IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v554y2020ics0378437119321697.html
   My bibliography  Save this article

Loss aversion, overconfidence and their effects on a virtual stock exchange

Author

Listed:
  • Bertella, Mario A.
  • Silva, Jonathas N.
  • Stanley, H. Eugene

Abstract

This paper studies the effects of overconfidence and loss aversion in an artificial stock exchange. When we model only fundamentalists we find results that are consistent with homogeneous agent models. Adding 5% of chartists increases the stock return rate but also increases other variables, including volatility and kurtosis. We find that the inclusion of confidence in 5% of chartists raises the trading volume as empirical evidences corroborate and price volatility increases considerably. On the other hand, loss aversion in 5% of chartists substantially decreases the trading volume, although chartist traders now have a higher percentage of stocks in their portfolios, and a buy and hold strategy is adopted to mitigate losses.

Suggested Citation

  • Bertella, Mario A. & Silva, Jonathas N. & Stanley, H. Eugene, 2020. "Loss aversion, overconfidence and their effects on a virtual stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    • Handle: RePEc:eee:phsmap:v:554:y:2020:i:c:s0378437119321697
    DOI: 10.1016/j.physa.2019.123909
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119321697
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.123909?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. Gervais, Simon & Odean, Terrance, 2001. "Learning to be Overconfident," Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 1-27.
    2. Terrance Odean., 1996. "Volume, Volatility, Price and Profit When All Trader Are Above Average," Research Program in Finance Working Papers RPF-266, University of California at Berkeley.
    3. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    4. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    5. Gordon, Myron J & Paradis, G E & Rorke, C H, 1972. "Experimental Evidence on Alternative Portfolio Decision Rules," American Economic Review, American Economic Association, vol. 62(1), pages 107-118, March.
    6. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    7. Levy, Haim, 1994. "Absolute and Relative Risk Aversion: An Experimental Study," Journal of Risk and Uncertainty, Springer, vol. 8(3), pages 289-307, May.
    8. Hiroshi Takahashi & Takao Terano, 2003. "Agent-Based Approach to Investors? Behavior and Asset Price Fluctuation in Financial Markets," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(3), pages 1-3.
    9. 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..
    10. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    11. Mario A Bertella & Felipe R Pires & Ling Feng & Harry Eugene Stanley, 2014. "Confidence and the Stock Market: An Agent-Based Approach," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-9, January.
    12. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    13. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    14. Mario A Bertella & Felipe R Pires & Henio H A Rego & Jonathas N Silva & Irena Vodenska & H Eugene Stanley, 2017. "Confidence and self-attribution bias in an artificial stock market," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-20, February.
    15. Friend, Irwin & Blume, Marshall E, 1975. "The Demand for Risky Assets," American Economic Review, American Economic Association, vol. 65(5), pages 900-922, December.
    16. Kroll, Yoram & Levy, Haim & Rapoport, Amnon, 1988. "Experimental Tests of the Separation Theorem and the Capital Asset Pricing Model," American Economic Review, American Economic Association, vol. 78(3), pages 500-519, June.
    17. Levy, Haim & Levy, Moshe & Solomon, Sorin, 2000. "Microscopic Simulation of Financial Markets," Elsevier Monographs, Elsevier, edition 1, number 9780124458901.
    18. Terrance Odean, 1999. "Do Investors Trade Too Much?," American Economic Review, American Economic Association, vol. 89(5), pages 1279-1298, December.
    19. Terrance Odean, 1998. "Volume, Volatility, Price, and Profit When All Traders Are Above Average," Journal of Finance, American Finance Association, vol. 53(6), pages 1887-1934, 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. Zhou, Xinxing & Gao, Yan & Wang, Ping & Zhu, Bangzhu, 2022. "Examining the overconfidence and overreaction in China’s carbon markets," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 472-489.
    2. Ramzi Boussaidi, 2022. "Implications of the overconfidence bias in presence of private information: Evidence from MENA stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3660-3678, July.

    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. Ramzi Boussaidi, 2022. "Implications of the overconfidence bias in presence of private information: Evidence from MENA stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3660-3678, July.
    2. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    3. Chuang, Wen-I & Lee, Bong-Soo, 2006. "An empirical evaluation of the overconfidence hypothesis," Journal of Banking & Finance, Elsevier, vol. 30(9), pages 2489-2515, September.
    4. Kenneth Yung & Yen-Chih Liu, 2009. "Implications of futures trading volume: Hedgers versus speculators," Journal of Asset Management, Palgrave Macmillan, vol. 10(5), pages 318-337, December.
    5. Helen X. H. Bao & Steven Haotong Li, 2020. "Investor Overconfidence and Trading Activity in the Asia Pacific REIT Markets," JRFM, MDPI, vol. 13(10), pages 1-21, September.
    6. Pereira Reichhardt, Joaquín & Iqbal, Tabassum, 2014. "Investment Decisions: Are we fully-Rational?," MPRA Paper 57686, University Library of Munich, Germany.
    7. Mushinada, Venkata Narasimha Chary, 2020. "Are individual investors irrational or adaptive to market dynamics?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    8. Krzysztof Zieliński, 2012. "Błędy popełniane w procesie podejmowania decyzji w świetle behawioralnej ekonomii finansowej," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 31.
    9. Leković Milјan, 2020. "Cognitive Biases as an Integral Part of Behavioral Finance," Economic Themes, Sciendo, vol. 58(1), pages 75-96, March.
    10. Laurent Germain & Fabrice Rousseau & Anne Vanhems, 2014. "Irrational Market Makers," Finance, Presses universitaires de Grenoble, vol. 35(1), pages 107-145.
    11. 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.
    12. Andreas Oehler & Julian Schneider, 2023. "Social trading: do signal providers trigger gambling?," Review of Managerial Science, Springer, vol. 17(4), pages 1269-1331, May.
    13. Jaya M. Prosad & Sujata Kapoor & Jhumur Sengupta & Saurav Roychoudhary, 2017. "Overconfidence and Disposition Effect in Indian Equity Market: An Empirical Evidence," Global Business Review, International Management Institute, vol. 19(5), pages 1303-1321, October.
    14. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.
    15. Zhou, Xinxing & Gao, Yan & Wang, Ping & Zhu, Bangzhu, 2022. "Examining the overconfidence and overreaction in China’s carbon markets," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 472-489.
    16. Glaser, Markus & Nöth, Markus & Weber, Martin, 2003. "Behavioral finance," Papers 03-14, Sonderforschungsbreich 504.
    17. Jitender Kumar & Neha Prince, 2022. "Overconfidence bias in the Indian stock market in diverse market situations: an empirical study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 3031-3047, December.
    18. David Hirshleife, 2015. "Behavioral Finance," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 133-159, December.
    19. 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.
    20. Fabrice Rousseau & Laurent Germain & Fabrice Rousseau & Anne Vanhems, 2008. "Irrational Financial Markets," Economics Department Working Paper Series n1870108.pdf, Department of Economics, National University of Ireland - Maynooth.

    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:phsmap:v:554:y:2020:i:c:s0378437119321697. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.