IDEAS home Printed from https://ideas.repec.org/p/kud/kucebi/2307.html
   My bibliography  Save this paper

Mental Models of the Stock Market

Author

Listed:
  • Peter Andre

    (Leibniz Institute for Financial Research SAFE)

  • Philipp Schirmer

    (University of Bonn)

  • Johannes Wohlfart

    (University of Cologne)

Abstract

Investors’ return expectations are pivotal in stock markets, but the reasoning behind these expectations is not well understood. 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, academic experts refer to market efficiency to explain their forecasts, whereas households and many professionals directly equate higher future earnings with higher future returns, neglecting the offsetting effects 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 or ignorance about how returns are calculated. Instead, it reflects a gap in respondents’ mental models: they are unfamiliar with the concept of equilibrium pricing. Lastly, we illustrate the potential consequences of neglecting equilibrium pricing. We use panel data on household expectations to show that this neglect predicts previously documented belief anomalies such as return extrapolation and pro-cyclicality.

Suggested Citation

  • Peter Andre & Philipp Schirmer & Johannes Wohlfart, 2024. "Mental Models of the Stock Market," CEBI working paper series 23-07, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
  • Handle: RePEc:kud:kucebi:2307
    as

    Download full text from publisher

    File URL: https://www.econ.ku.dk/cebi/publikationer/working-papers/CEBI_WP_07-23.rev1.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    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. Ernesto Dal Bó & Pedro Dal Bó & Erik Eyster, 2018. "The Demand for Bad Policy when Voters Underappreciate Equilibrium Effects," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(2), pages 964-998.
    3. Fink, Josef, 2021. "A review of the Post-Earnings-Announcement Drift," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    4. Hirshleifer, David & Li, Jun & Yu, Jianfeng, 2015. "Asset pricing in production economies with extrapolative expectations," Journal of Monetary Economics, Elsevier, vol. 76(C), pages 87-106.
    5. Rob Bauer & Katrin Gödker & Paul Smeets & Florian Zimmermann, 2024. "Mental Models in Financial Markets: How Do Experts Reason About the Pricing of Climate Change?," CRC TR 224 Discussion Paper Series crctr224_2024_569, University of Bonn and University of Mannheim, Germany.
    6. Luis Armona & Andreas Fuster & Basit Zafar, 2019. "Home Price Expectations and Behaviour: Evidence from a Randomized Information Experiment," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(4), pages 1371-1410.
    7. James J. Choi & Adriana Z. Robertson, 2020. "What Matters to Individual Investors? Evidence from the Horse's Mouth," Journal of Finance, American Finance Association, vol. 75(4), pages 1965-2020, August.
    8. Peter Andrebriq & Carlo Pizzinelli & Christopher Roth & Johannes Wohlfart, 2022. "Subjective Models of the Macroeconomy: Evidence From Experts and Representative Samples," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(6), pages 2958-2991.
    9. Rob Bauer & Katrin Gödker & Paul Smeets & Florian Zimmermann, 2024. "Mental Models in Financial Markets: How Do Experts Reason about the Pricing of Climate Risk?," CESifo Working Paper Series 11149, CESifo.
    10. 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.
    11. 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.
    12. Muriel Niederle & Emanuel Vespa, 2023. "Cognitive Limitations: Failures of Contingent Thinking," Annual Review of Economics, Annual Reviews, vol. 15(1), pages 307-328, September.
    13. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
    14. 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.
    15. Gorodnichenko, Yuriy & Yin, Xiao, 2024. "Higher-Order Beliefs and Risky Asset Holdings," IZA Discussion Papers 17120, Institute of Labor Economics (IZA).
    16. Bender, Svetlana & Choi, James J. & Dyson, Danielle & Robertson, Adriana Z., 2022. "Millionaires speak: What drives their personal investment decisions?," Journal of Financial Economics, Elsevier, vol. 146(1), pages 305-330.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
    22. Liu, Hongqi & Peng, Cameron & Wei, Xiong & Wei, Xiong, 2022. "Taming the bias zoo," LSE Research Online Documents on Economics 109301, London School of Economics and Political Science, LSE Library.
    23. 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.
    24. 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.
    25. Beckmann, Elisabeth & Schmidt, Tobias, 2020. "Bundesbank online pilot survey on consumer expectations," Technical Papers 01/2020, Deutsche Bundesbank.
    26. Terrance Odean, 1999. "Do Investors Trade Too Much?," American Economic Review, American Economic Association, vol. 89(5), pages 1279-1298, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rob Bauer & Katrin Gödker & Paul Smeets & Florian Zimmermann, 2024. "Mental Models in Financial Markets: How Do Experts Reason About the Pricing of Climate Risk?," ECONtribute Discussion Papers Series 319, University of Bonn and University of Cologne, Germany.
    2. Ingar Haaland & Christopher Roth & Stefanie Stantcheva & Johannes Wohlfart, 2024. "Measuring What Is Top of Mind," ECONtribute Discussion Papers Series 298, University of Bonn and University of Cologne, Germany.
    3. Hackethal, Andreas & Hanspal, Tobin & Hartzmark, Samuel M. & Bräuer, Konstantin, 2024. "Educating investors about dividends," CFS Working Paper Series 725, Center for Financial Studies (CFS).
    4. Bocar A. Ba & Abdoulaye Ndiaye & Roman G. Rivera & Alexander Whitefield, 2024. "Mispricing Narratives after Social Unrest," Opportunity and Inclusive Growth Institute Working Papers 096, Federal Reserve Bank of Minneapolis.
    5. Yuriy Gorodnichenko & Xiao Yin, 2024. "Higher-Order Beliefs and Risky Asset Holdings," NBER Working Papers 32680, National Bureau of Economic Research, Inc.
    6. Rob Bauer & Katrin Gödker & Paul Smeets & Florian Zimmermann, 2024. "Mental Models in Financial Markets: How Do Experts Reason About the Pricing of Climate Change?," CRC TR 224 Discussion Paper Series crctr224_2024_569, University of Bonn and University of Mannheim, Germany.
    7. Duraj, Kamila & Grunow, Daniela & Chaliasos, Michael & Laudenbach, Christine & Siegel, Stephan, 2024. "Rethinking the stock market participation puzzle: A qualitative approach," IMFS Working Paper Series 210, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    8. Bocar A. Ba & Abdoulaye Ndiaye & Roman G. Rivera & Alexander Whitefield, 2024. "Mispricing Narratives after Social Unrest," CESifo Working Paper Series 11264, CESifo.
    9. Hackethal, Andreas & Hanspal, Tobin & Hartzmark, Samuel M. & Bräuer, Konstantin, 2024. "Educating investors about dividends," SAFE Working Paper Series 420, Leibniz Institute for Financial Research SAFE.

    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. Na, Haejung & Kim, Soonho, 2021. "Predicting stock prices based on informed traders’ activities using deep neural networks," Economics Letters, Elsevier, vol. 204(C).
    2. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021, January-A.
    3. Doron Avramov & Guy Kaplanski & Avanidhar Subrahmanyam, 2022. "Postfundamentals Price Drift in Capital Markets: A Regression Regularization Perspective," Management Science, INFORMS, vol. 68(10), pages 7658-7681, October.
    4. Jiang, Hao & Li, Sophia Zhengzi & Wang, Hao, 2021. "Pervasive underreaction: Evidence from high-frequency data," Journal of Financial Economics, Elsevier, vol. 141(2), pages 573-599.
    5. Ingar Haaland & Christopher Roth & Johannes Wohlfart, 2023. "Designing Information Provision Experiments," Journal of Economic Literature, American Economic Association, vol. 61(1), pages 3-40, March.
    6. Lim, Kian-Ping & Kim, Jae H., 2011. "Trade openness and the informational efficiency of emerging stock markets," Economic Modelling, Elsevier, vol. 28(5), pages 2228-2238, September.
    7. Paul Handro & Bogdan Dima, 2024. "Analyzing Financial Markets Efficiency: Insights from a Bibliometric and Content Review," Journal of Financial Studies, Institute of Financial Studies, vol. 16(9), pages 119-175, May.
    8. Bolin Mao & Chenhui Chu & Yuta Nakashima & Hajime Nagahara, 2022. "Efficient Market Hypothesis Test with Stock Tweets and Natural Language Processing Models," KIER Working Papers 1082, Kyoto University, Institute of Economic Research.
    9. Pedersen, Lasse Heje, 2022. "Game on: Social networks and markets," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1097-1119.
    10. Daniel, Kent & Hirshleifer, David & Teoh, Siew Hong, 2002. "Investor psychology in capital markets: evidence and policy implications," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 139-209, January.
    11. Stephen Foerster, 2011. "Double then Nothing: Why Stock Investments Relying on Simple Heuristics May Disappoint," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 3(2), pages 115-140, September.
    12. Bradley Jones, 2015. "Asset Bubbles: Re-thinking Policy for the Age of Asset Management," IMF Working Papers 2015/027, International Monetary Fund.
    13. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.
    14. Glaser, Markus & Nöth, Markus & Weber, Martin, 2003. "Behavioral finance," Papers 03-14, Sonderforschungsbreich 504.
    15. Baltzer, Markus & Jank, Stephan & Smajlbegovic, Esad, 2019. "Who trades on momentum?," Journal of Financial Markets, Elsevier, vol. 42(C), pages 56-74.
    16. Kent Daniel & David Hirshleifer, 2015. "Overconfident Investors, Predictable Returns, and Excessive Trading," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 61-88, Fall.
    17. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2005. "Evidence on the speed of convergence to market efficiency," Journal of Financial Economics, Elsevier, vol. 76(2), pages 271-292, May.
    18. Li, Kai, 2021. "Nonlinear effect of sentiment on momentum," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    19. Committee, Nobel Prize, 2013. "Understanding Asset Prices," Nobel Prize in Economics documents 2013-1, Nobel Prize Committee.
    20. I-Cheng Yeh & Yi-Cheng Liu, 2020. "Discovering optimal weights in weighted-scoring stock-picking models: a mixture design approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-28, December.

    More about this item

    Keywords

    Mental models; Return expectations;

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:kud:kucebi:2307. 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: Thomas Hoffmann (email available below). General contact details of provider: https://edirc.repec.org/data/cebkudk.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.