IDEAS home Printed from https://ideas.repec.org/a/oup/rfinst/v30y2017i6p2066-2109..html
   My bibliography  Save this article

A Mind Is a Terrible Thing to Change: Confirmatory Bias in Financial Markets

Author

Listed:
  • Sebastien Pouget
  • Julien Sauvagnat
  • Stephane Villeneuve

Abstract

This paper studies the impact of the confirmatory bias on financial markets. We propose a model in which some traders may ignore new evidence inconsistent with their favorite hypothesis regarding the state of the world. The confirmatory bias provides a unified rationale for several existing stylized facts, including excess volatility, excess volume, and momentum. It also delivers novel predictions for which we find empirical support using data on analysts’ earnings forecasts: traders update beliefs depending on the sign of past signals and previous beliefs, and, at the stock level, differences of opinion are larger when past signals have different signs.

Suggested Citation

  • Sebastien Pouget & Julien Sauvagnat & Stephane Villeneuve, 2017. "A Mind Is a Terrible Thing to Change: Confirmatory Bias in Financial Markets," The Review of Financial Studies, Society for Financial Studies, vol. 30(6), pages 2066-2109.
    • Handle: RePEc:oup:rfinst:v:30:y:2017:i:6:p:2066-2109.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/rfs/hhw100
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    Citations

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


    Cited by:

    1. Tao Chen & Andreas Karathanasopoulos, 2022. "Do Heterogeneous Beliefs Matter to Post‐announcement Informed Trading?," Abacus, Accounting Foundation, University of Sydney, vol. 58(4), pages 714-741, December.
    2. Heusel, Nicola & Mager, Ferdinand, 2023. "Pension funding and the cross section of stock returns - The case of Germany," Journal of Banking & Finance, Elsevier, vol. 150(C).
    3. Simon Kloker & Tim Straub & Christof Weinhardt, 2019. "Moderators for Partition Dependence in Prediction Markets," Group Decision and Negotiation, Springer, vol. 28(4), pages 723-756, August.
    4. Li Qian & Mingsheng Li & Yan Li, 2020. "Does news travel slowly before a market crash? The role of margin traders," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(3), pages 3065-3101, September.
    5. Goldman, Eitan & Martel, Jordan & Schneemeier, Jan, 2022. "A theory of financial media," Journal of Financial Economics, Elsevier, vol. 145(1), pages 239-258.
    6. Xiaoqiao Wang & Jing Xie & Bohui Zhang & Xiaofeng Zhao, 2024. "Unraveling the Dividend Puzzle: A Field Experiment," Working Papers 202406, University of Macau, Faculty of Business Administration.
    7. Daniel J. Benjamin, 2018. "Errors in Probabilistic Reasoning and Judgment Biases," NBER Working Papers 25200, National Bureau of Economic Research, Inc.
    8. Qingchong Chen & Xiong Xiong & Ya Gao, 2021. "Is information really efficient for the market? Evidence of confirmatory bias in China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(5), pages 5965-5997, December.
    9. Tao Chen, 2022. "Investor Protection and Post-Disclosure Disagreement: International Evidence," The International Journal of Accounting (TIJA), World Scientific Publishing Co. Pte. Ltd., vol. 57(03), pages 1-28, September.
    10. Cookson, J. Anthony & Engelberg, Joseph E. & Mullins, William, 2020. "Echo Chambers," SocArXiv n2q9h, Center for Open Science.
    11. Ruzzier, Christian A. & Woo, Marcelo D., 2023. "Discrimination with inaccurate beliefs and confirmation bias," Journal of Economic Behavior & Organization, Elsevier, vol. 210(C), pages 379-390.
    12. Ulrike Malmendier, 2018. "Behavioral Corporate Finance," NBER Working Papers 25162, National Bureau of Economic Research, Inc.
    13. Pedro Gonzalez-Fernandez, 2024. "Belief Bias Identification," Papers 2404.09297, arXiv.org, revised Nov 2024.
    14. Kong, Dongmin & Liu, Lihua & Liu, Shasha, 2020. "Market information traveling on high-speed rails: The case of analyst forecasts," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    15. Suresh G., 2024. "Impact of Financial Literacy and Behavioural Biases on Investment Decision-making," FIIB Business Review, , vol. 13(1), pages 72-86, January.
    16. Cafferata, Alessia & Tramontana, Fabio, 2019. "A financial market model with confirmation bias," Structural Change and Economic Dynamics, Elsevier, vol. 51(C), pages 252-259.
    17. Park, Hyoeun & Tayawa, Jason Paulo, 2024. "Anchored belief updating from recommendations," Journal of Mathematical Economics, Elsevier, vol. 110(C).
    18. Cafferata, Alessia & Dávila-Fernández, Marwil J. & Sordi, Serena, 2021. "Seeing what can(not) be seen: Confirmation bias, employment dynamics and climate change," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 567-586.
    19. Zhang, Yuan-Yuan & Zhang, Yue-Jun, 2022. "The impact of institutional analyst forecast divergence on crude oil market: Evidence from the mixed frequency models," International Review of Financial Analysis, Elsevier, vol. 84(C).
    20. M. Rozina & М. Розина, 2019. "Теория и практика поведенческой экономики в процессе принятия финансовых решений // The Use of Theory and Methods of Behavioural Economics in the Process of Making Financial Decisions," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 7(3), pages 45-82.
    21. Chen, Tao, 2021. "Informed trading and earnings announcement driven disagreement in global markets," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 43(C).
    22. Goutte, Maud-Rose, 2022. "Do actions speak louder than words? Evidence from microblogs," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).
    23. Wang, Hailong & Hu, Duni, 2022. "Heterogenous beliefs with sentiments and asset pricing," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    24. Shuyu Zhang & Xuanyu Zhou & Huifeng Pan & Junyi Jia, 2019. "Cryptocurrency, confirmatory bias and news readability – evidence from the largest Chinese cryptocurrency exchange," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(5), pages 1445-1468, March.
    25. Shuyi Li & Junhao Kong & Stefan Cristian Gherghina, 2022. "News Sentiment and the Risk of a Stock Price Crash Risk: Based on Financial Dictionary Combined BERT-DCA," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-28, July.

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:oup:rfinst:v:30:y:2017:i:6:p:2066-2109.. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/sfsssea.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.