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Mathematical and Statistical Methods for Actuarial Sciences and Finance pp 161–167Cite as

Trading System Mixed-Integer Optimization by PSO

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Abstract

This work concerns the optimization of a Trading Systems (TS) based on a small set of Technical Analysis (TA) indicators. Usually, in TA the values of the parameters (window lengths and thresholds) of these indicators are fixed by professional experience. Here, we propose to design the parametric configuration according to historical data, optimizing some performance measures subjected to proper constraints using a Particle Swarm Optimization-based metaheuristic. In particular, such an optimization procedure is applied to obtain both the optimal parameter values and the optimal weighting of the trading signals from the considered TA indicators, in order to provide an optimal trading decision. The use of a metaheuristic is necessary since the involved optimization problem is strongly nonlinear, nondifferentiable and mixed-integer. The proposed TS is optimized using the daily adjusted closing returns of seven Italian stocks coming from different industries and of two stock market indices.

Keywords

  • Trading Systems
  • Technical Analysis
  • Mixed-Integer Optimization
  • Particle Swarm Optimization

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Fig. 1

Notes

  1. 1.

    Notice that \(e(\cdot )\) is a function of \(S(\cdot )\), that \(S(\cdot )\) is a function of \(signal_i(\cdot )\), and that \(signal_i(\cdot )\) is a function of the i-th indicator.

  2. 2.

    Notice that we performed our procedure 100 times, so we could apply the central limit theorem according to which the sample mean is asymptotically normally distributed.

References

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  5. Ratnaweera, A., Halgamuge, S.K.: Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients. IEEE Trans. Evol. Comput. 8, 240–255 (2004)

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Authors and Affiliations

  1. Department of Economics, Ca’ Foscari University of Venice, Sestiere Cannaregio 873, 30121, Venezia, Italy

    Marco Corazza, Francesca Parpinel & Claudio Pizzi

Authors
  1. Marco Corazza
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  2. Francesca Parpinel
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  3. Claudio Pizzi
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Corresponding author

Correspondence to Francesca Parpinel .

Editor information

Editors and Affiliations

  1. Department of Economics, Ca' Foscari University of Venice, Venezia, Italy

    Prof. Dr. Marco Corazza

  2. Geneva School of Economics and Management (GSEM), University of Geneva, Genève, Switzerland

    Prof. Manfred Gilli

  3. Department of Economics and Statistics, University of Salerno, Fisciano, Italy

    Prof. Dr. Cira Perna

  4. Department of Economics, Ca' Foscari University of Venice, Venezia, Italy

    Prof. Dr. Claudio Pizzi

  5. Department of Economics and Statistics, University of Salerno, Fisciano, Italy

    Prof. Dr. Marilena Sibillo

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Corazza, M., Parpinel, F., Pizzi, C. (2021). Trading System Mixed-Integer Optimization by PSO. In: Corazza, M., Gilli, M., Perna, C., Pizzi, C., Sibillo, M. (eds) Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer, Cham. https://doi.org/10.1007/978-3-030-78965-7_24

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