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Mental Models of the Stock Market

Author

Listed:
  • Peter Andre

    (SAFE and Goethe University Frankfurt)

  • Philipp Schirmer

    (University of Bonn)

  • Johannes Wohlfart

    (University of Copenhagen)

Abstract

Investors’ return expectations are pivotal in stock markets, but the reasoning behind these expectations remains a black box for economists. This paper sheds light on economic agents’ mental models – their subjective understanding – of the stock market. We conduct surveys with the general population, retail investors, financial professionals, and academic experts. Respondents forecast and explain how future returns respond to stale news about the future earnings streams of companies. We document four main results. First, while academic experts view stale news as irrelevant, households and professionals often believe that stale good news leads to persistently higher expected future returns. Second, while academic experts refer to market efficiency to explain their forecasts, households and many professionals directly equate higher future earnings with higher future returns, neglecting the offsetting effect of endogenous price adjustments. Third, additional experiments with households demonstrate that this neglect of equilibrium pricing does not reflect inattention to trading or price responses but rather a gap in respondents’ mental models: they are unfamiliar with the concept of equilibrium. Lastly, we illustrate the consequences of equilibrium neglect. We use panel data on household expectations to show that equilibrium neglect predicts previously documented belief anomalies such as return extrapolation and pro-cyclicality.

Suggested Citation

  • Peter Andre & Philipp Schirmer & Johannes Wohlfart, 2023. "Mental Models of the Stock Market," ECONtribute Discussion Papers Series 259, University of Bonn and University of Cologne, Germany.
  • Handle: RePEc:ajk:ajkdps:259
    as

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    File URL: https://www.econtribute.de/RePEc/ajk/ajkdps/ECONtribute_259_2023.pdf
    File Function: First version, 2023
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    References listed on IDEAS

    as
    1. Joshua Schwartzstein, 2014. "Selective Attention And Learning," Journal of the European Economic Association, European Economic Association, vol. 12(6), pages 1423-1452, December.
    2. Peter Andrebriq & Carlo Pizzinelli & Christopher Roth & Johannes Wohlfart, 2022. "Subjective Models of the Macroeconomy: Evidence From Experts and Representative Samples [Rationally Confused: On the Aggregate Implications of Information Provision Policies]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(6), pages 2958-2991.
    3. Jonathan de Quidt & Johannes Haushofer & Christopher Roth, 2018. "Measuring and Bounding Experimenter Demand," American Economic Review, American Economic Association, vol. 108(11), pages 3266-3302, November.
    4. De Long, J Bradford, et al, 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-395, June.
    5. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    6. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    7. Paul C. Tetlock, 2011. "All the News That's Fit to Reprint: Do Investors React to Stale Information?," The Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1481-1512.
    8. Pedro Bordalo & John J. Conlon & Nicola Gennaioli & Spencer Yongwook Kwon & Andrei Shleifer, 2023. "How People Use Statistics," NBER Working Papers 31631, National Bureau of Economic Research, Inc.
      • Pedro Bordalo & John Conlon & Nicola Gennaioli & Spencer Kwon & Andrei Shleifer, 2023. "How People Use Statistics," Working Papers 699, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Terrance Odean, 1999. "Do Investors Trade Too Much?," American Economic Review, American Economic Association, vol. 89(5), pages 1279-1298, December.
    10. 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.
    11. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    12. Rema Hanna & Sendhil Mullainathan & Joshua Schwartzstein, 2014. "Learning Through Noticing: Theory and Evidence from a Field Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(3), pages 1311-1353.
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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • G51 - Financial Economics - - Household Finance - - - Household Savings, Borrowing, Debt, and Wealth
    • G53 - Financial Economics - - Household Finance - - - Financial Literacy

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