IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v294y2001i1p213-225.html
   My bibliography  Save this article

Learning the optimal trading strategy

Author

Listed:
  • Franci, Fabio
  • Marschinski, Robert
  • Matassini, Lorenzo

Abstract

Within a realistic model of the stockmarket, we derive the most successful trading strategy. We first identify the agent who has realized the largest percentual gain and then analyze all the operations this trader has performed during the simulation run. We report them in a proper trading space and we extend the model, introducing an additional operator acting with the help of a look up table derived from a clusterization of space. We discuss the robustness of this optimal strategy, its performance and the applicability to real markets.

Suggested Citation

  • Franci, Fabio & Marschinski, Robert & Matassini, Lorenzo, 2001. "Learning the optimal trading strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 294(1), pages 213-225.
    • Handle: RePEc:eee:phsmap:v:294:y:2001:i:1:p:213-225
    DOI: 10.1016/S0378-4371(01)00132-7
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437101001327
    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/S0378-4371(01)00132-7?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. Jean-Philippe Bouchaud & Andrew Matacz & Marc Potters, 2001. "The leverage effect in financial markets: retarded volatility and market panic," Science & Finance (CFM) working paper archive 0101120, Science & Finance, Capital Fund Management.
    2. Takayasu, H. & Takayasu, M., 1999. "Critical fluctuations of demand and supply," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 269(1), pages 24-29.
    3. Hendrik J. Blok, 2000. "On the nature of the stock market: Simulations and experiments," Papers cond-mat/0010211, arXiv.org.
    4. Ramsey, James B., 1996. "On the existence of macro variables and of macro relationships," Journal of Economic Behavior & Organization, Elsevier, vol. 30(3), pages 275-299, September.
    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. Ravi Kashyap, 2019. "Concepts, Components and Collections of Trading Strategies and Market Color," Papers 1910.02144, arXiv.org, revised Jan 2020.
    2. Matassini, Lorenzo, 2001. "The trading rectangle strategy within book models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 301(1), pages 449-456.
    3. Boer-Sorban, K. & de Bruin, A. & Kaymak, U., 2005. "On the Design of Artificial Stock Markets," ERIM Report Series Research in Management ERS-2005-001-LIS, 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.

    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. Matassini, Lorenzo & Franci, Fabio, 2001. "On financial markets trading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(3), pages 526-542.
    2. Yang, Qing-Qing & Ching, Wai-Ki & Gu, Jia-Wen & Siu, Tak-Kuen, 2018. "Market-making strategy with asymmetric information and regime-switching," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 408-433.
    3. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    4. Linton, Oliver & Whang, Yoon-Jae & Yen, Yu-Min, 2016. "A nonparametric test of a strong leverage hypothesis," Journal of Econometrics, Elsevier, vol. 194(1), pages 153-186.
    5. Staccioli, Jacopo & Napoletano, Mauro, 2021. "An agent-based model of intra-day financial markets dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 331-348.
    6. Marcus Alexander Ong, 2015. "An information theoretic analysis of stock returns, volatility and trading volumes," Applied Economics, Taylor & Francis Journals, vol. 47(36), pages 3891-3906, August.
    7. Zhang, Jiu & Jin, Li-Fu & Zheng, Bo & Li, Yan & Jiang, Xiong-Fei, 2022. "Simplified calculations of time correlation functions in non-stationary complex financial systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    8. T. T. Chen & B. Zheng & Y. Li & X. F. Jiang, 2017. "New approaches in agent-based modeling of complex financial systems," Papers 1703.06840, arXiv.org.
    9. Sebastien Valeyre, 2022. "Optimal trend following portfolios," Papers 2201.06635, arXiv.org.
    10. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    11. Rituparna Sen & Manavathi Subramaniam, 2019. "Stylized Facts of the Indian Stock Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(4), pages 479-493, December.
    12. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    13. Endres, Sylvia & Stübinger, Johannes, 2018. "A flexible regime switching model with pairs trading application to the S&P 500 high-frequency stock returns," FAU Discussion Papers in Economics 07/2018, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    14. Gu, Gao-Feng & Zhou, Wei-Xing, 2007. "Statistical properties of daily ensemble variables in the Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(2), pages 497-506.
    15. Liu, Chang & Chang, Chuo, 2021. "Combination of transition probability distribution and stable Lorentz distribution in stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    16. Jan Jakub Szczygielski & Chimwemwe Chipeta, 2023. "Properties of returns and variance and the implications for time series modelling: Evidence from South Africa," Modern Finance, Modern Finance Institute, vol. 1(1), pages 35-55.
    17. Pierre Cizeau & Marc Potters & Jean-Philippe Bouchaud, 2000. "Correlation structure of extreme stock returns," Papers cond-mat/0006034, arXiv.org, revised Jan 2001.
    18. Li, Chao & Shang, Pengjian, 2018. "Complexity analysis based on generalized deviation for financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 118-128.
    19. Andersen, J.V. & Sornette, D., 2004. "Fearless versus fearful speculative financial bubbles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 337(3), pages 565-585.
    20. Lisa Borland & Jean-Philippe Bouchaud & Jean-Francois Muzy & Gilles Zumbach, 2005. "The Dynamics of Financial Markets -- Mandelbrot's multifractal cascades, and beyond," Science & Finance (CFM) working paper archive 500061, Science & Finance, Capital Fund Management.

    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:294:y:2001:i:1:p:213-225. 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.