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Trading System Mixed-Integer Optimization by PSO

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Marco Corazza

    (Ca’ Foscari University of Venice)

  • Francesca Parpinel

    (Ca’ Foscari University of Venice)

  • Claudio Pizzi

    (Ca’ Foscari University of Venice)

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.

Suggested Citation

  • Marco Corazza & Francesca Parpinel & Claudio Pizzi, 2021. "Trading System Mixed-Integer Optimization by PSO," Springer Books, in: Marco Corazza & Manfred Gilli & Cira Perna & Claudio Pizzi & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 161-167, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-78965-7_24
    DOI: 10.1007/978-3-030-78965-7_24
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