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Are random trading strategies more successful than technical ones?

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  • A. E. Biondo
  • A. Pluchino
  • A. Rapisarda
  • D. Helbing

Abstract

In this paper we explore the specific role of randomness in financial markets, inspired by the beneficial role of noise in many physical systems and in previous applications to complex socio- economic systems. After a short introduction, we study the performance of some of the most used trading strategies in predicting the dynamics of financial markets for different international stock exchange indexes, with the goal of comparing them with the performance of a completely random strategy. In this respect, historical data for FTSE-UK, FTSE-MIB, DAX, and S&P500 indexes are taken into account for a period of about 15-20 years (since their creation until today).

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  • A. E. Biondo & A. Pluchino & A. Rapisarda & D. Helbing, 2013. "Are random trading strategies more successful than technical ones?," Papers 1303.4351, arXiv.org, revised Jul 2013.
    • Handle: RePEc:arx:papers:1303.4351
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    Cited by:

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    2. Alessandro Pluchino & Alessio. E. Biondo & Andrea Rapisarda, 2018. "Exploring the role of talent and luck in getting success," Papers 1811.05206, arXiv.org.
    3. N'yoma Diamond & Grant Perkins, 2022. "Using Intermarket Data to Evaluate the Efficient Market Hypothesis with Machine Learning," Papers 2212.08734, arXiv.org, revised Dec 2022.
    4. Tanimoto, Jun & Sagara, Hirokji, 2015. "How the indirect reciprocity with co-evolving norm and strategy for 2 × 2 prisoner’s dilemma game works for emerging cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 595-602.
    5. Aleksejus Kononovicius & Vygintas Gontis, 2014. "Herding interactions as an opportunity to prevent extreme events in financial markets," Papers 1409.8024, arXiv.org, revised May 2015.
    6. Yuri S. Popkov & Alexey Yu. Popkov & Yuri A. Dubnov & Dimitri Solomatine, 2020. "Entropy-Randomized Forecasting of Stochastic Dynamic Regression Models," Mathematics, MDPI, vol. 8(7), pages 1-20, July.
    7. Chengwei Liu, 2021. "In luck we trust: Capturing the diversity bonus through random selection," Journal of Organization Design, Springer;Organizational Design Community, vol. 10(2), pages 85-91, June.
    8. Tran Phuoc & Pham Thi Kim Anh & Phan Huy Tam & Chien V. Nguyen, 2024. "Applying machine learning algorithms to predict the stock price trend in the stock market – The case of Vietnam," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.
    9. L. S. Di Mauro & A. Pluchino & A. E. Biondo, 2018. "A Game of Tax Evasion: evidences from an agent-based model," Papers 1809.08146, arXiv.org.
    10. Condorelli, Stefano, 2018. "Price momentum and the 1719-20 bubbles: A method to compare and interpret booms and crashes in asset markets," MPRA Paper 89888, University Library of Munich, Germany.
    11. Alessio Emanuele Biondo, 2018. "Order book microstructure and policies for financial stability," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 35(1), pages 196-218, March.
    12. David Garcia & Frank Schweitzer, 2015. "Social signals and algorithmic trading of Bitcoin," Papers 1506.01513, arXiv.org, revised Sep 2015.
    13. Yan Li & Bo Zheng & Ting-Ting Chen & Xiong-Fei Jiang, 2017. "Fluctuation-driven price dynamics and investment strategies," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-15, December.
    14. Stefan, F.M. & Atman, A.P.F., 2023. "Asymmetric rate of returns and wealth distribution influenced by the introduction of technical analysis into a behavioral agent-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    15. Alessio Emanuele Biondo & Alfio Giarlotta & Alessandro Pluchino & Andrea Rapisarda, 2016. "Perfect Information vs Random Investigation: Safety Guidelines for a Consumer in the Jungle of Product Differentiation," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-26, January.
    16. Biondo, A.E. & Pluchino, A. & Rapisarda, A., 2018. "Modeling surveys effects in political competitions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 714-726.
    17. Alessandro Pluchino & Giulio Burgio & Andrea Rapisarda & Alessio Emanuele Biondo & Alfredo Pulvirenti & Alfredo Ferro & Toni Giorgino, 2019. "Exploring the role of interdisciplinarity in physics: Success, talent and luck," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-15, June.
    18. Alessandro Pluchino & Alessio Emanuele Biondo & Andrea Rapisarda, 2018. "Talent Versus Luck: The Role Of Randomness In Success And Failure," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(03n04), pages 1-31, May.
    19. Huishu Zhang & Jianrong Wei & Jiping Huang, 2014. "Scaling and Predictability in Stock Markets: A Comparative Study," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-5, March.
    20. Biondo, Alessio Emanuele, 2017. "Learning to forecast, risk aversion, and microstructural aspects of financial stability," Economics Discussion Papers 2017-104, Kiel Institute for the World Economy (IfW Kiel).
    21. Caserta, Maurizio & Pluchino, Alessandro & Rapisarda, Andrea & Spagano, Salvatore, 2021. "Why lot? How sortition could help representative democracy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    22. F. M. Stefan & A. P. F. Atman, 2017. "Asymmetric return rates and wealth distribution influenced by the introduction of technical analysis into a behavioral agent based model," Papers 1711.08282, arXiv.org.

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