Toulouse School of Economics (TSE), revised Aug 2024.
    23. 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.
    24. repec:bla:jfinan:v:59:y:2004:i:1:p:407-446 is not listed on IDEAS
    25. Larry G. Epstein, 2006. "An Axiomatic Model of Non-Bayesian Updating," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 73(2), pages 413-436.
    26. Felix Holzmeister & Matthias Stefan, 2019. "The risk elicitation puzzle revisited: Across-methods (in)consistency?," Working Papers 2019-19, Faculty of Economics and Statistics, Universität Innsbruck.
    27. 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.
    28. 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.
    29. Joost M.E. Pennings & Ale Smidts, 2000. "Assessing the Construct Validity of Risk Attitude," Management Science, INFORMS, vol. 46(10), pages 1337-1348, October.
    30. 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.
    31. 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.
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    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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