IDEAS home Printed from https://ideas.repec.org/a/eee/jeborg/v218y2024icp20-29.html
   My bibliography  Save this article

Does the left-digit bias affect prices in financial markets?

Author

Listed:
  • Heraud, Florian
  • Page, Lionel

Abstract

According to the left-digit bias, people pay more attention to the leftmost digits of a number and tend to disregard the last digits of that number. We investigate whether this bias affects traders' perception and pricing in a large financial market trading foreign exchange options. Our theoretical model predicts that the left-digit bias affects prices, causing a discontinuous jump in expected returns when comparing markets at threshold prices 10,20,…,90 with markets at prices just below these thresholds, such as 9.9,19.99, etc. The model predicts no discontinuity in returns among unbiased traders. Using a regression discontinuity approach over the returns of more than 1 million options, we find significant discontinuities in the expected returns, consistent with mispricing induced by the left-digit bias.

Suggested Citation

  • Heraud, Florian & Page, Lionel, 2024. "Does the left-digit bias affect prices in financial markets?," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 20-29.
    • Handle: RePEc:eee:jeborg:v:218:y:2024:i:c:p:20-29
    DOI: 10.1016/j.jebo.2023.10.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167268123003645
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jebo.2023.10.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    References listed on IDEAS

    as
    1. Wei-Yu Kuo & Tse-Chun Lin & Jing Zhao, 2015. "Cognitive Limitation and Investment Performance: Evidence from Limit Order Clustering," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 838-875.
    2. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    3. Brown, Alasdair & Yang, Fuyu, 2016. "Limited cognition and clustered asset prices: Evidence from betting markets," Journal of Financial Markets, Elsevier, vol. 29(C), pages 27-46.
    4. Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2013. "Prediction Markets for Economic Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 657-687, Elsevier.
    5. Nicola Lacetera & Devin G. Pope & Justin R. Sydnor, 2012. "Heuristic Thinking and Limited Attention in the Car Market," American Economic Review, American Economic Association, vol. 102(5), pages 2206-2236, August.
    6. Marco Ottaviani & Peter Norman Sørensen, 2015. "Price Reaction to Information with Heterogeneous Beliefs and Wealth Effects: Underreaction, Momentum, and Reversal," American Economic Review, American Economic Association, vol. 105(1), pages 1-34, January.
    7. Luca Repetto & Alex Solís, 2020. "The Price of Inattention: Evidence from the Swedish Housing Market," Journal of the European Economic Association, European Economic Association, vol. 18(6), pages 3261-3304.
    8. Sebastian Calonico & Matias D Cattaneo & Max H Farrell, 2020. "Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs," The Econometrics Journal, Royal Economic Society, vol. 23(2), pages 192-210.
    9. Krishnamurthy Iyer & Ramesh Johari & Ciamac C. Moallemi, 2014. "Information Aggregation and Allocative Efficiency in Smooth Markets," Management Science, INFORMS, vol. 60(10), pages 2509-2524, October.
    10. Joyce E. Berg & George R. Neumann & Thomas A. Rietz, 2009. "Searching for Google's Value: Using Prediction Markets to Forecast Market Capitalization Prior to an Initial Public Offering," Management Science, INFORMS, vol. 55(3), pages 348-361, March.
    11. Ahrash Dianat & Christoph Siemroth, 2021. "Correction to: Improving decisions with market information: an experiment on corporate prediction markets," Experimental Economics, Springer;Economic Science Association, vol. 24(3), pages 1074-1074, September.
    12. Burton G. Malkiel, 2005. "Reflections on the Efficient Market Hypothesis: 30 Years Later," The Financial Review, Eastern Finance Association, vol. 40(1), pages 1-9, February.
    13. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    14. Matias D. Cattaneo & Rocío Titiunik & Gonzalo Vazquez-Bare, 2020. "Analysis of regression-discontinuity designs with multiple cutoffs or multiple scores," Stata Journal, StataCorp LP, vol. 20(4), pages 866-891, December.
    15. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    16. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    17. Bo Cowgill & Eric Zitzewitz, 2015. "Corporate Prediction Markets: Evidence from Google, Ford, and Firm X," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1309-1341.
    18. repec:pri:cepsud:91malkiel is not listed on IDEAS
    19. Utpal Bhattacharya & Craig W. Holden & Stacey Jacobsen, 2012. "Penny Wise, Dollar Foolish: Buy-Sell Imbalances On and Around Round Numbers," Management Science, INFORMS, vol. 58(2), pages 413-431, February.
    20. Kenneth Oliven & Thomas A. Rietz, 2004. "Suckers Are Born but Markets Are Made: Individual Rationality, Arbitrage, and Market Efficiency on an Electronic Futures Market," Management Science, INFORMS, vol. 50(3), pages 336-351, March.
    21. Page, Lionel & Siemroth, Christoph, 2017. "An experimental analysis of information acquisition in prediction markets," Games and Economic Behavior, Elsevier, vol. 101(C), pages 354-378.
    22. Ahrash Dianat & Christoph Siemroth, 2021. "Improving decisions with market information: an experiment on corporate prediction markets," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 143-176, March.
    23. Manoj Thomas & Vicki Morwitz, 2005. "Penny Wise and Pound Foolish: The Left-Digit Effect in Price Cognition," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(1), pages 54-64, June.
    24. M. Keith Chen & Jonathan E. Ingersoll, Jr. & Edward H. Kaplan, 2008. "Modeling a Presidential Prediction Market," Management Science, INFORMS, vol. 54(8), pages 1381-1394, August.
    25. Lionel Page & Robert T. Clemen, 2013. "Do Prediction Markets Produce Well‐Calibrated Probability Forecasts?-super-," Economic Journal, Royal Economic Society, vol. 123(568), pages 491-513, May.
    Full references (including those not matched with items on IDEAS)

    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. Lionel Page & Christoph Siemroth, 2021. "How Much Information Is Incorporated into Financial Asset Prices? Experimental Evidence," Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4412-4449.
    2. Angelini, Giovanni & De Angelis, Luca & Singleton, Carl, 2022. "Informational efficiency and behaviour within in-play prediction markets," International Journal of Forecasting, Elsevier, vol. 38(1), pages 282-299.
    3. Patrick Buckley & Fergal O’Brien, 0. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 0, pages 1-13.
    4. Patrick Buckley & Fergal O’Brien, 2017. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 19(3), pages 611-623, June.
    5. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    6. Zhao, Yang & Yu, Min-Teh, 2020. "Predicting catastrophe risk: Evidence from catastrophe bond markets," Journal of Banking & Finance, Elsevier, vol. 121(C).
    7. Saker Sabkha & Christian Peretti & Dorra Hmaied, 2019. "On the informational market efficiency of the worldwide sovereign credit default swaps," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 581-608, December.
    8. Majumder, Debasish, 2013. "Towards an efficient stock market: Empirical evidence from the Indian market," Journal of Policy Modeling, Elsevier, vol. 35(4), pages 572-587.
    9. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Long Run Returns Predictability and Volatility with Moving Averages," Risks, MDPI, vol. 6(4), pages 1-18, September.
    10. Romain Gauriot Author e-mail: romain.gauriot@nyu.edu & Lionel Page Author e-mail: lionel.page@uts.edu.au, 2021. "How Market Prices React to Information: Evidence from Binary Options Markets," Working Papers 20200058, New York University Abu Dhabi, Department of Social Science, revised Oct 2021.
    11. Cristi Spulbar & Ramona Birau & Lucian Florin Spulbar, 2021. "A Critical Survey on Efficient Market Hypothesis (EMH), Adaptive Market Hypothesis (AMH) and Fractal Markets Hypothesis (FMH) Considering Their Implication on Stock Markets Behavior," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 1161-1165, December.
    12. Taufiq Choudhry & Ranadeva Jayasekera, 2015. "Level of efficiency in the UK equity market: empirical study of the effects of the global financial crisis," Review of Quantitative Finance and Accounting, Springer, vol. 44(2), pages 213-242, February.
    13. Stöckl, Thomas & Huber, Jürgen & Kirchler, Michael & Lindner, Florian, 2015. "Hot hand and gambler's fallacy in teams: Evidence from investment experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 327-339.
    14. Yardley, Ben, 2020. "The Effects of Donald Trump’s Tweets on The Stock Exchange," MPRA Paper 102578, University Library of Munich, Germany.
    15. Thorsten Hens & Peter Wöhrmann, 2007. "Strategic asset allocation and market timing: a reinforcement learning approach," Computational Economics, Springer;Society for Computational Economics, vol. 29(3), pages 369-381, May.
    16. Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2022. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Management Science, INFORMS, vol. 68(7), pages 5216-5232, July.
    17. Kevin Primicerio & Damien Challet & Stanislao Gualdi, 2017. "Wisdom of the institutional crowd," Working Papers hal-01484914, HAL.
    18. Kin-Boon Tang & Shao-Jye Wong & Shih-Kuei Lin & Szu-Lang Liao, 2020. "Excess volatility and market efficiency in government bond markets: the ASEAN-5 context," Journal of Asset Management, Palgrave Macmillan, vol. 21(2), pages 154-165, March.
    19. Cao, K.H. & Qi, H.S. & Tsai, C.H. & Woo, C.K. & Zarnikau, J., 2021. "Energy trading efficiency in the US Midcontinent electricity markets," Applied Energy, Elsevier, vol. 302(C).
    20. Chen, Tao, 2018. "Round-number biases and informed trading in global markets," Journal of Business Research, Elsevier, vol. 92(C), pages 105-117.

    More about this item

    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:eee:jeborg:v:218:y:2024:i:c:p:20-29. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jebo .

    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.