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Asymmetric learning from financial information

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  • Kuhnen, Camelia M.

Abstract

The goal of this study is to ask whether investors learn differently from gains (positive news) versus losses (negative news), whether learning performance is better or worse when people are actively investing in a security or passively observing the security’s payoffs, and whether there are personal characteristics that correlate with learning performance. The experimental evidence documented here indicates that the ability to learn from financial information is on average worse in the loss domain, in particular if the investor has personally experienced the prior outcomes of the financial asset considered. Within individual, learning from gains versus losses, or during active versus passive involvement, are not perfectly correlated, indicating that there exists heterogeneity across people with respect to the type of financial information or context to which they are the most sensitive. Learning performance is determined by acquired financial expertise as well as by genetic factors related to memory and cognitive control.

Suggested Citation

  • Kuhnen, Camelia M., 2012. "Asymmetric learning from financial information," MPRA Paper 39412, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:39412
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    References listed on IDEAS

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    1. Froot, Kenneth A., 2001. "The market for catastrophe risk: a clinical examination," Journal of Financial Economics, Elsevier, vol. 60(2-3), pages 529-571, May.
    2. Markus K. Brunnermeier & Jonathan A. Parker & Christian Gollier, 2007. "Optimal Beliefs, Asset Prices, and the Preference for Skewed Returns," American Economic Review, American Economic Association, vol. 97(2), pages 159-165, May.
    3. John Y. Campbell, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    4. Xavier Gabaix, 2014. "A Sparsity-Based Model of Bounded Rationality," The Quarterly Journal of Economics, Oxford University Press, vol. 129(4), pages 1661-1710.
    5. repec:hrv:faseco:30747159 is not listed on IDEAS
    6. Tim Bollerslev & Viktor Todorov, 2011. "Tails, Fears, and Risk Premia," Journal of Finance, American Finance Association, vol. 66(6), pages 2165-2211, December.
    7. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    8. Lusardi, Annamaria & Mitchell, Olivia S., 2007. "Baby Boomer retirement security: The roles of planning, financial literacy, and housing wealth," Journal of Monetary Economics, Elsevier, vol. 54(1), pages 205-224, January.
    9. Andrew W. Lo & Dmitry V. Repin & Brett N. Steenbarger, 2005. "Fear and Greed in Financial Markets: A Clinical Study of Day-Traders," American Economic Review, American Economic Association, vol. 95(2), pages 352-359, May.
    10. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    11. Marcin Kacperczyk & Stijn Van Nieuwerburgh & Laura Veldkamp, 2009. "Rational Attention Allocation Over the Business Cycle," NBER Working Papers 15450, National Bureau of Economic Research, Inc.
    12. Nicola Gennaioli & Andrei Shleifer, 2010. "What Comes to Mind," The Quarterly Journal of Economics, Oxford University Press, vol. 125(4), pages 1399-1433.
    13. Xavier Gabaix & David Laibson & Guillermo Moloche & Stephen Weinberg, 2006. "Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model," American Economic Review, American Economic Association, vol. 96(4), pages 1043-1068, September.
    14. Terrance Odean, 1998. "Are Investors Reluctant to Realize Their Losses?," Journal of Finance, American Finance Association, vol. 53(5), pages 1775-1798, October.
    15. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-1153, December.
    16. Antoine J. Bruguier & Steven R. Quartz & Peter Bossaerts, 2010. "Exploring the Nature of "Trader Intuition"," Journal of Finance, American Finance Association, vol. 65(5), pages 1703-1723, October.
    17. Nicholas Barberis, 2001. "Mental Accounting, Loss Aversion, and Individual Stock Returns," Journal of Finance, American Finance Association, vol. 56(4), pages 1247-1292, August.
    18. Camelia Kuhnen & Brian Knutson, 2005. "The Neural Basis of Financial Risk Taking," Experimental 0509001, EconWPA.
    19. Peter Bossaerts, 2009. "What Decision Neuroscience Teaches Us About Financial Decision Making," Annual Review of Financial Economics, Annual Reviews, vol. 1(1), pages 383-404, November.
    20. Brian D. Kluger & Steve B. Wyatt, 2004. "Are Judgment Errors Reflected in Market Prices and Allocations? Experimental Evidence Based on the Monty Hall Problem," Journal of Finance, American Finance Association, vol. 59(3), pages 969-998, June.
    21. Kuhnen, Camelia M. & Knutson, Brian, 2011. "The Influence of Affect on Beliefs, Preferences, and Financial Decisions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 46(03), pages 605-626, June.
    22. Nicholas Barberis & Ming Huang, 2001. "Mental Accounting, Loss Aversion, and Individual Stock Returns," NBER Working Papers 8190, National Bureau of Economic Research, Inc.
    23. Nicholas Barberis & Ming Huang & Tano Santos, 2001. "Prospect Theory and Asset Prices," The Quarterly Journal of Economics, Oxford University Press, vol. 116(1), pages 1-53.
    24. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    25. Shimon Kogan, 2009. "Distinguishing the Effect of Overconfidence from Rational Best-Response on Information Aggregation," Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1889-1914, May.
    26. Ulrike Malmendier & Stefan Nagel, 2011. "Depression Babies: Do Macroeconomic Experiences Affect Risk Taking?," The Quarterly Journal of Economics, Oxford University Press, vol. 126(1), pages 373-416.
    27. Gary Charness & Dan Levin, 2005. "When Optimal Choices Feel Wrong: A Laboratory Study of Bayesian Updating, Complexity, and Affect," American Economic Review, American Economic Association, vol. 95(4), pages 1300-1309, September.
    28. Viktor Todorov, 2010. "Variance Risk-Premium Dynamics: The Role of Jumps," Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 345-383, January.
    29. Élise PAYZAN LE NESTOUR, 2010. "Bayesian Learning in UnstableSettings: Experimental Evidence Based on the Bandit Problem," Swiss Finance Institute Research Paper Series 10-28, Swiss Finance Institute.
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    Cited by:

    1. Anthony Newell & Lionel Page, 2017. "Countercyclical risk aversion and self-reinforcing feedback loops in experimental asset markets," QuBE Working Papers 050, QUT Business School.
    2. Kuhnen, Camelia M. & Miu, Andrei C., 2017. "Socioeconomic status and learning from financial information," Journal of Financial Economics, Elsevier, vol. 124(2), pages 349-372.
    3. Hainz, Christa & Fidrmuc, Jarko & Hölzl, Werner, 2016. "Firm Credit Experience and Perceptions of Lending Policy: Business Survey Evidence from Austria," Annual Conference 2016 (Augsburg): Demographic Change 145863, Verein für Socialpolitik / German Economic Association.
    4. Das, Sreyoshi & Kuhnen, Camelia & Nagel, Stefan, 2017. "Socioeconomic Status and Macroeconomic Expectations," CEPR Discussion Papers 12464, C.E.P.R. Discussion Papers.
    5. Fidrmuc, Jarko & Hainz, Christa & Hölzl, Werner, 2017. "Dynamics of Access to Credit and Perceptions of Lending Policy: Evidence from a Firm Survey," Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168254, Verein für Socialpolitik / German Economic Association.
    6. Peiran Jiao & Amos Nadler, 2016. "The Bull of Wall Street: Experimental Analysis of Testosterone and Asset Trading," Economics Series Working Papers 806, University of Oxford, Department of Economics.

    More about this item

    Keywords

    financial decision making; learning; gains; losses; genes; COMT; neuroeconomics;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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