IDEAS home Printed from https://ideas.repec.org/a/gam/jijfss/v11y2023i2p73-d1159533.html
   My bibliography  Save this article

Winner Strategies in a Simulated Stock Market

Author

Listed:
  • Ali Taherizadeh

    (Graduate School of Management and Economics, Sharif University of Technology, Teymoori Sq., Tehran 145997-3941, Iran)

  • Shiva Zamani

    (Graduate School of Management and Economics, Sharif University of Technology, Teymoori Sq., Tehran 145997-3941, Iran)

Abstract

In this study, we explore the dynamics of the stock market using an agent-based simulation platform. Our approach involves creating a multi-strategy market where each agent considers both fundamental and technical factors when determining their strategy. The agents vary in their approach to these factors and the time interval they use for technical analysis. Our findings indicate that investing heavily in reducing the value–price gap was a successful strategy, even in markets where there were no trading forces to reduce this gap. Furthermore, our results remain consistent across various modifications to the simulation’s structure.

Suggested Citation

  • Ali Taherizadeh & Shiva Zamani, 2023. "Winner Strategies in a Simulated Stock Market," IJFS, MDPI, vol. 11(2), pages 1-17, May.
    • Handle: RePEc:gam:jijfss:v:11:y:2023:i:2:p:73-:d:1159533
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7072/11/2/73/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7072/11/2/73/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Palczewski, Jan & Schenk-Hoppé, Klaus Reiner & Wang, Tongya, 2016. "Itchy feet vs cool heads: Flow of funds in an agent-based financial market," Journal of Economic Dynamics and Control, Elsevier, vol. 63(C), pages 53-68.
    2. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    3. Westerhoff Frank H., 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 195-227, April.
    4. Hakansson, Nils H, 1971. "Multi-Period Mean-Variance Analysis: Toward A General Theory of Portfolio Choice," Journal of Finance, American Finance Association, vol. 26(4), pages 857-884, September.
    5. Shleifer, Andrei & Vishny, Robert W, 1997. "The Limits of Arbitrage," Journal of Finance, American Finance Association, vol. 52(1), pages 35-55, March.
    6. Arthur, W.B. & Holland, J.H. & LeBaron, B. & Palmer, R. & Tayler, P., 1996. "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Working papers 9625, Wisconsin Madison - Social Systems.
    7. Thorsten Hens & Klaus R. Schenk‐Hoppé, 2020. "Patience Is a Virtue: In Value Investing," International Review of Finance, International Review of Finance Ltd., vol. 20(4), pages 1019-1031, December.
    8. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    9. Iwao Maeda & David deGraw & Michiharu Kitano & Hiroyasu Matsushima & Hiroki Sakaji & Kiyoshi Izumi & Atsuo Kato, 2020. "Deep Reinforcement Learning in Agent Based Financial Market Simulation," JRFM, MDPI, vol. 13(4), pages 1-17, April.
    10. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    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. Michael Senescall & Rand Kwong Yew Low, 2024. "Quantitative Portfolio Management: Review and Outlook," Mathematics, MDPI, vol. 12(18), pages 1-25, September.
    2. Söhnke M. Bartram & Harald Lohre & Peter F. Pope & Ananthalakshmi Ranganathan, 2021. "Navigating the factor zoo around the world: an institutional investor perspective," Journal of Business Economics, Springer, vol. 91(5), pages 655-703, July.
    3. Bucher, Melk C., 2017. "Investor Attention and Sentiment: Risk or Anomaly?," Working Papers on Finance 1712, University of St. Gallen, School of Finance.
    4. Stephen A. Gorman & Frank J. Fabozzi, 2021. "The ABC’s of the alternative risk premium: academic roots," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 405-436, October.
    5. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, July.
    6. Lu Zhang, 2017. "The Investment CAPM," European Financial Management, European Financial Management Association, vol. 23(4), pages 545-603, September.
    7. Lin, Yu-En & Teng, Shi & Cheng, Teng-Yuan & Wang, Qianqian & Hu, Chunyang, 2024. "The influence of deleveraging the excessive debt firms on investment efficiency," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 2130-2149.
    8. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    9. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    10. Chue, Timothy K. & Gul, Ferdinand A. & Mian, G. Mujtaba, 2019. "Aggregate investor sentiment and stock return synchronicity," Journal of Banking & Finance, Elsevier, vol. 108(C).
    11. Linnenluecke, Martina K. & Chen, Xiaoyan & Ling, Xin & Smith, Tom & Zhu, Yushu, 2017. "Research in finance: A review of influential publications and a research agenda," Pacific-Basin Finance Journal, Elsevier, vol. 43(C), pages 188-199.
    12. Geertsema, Paul & Lu, Helen, 2020. "The correlation structure of anomaly strategies," Journal of Banking & Finance, Elsevier, vol. 119(C).
    13. Obaid, Khaled & Pukthuanthong, Kuntara, 2022. "A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news," Journal of Financial Economics, Elsevier, vol. 144(1), pages 273-297.
    14. Lars Hornuf & Gül Yüksel, 2022. "The Performance of Socially Responsible Investments: A Meta-Analysis," CESifo Working Paper Series 9724, CESifo.
    15. Qi Shi & Bin Li & Adrian (Wai Kong) Cheung & Richard Chung, 2017. "Augmenting the intertemporal CAPM with inflation: Further evidence from alternative models," Australian Journal of Management, Australian School of Business, vol. 42(4), pages 653-672, November.
    16. Scott Condie & Lars Stentoft & Marie-Louise Vierø, 2023. "Unawareness Premia," Economics Working Papers 2023-09, Department of Economics and Business Economics, Aarhus University.
    17. Zhu, Zhaobo & Ding, Wenjie & Jin, Yi & Shen, Dehua, 2023. "Dissecting the idiosyncratic volatility puzzle: A fundamental analysis approach," Research in International Business and Finance, Elsevier, vol. 66(C).
    18. Lu Zhang, 2019. "Q-factors and Investment CAPM," NBER Working Papers 26538, National Bureau of Economic Research, Inc.
    19. Ho, Kin-Yip & An, Jiyoun, 2020. "Decomposing the value premium: The role of intangible information in the Chinese stock market," Emerging Markets Review, Elsevier, vol. 44(C).
    20. Kan, Raymond & Wang, Xiaolu & Zheng, Xinghua, 2024. "In-sample and out-of-sample Sharpe ratios of multi-factor asset pricing models," Journal of Financial Economics, Elsevier, vol. 155(C).

    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:gam:jijfss:v:11:y:2023:i:2:p:73-:d:1159533. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.