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Learning the optimal trading strategy

Author

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. Hendrik J. Blok, 2000. "On the nature of the stock market: Simulations and experiments," Papers cond-mat/0010211, arXiv.org.
    3. 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.
    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.
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    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.

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