IDEAS home Printed from https://ideas.repec.org/p/war/wpaper/2025-14.html
   My bibliography  Save this paper

Can Artificial Intelligence Trade the Stock Market?

Author

Listed:
  • Jędrzej Maskiewicz

    (Quantitative Finance Research Group, Department of Quantitative Finance, Faculty of Economic Sciences, University of Warsaw)

  • Paweł Sakowski

    (Quantitative Finance Research Group, Department of Quantitative Finance, Faculty of Economic Sciences, University of Warsaw)

Abstract

The paper explores the use of Deep Reinforcement Learning (DRL) in stock market trading, focusing on two algorithms: Double Deep Q-Network (DDQN) and Proximal Policy Optimization (PPO) and compares them with Buy and Hold benchmark. It evaluates these algorithms across three currency pairs, the S&P 500 index and Bitcoin, on the daily data in the period of 2019-2023. The results demonstrate DRL's effectiveness in trading and its ability to manage risk by strategically avoiding trades in unfavorable conditions, providing a substantial edge over classical approaches, based on supervised learning in terms of risk-adjusted returns.

Suggested Citation

  • Jędrzej Maskiewicz & Paweł Sakowski, 2025. "Can Artificial Intelligence Trade the Stock Market?," Working Papers 2025-14, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2025-14
    as

    Download full text from publisher

    File URL: https://www.wne.uw.edu.pl/download_file/5608/0
    File Function: First version, 2025
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tidor-Vlad Pricope, 2021. "Deep Reinforcement Learning in Quantitative Algorithmic Trading: A Review," Papers 2106.00123, arXiv.org.
    2. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, 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. Jk{e}drzej Maskiewicz & Pawe{l} Sakowski, 2025. "Can Artificial Intelligence Trade the Stock Market?," Papers 2506.04658, arXiv.org.
    2. David M. Ritzwoller & Joseph P. Romano, 2019. "Uncertainty in the Hot Hand Fallacy: Detecting Streaky Alternatives to Random Bernoulli Sequences," Papers 1908.01406, arXiv.org, revised Apr 2021.
    3. Shazia Ghani, 2011. "A re-visit to Minsky after 2007 financial meltdown," Post-Print halshs-01027435, HAL.
    4. Christiane Goodfellow & Dirk Schiereck & Steffen Wippler, 2013. "Are behavioural finance equity funds a superior investment? A note on fund performance and market efficiency," Journal of Asset Management, Palgrave Macmillan, vol. 14(2), pages 111-119, April.
    5. Cagli, Efe Caglar & Taskin, Dilvin & Evrim Mandaci, Pınar, 2019. "The short- and long-run efficiency of energy, precious metals, and base metals markets: Evidence from the exponential smooth transition autoregressive models," Energy Economics, Elsevier, vol. 84(C).
    6. Andrew Weinbach & Rodney J. Paul, 2009. "National television coverage and the behavioural bias of bettors: the American college football totals market," International Gambling Studies, Taylor & Francis Journals, vol. 9(1), pages 55-66, April.
    7. Oxelheim, Lars & Rafferty, Michael, 2005. "On the static efficiency of secondary bond markets," Journal of Multinational Financial Management, Elsevier, vol. 15(2), pages 117-135, April.
    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. Nuruddeen Usman & Kodili Nwanneka & Nduka, 2023. "Announcement Effect of COVID-19 on Cryptocurrencies," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 3(3), pages 1-4.
    10. Robert C. Merton, 2006. "Paul Samuelson and Financial Economics," The American Economist, Sage Publications, vol. 50(2), pages 9-31, October.
    11. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    12. Camille Baulant & Nivine Albouz, 2021. "Has financial globalization since 1990 reduced income inequality: the role of rating announcements on the volatility and the returns of the Brazilian Financial Market [Les annonces de notation souv," Working Papers hal-03258994, HAL.
    13. Carlo Rosa & Giovanni Verga, 2006. "The Impact of Central Bank Announcements on Asset Prices in Real Time: Testing the Efficiency of the Euribor Futures Market," CEP Discussion Papers dp0764, Centre for Economic Performance, LSE.
    14. Choi, Gahyun & Park, Kwangyeol & Yi, Eojin & Ahn, Kwangwon, 2023. "Price fairness: Clean energy stocks and the overall market," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    15. Sellin, Peter, 1998. "Monetary Policy and the Stock Market: Theory and Empirical Evidence," Working Paper Series 72, Sveriges Riksbank (Central Bank of Sweden).
    16. Thomas Delcey, 2019. "Samuelson vs Fama on the Efficient Market Hypothesis: The Point of View of Expertise [Samuelson vs Fama sur l’efficience informationnelle des marchés financiers : le point de vue de l’expertise]," Post-Print hal-01618347, HAL.
    17. Spira, Robin, 2024. "How does ESG rating disagreement influence analyst forecast dispersion?," Junior Management Science (JUMS), Junior Management Science e. V., vol. 9(3), pages 1769-1804.
    18. Dhanya Jothimani & Ravi Shankar & Surendra S. Yadav, 2016. "Discrete Wavelet Transform-Based Prediction of Stock Index: A Study on National Stock Exchange Fifty Index," Papers 1605.07278, arXiv.org.
    19. Neely, Christopher J. & Weller, Paul, 2000. "Predictability in International Asset Returns: A Reexamination," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(4), pages 601-620, December.
    20. Berna Karali & Scott H. Irwin & Olga Isengildina‐Massa, 2020. "Supply Fundamentals and Grain Futures Price Movements," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 548-568, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    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:war:wpaper:2025-14. 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: Jacek Rapacz (email available below). General contact details of provider: https://edirc.repec.org/data/fesuwpl.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.