IDEAS home Printed from https://ideas.repec.org/p/bge/wpaper/1133.html
   My bibliography  Save this paper

Human vs. Machine: Disposition Effect Among Algorithmic and Human Day-traders

Author

Listed:
  • Karolis Liaudinskas

Abstract

Can humans achieve rationality, as defined by the expected utility theory, by automating their decision making? We use millisecond-stamped transaction-level data from the Copenhagen Stock Exchange to estimate the disposition effect – the tendency to sell winning but not losing stocks – among algorithmic and human professional day-traders. We find that: (1) the disposition effect is substantial among humans but virtually zero among algorithms; (2) this difference is not fully explained by rational explanations and is, at least partially, attributed to prospect theory, realization utility and beliefs in mean-reversion; (3) the disposition effect harms trading performance, which further deems such behavior irrational.

Suggested Citation

  • Karolis Liaudinskas, 2019. "Human vs. Machine: Disposition Effect Among Algorithmic and Human Day-traders," Working Papers 1133, Barcelona School of Economics.
    • Handle: RePEc:bge:wpaper:1133
    as

    Download full text from publisher

    File URL: https://www.barcelonagse.eu/sites/default/files/working_paper_pdfs/1133.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ohlson, James A. & Penman, Stephen H., 1985. "Volatility increases subsequent to stock splits: An empirical aberration," Journal of Financial Economics, Elsevier, vol. 14(2), pages 251-266, June.
    2. repec:bla:jfinan:v:53:y:1998:i:5:p:1775-1798 is not listed on IDEAS
    3. Henderson, Vicky & Hobson, David & Tse, Alex S.L., 2018. "Probability weighting, stop-loss and the disposition effect," Journal of Economic Theory, Elsevier, vol. 178(C), pages 360-397.
    4. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.
    5. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Jonathan E. Ingersoll & Lawrence J. Jin, 2013. "Realization Utility with Reference-Dependent Preferences," The Review of Financial Studies, Society for Financial Studies, vol. 26(3), pages 723-767.
    8. Dierick, Nicolas & Heyman, Dries & Inghelbrecht, Koen & Stieperaere, Hannes, 2019. "Financial attention and the disposition effect," Journal of Economic Behavior & Organization, Elsevier, vol. 163(C), pages 190-217.
    9. Vicky Henderson, 2012. "Prospect Theory, Liquidation, and the Disposition Effect," Management Science, INFORMS, vol. 58(2), pages 445-460, February.
    10. Weber, Martin & Welfens, Frank, 2007. "An Individual Level Analysis of the Disposition Effect: Empirical and Experimental Evidence," Sonderforschungsbereich 504 Publications 07-45, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    11. Hendershott, Terrence & Riordan, Ryan, 2013. "Algorithmic Trading and the Market for Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(4), pages 1001-1024, August.
    12. Weber, Martin & Camerer, Colin F., 1998. "The disposition effect in securities trading: an experimental analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 167-184, January.
    13. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    14. Ahmed, Anwer S. & Takeda, Carolyn, 1995. "Stock market valuation of gains and losses on commercial banks' investment securities An empirical analysis," Journal of Accounting and Economics, Elsevier, vol. 20(2), pages 207-225, September.
    15. Machina, Mark J, 1987. "Choice under Uncertainty: Problems Solved and Unsolved," Journal of Economic Perspectives, American Economic Association, vol. 1(1), pages 121-154, Summer.
    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. Karolis Liaudinskas, 2022. "Human vs. Machine: Disposition Effect among Algorithmic and Human Day Traders," Working Paper 2022/6, Norges Bank.
    2. Brettschneider, Julia & Burro, Giovanni & Henderson, Vicky, 2021. "Wide framing disposition effect: An empirical study," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 330-347.
    3. Hermann, Daniel & Mußhoff, Oliver & Rau, Holger A., 2019. "The disposition effect when deciding on behalf of others," Journal of Economic Psychology, Elsevier, vol. 74(C).
    4. Urs Fischbacher & Gerson Hoffmann & Simeon Schudy, 2017. "The Causal Effect of Stop-Loss and Take-Gain Orders on the Disposition Effect," The Review of Financial Studies, Society for Financial Studies, vol. 30(6), pages 2110-2129.
    5. Weber, Martin & Welfens, Frank, 2007. "How do Markets React to Fundamental Shocks? An Experimental Analysis on Underreaction and Momentum," Sonderforschungsbereich 504 Publications 07-42, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    6. Cafferata, Alessia & Tramontana, Fabio, 2022. "Disposition Effect and its outcome on endogenous price fluctuations," MPRA Paper 113904, University Library of Munich, Germany.
    7. David Hirshleife, 2015. "Behavioral Finance," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 133-159, December.
    8. Frydman, Cary & Rangel, Antonio, 2014. "Debiasing the disposition effect by reducing the saliency of information about a stock's purchase price," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 541-552.
    9. Henderson, Vicky & Hobson, David & Tse, Alex S.L., 2018. "Probability weighting, stop-loss and the disposition effect," Journal of Economic Theory, Elsevier, vol. 178(C), pages 360-397.
    10. Barber, Brad M. & Odean, Terrance, 2013. "The Behavior of Individual Investors," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1533-1570, Elsevier.
    11. Vicky Henderson & Jonathan Muscat, 2020. "Partial liquidation under reference-dependent preferences," Finance and Stochastics, Springer, vol. 24(2), pages 335-357, April.
    12. Alex S. L. Tse & Harry Zheng, 2019. "Speculative Trading, Prospect Theory and Transaction Costs," Papers 1911.10106, arXiv.org, revised Oct 2022.
    13. Youki Kohsaka & Grzegorz Mardyla & Shinji Takenaka & Yoshiro Tsutsui, 2017. "Disposition Effect and Diminishing Sensitivity: An Analysis Based on a Simulated Experimental Stock Market," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 18(2), pages 189-201, April.
    14. David S. Sun & Shih-Chuan Tsai & Wei Wang, 2013. "Behavioral Investment Strategy Matters: A Statistical Arbitrage Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S3), pages 47-61, July.
    15. Ballestra, Luca Vincenzo & Guizzardi, Andrea & Mazzucchelli, Lorenzo, 2024. "Integrating narrow and wide framing disposition effect: A novel approach incorporating perceived risk and realized asset performance," Journal of Economic Behavior & Organization, Elsevier, vol. 220(C), pages 422-432.
    16. Choi, Darwin, 2019. "Disposition sales and stock market liquidity," Journal of Financial Markets, Elsevier, vol. 45(C), pages 19-36.
    17. Kahya, Evrim Hilal & Ekinci, Cumhur, 2022. "Disposition bias among Borsa Istanbul investors: What do we know about type, size and trading frequency?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 35(C).
    18. Jakusch, Sven Thorsten & Meyer, Steffen & Hackethal, Andreas, 2019. "Taming models of prospect theory in the wild? Estimation of Vlcek and Hens (2011)," SAFE Working Paper Series 146, Leibniz Institute for Financial Research SAFE, revised 2019.
    19. Markus Glaser & Martin Weber, 2007. "Overconfidence and trading volume," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 32(1), pages 1-36, June.
    20. Janssen, Dirk-Jan & Li, Jiangyan & Qiu, Jianying & Weitzel, Utz, 2020. "The disposition effect and underreaction to private information," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).

    More about this item

    Keywords

    disposition effect; algorithmic trading; financial markets; rationality; automation;
    All these keywords.

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

    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:bge:wpaper:1133. 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: Bruno Guallar (email available below). General contact details of provider: https://edirc.repec.org/data/bargses.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.