IDEAS home Printed from https://ideas.repec.org/p/ven/wpaper/202403.html
   My bibliography  Save this paper

Learning Whether to Be Informed in an Agent-Based Evolutionary Market Model

Author

Listed:
  • Paolo Pellizzari

    (Department of Economics, Ca’ Foscari University of Venice)

Abstract

Can traders in a financial market learn whether to be informed and which information to use in their demand for risky assets? We describe in this paper an agent-based model where heterogeneous traders seek short-term profits and differ in their choices to use or discard some signals. In the model, a vector of fresh news/signals is available at every period and some (but not all) the signals affect the stochastic payoff of the stock. Under an evolutionary dynamics favouring higher myopic returns we find that, in equilibrium, traders mostly end up in either discarding all signals or being (perfectly) informed using all the relevant signals (paying the related costs). Moreover, the rate of use of information strongly depends on the "complexity" of the market: an excessively large abundance of signals to be screened or a high volatility of the market, result in large shares of passive agents who overestimate the market's risk; conversely, low market complexity is associated with a more intense use of information and aggressiveness of informed traders. Evolutionary models and Agent-based models and Information in financial markets

Suggested Citation

  • Paolo Pellizzari, 2024. "Learning Whether to Be Informed in an Agent-Based Evolutionary Market Model," Working Papers 2024: 03, Department of Economics, University of Venice "Ca' Foscari".
    • Handle: RePEc:ven:wpaper:2024:03
    as

    Download full text from publisher

    File URL: https://www.unive.it/web/fileadmin/user_upload/dipartimenti/DEC/doc/Pubblicazioni_scientifiche/working_papers/2024/WP_DSE_pellizzari_03_24.pdf
    File Function: First version, anno
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    2. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Klaus Schredelseker, 2014. "Pascal's Wager and Information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 455-470, September.
    3. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    4. Shlomo Benartzi & Richard H. Thaler, 1995. "Myopic Loss Aversion and the Equity Premium Puzzle," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(1), pages 73-92.
    5. Mehra, Rajnish & Prescott, Edward C., 1985. "The equity premium: A puzzle," Journal of Monetary Economics, Elsevier, vol. 15(2), pages 145-161, March.
    6. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, 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. Lukas Menkhoff & Mark P. Taylor, 2007. "The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis," Journal of Economic Literature, American Economic Association, vol. 45(4), pages 936-972, December.
    2. Phan, Thuy Chung & Rieger, Marc Oliver & Wang, Mei, 2018. "What leads to overtrading and under-diversification? Survey evidence from retail investors in an emerging market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 19(C), pages 39-55.
    3. Committee, Nobel Prize, 2013. "Understanding Asset Prices," Nobel Prize in Economics documents 2013-1, Nobel Prize Committee.
    4. Mr. Bernhard Eckwert & Mr. Burkhard Drees, 2005. "Asset Mispricing Due to Cognitive Dissonance," IMF Working Papers 2005/009, International Monetary Fund.
    5. Xue-Zhong He & Lei Shi, 2010. "Differences in Opinion and Risk Premium," Research Paper Series 271, Quantitative Finance Research Centre, University of Technology, Sydney.
    6. Siddiqi, Hammad, 2015. "Anchoring and Adjustment Heuristic: A Unified Explanation for Equity Puzzles," MPRA Paper 68729, University Library of Munich, Germany.
    7. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    8. Uri Gneezy & Jan Potters, 1997. "An Experiment on Risk Taking and Evaluation Periods," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(2), pages 631-645.
    9. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    10. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    11. Iñigo Iturbe-Ormaetxe & Giovanni Ponti & Josefa Tomás, 2016. "Myopic Loss Aversion under Ambiguity and Gender Effects," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-11, December.
    12. Zeisberger, Stefan & Langer, Thomas & Trede, Mark, 2007. "A note on myopic loss aversion and the equity premium puzzle," Finance Research Letters, Elsevier, vol. 4(2), pages 127-136, June.
    13. Stephan Schulmeister, 2000. "Technical Analysis and Exchange Rate Dynamics," WIFO Studies, WIFO, number 25857, August.
    14. Kun Xing & Honggang Li, 2024. "The profitability of interacting trading strategies from an ecological perspective," Annals of Finance, Springer, vol. 20(3), pages 377-394, September.
    15. Eriksen, Kristoffer W. & Kvaløy, Ola, 2014. "Myopic risk-taking in tournaments," Journal of Economic Behavior & Organization, Elsevier, vol. 97(C), pages 37-46.
    16. Enrico G. De Giorgi & Thierry Post, 2011. "Loss Aversion with a State-Dependent Reference Point," Management Science, INFORMS, vol. 57(6), pages 1094-1110, June.
    17. 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.
    18. Prat, Georges, 2013. "Equity risk premium and time horizon: What do the U.S. secular data say?," Economic Modelling, Elsevier, vol. 34(C), pages 76-88.
    19. Michele Costola & Massimiliano Caporin, 2016. "Rational Learning For Risk-Averse Investors By Conditioning On Behavioral Choices," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-26, March.
    20. Abootaleb Shirvani & Stoyan V. Stoyanov & Frank J. Fabozzi & Svetlozar T. Rachev, 2019. "Equity Premium Puzzle or Faulty Economic Modelling?," Papers 1909.13019, arXiv.org, revised Jan 2020.

    More about this item

    Keywords

    financial markets w information; agent-based models; evolutionary game theory; equity premium puzzle;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

    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:ven:wpaper:2024:03. 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: Sassano Sonia (email available below). General contact details of provider: https://edirc.repec.org/data/dsvenit.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.