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A meta-grammatical evolutionary process for portfolio selection and trading

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Abstract

This study presents the implementation of an automated trading system that uses three critical analyses to determine time-decisions and portfolios for investment. The approach is based on a meta-grammatical evolution methodology that combines technical, fundamental and macroeconomic analysis on a hybrid top-down paradigm. First, the method provides a low-risk portfolio by analyzing countries and industries. Next, aiming to focus on the most robust companies, the system filters the portfolio by analyzing their economic variables. Finally, the system analyzes prices and volumes to optimize investment decisions during a given period. System validation involves a series of experiments in the European financial markets, which are reflected with a data set of over nine hundred companies. The final solutions have been compared with static strategies and other evolutionary implementations and the results show the effectiveness of the proposal.

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Notes

  1. An algorithm that exists to manipulate some other algorithm.

  2. NET_INC: Total profits.

    MARK_CAP: Total market value of all outstanding shares of a company.

    EBIT: Earnings before interest and taxes.

    EBITDA: Earnings before interest, taxes, depreciation and amortization.

    COM_EQY: Total value of shares issued.

    LT_DEBT: Long-term debt (greater than 1 year).

    TOT_AS: The sum of current and long-term assets.

    SALES: Total volume of sales.

  3. B&H consists of buying at the beginning of the period and selling at the end, and it is widely used as comparison metric.

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Acknowledgements

This work was partially supported by the Spanish Government Minister of Science and Innovation under Grant TIN2014-54806-R and the People program (Marie Curie Actions) of the European Union Seventh Framework Programme (FP7/2007–2013) with the Agreement No. 600388 of the REA and the Agencia per a la Competitivitat de L’Empresa (ACCIÓ). J. I. Hidalgo also acknowledges the support of the Spanish Ministry of Education mobility Grant PRX16/00216.

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Authors and Affiliations

  1. Adaptive and Bioinspired Systems Research Group, Universidad Complutense de Madrid, Madrid, Spain

    J. Ignacio Hidalgo & J. Manuel Velasco

  2. Institut d’Informática i Aplicacions, Universitat de Girona, Girona, Spain

    Iván Contreras

  3. IE Business School, Madrid, Spain

    Laura Nuñez-Letamendía

Authors
  1. Iván Contreras
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  2. J. Ignacio Hidalgo
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  3. Laura Nuñez-Letamendía
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  4. J. Manuel Velasco
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Correspondence to J. Ignacio Hidalgo.

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Contreras, I., Hidalgo, J.I., Nuñez-Letamendía, L. et al. A meta-grammatical evolutionary process for portfolio selection and trading. Genet Program Evolvable Mach 18, 411–431 (2017). https://doi.org/10.1007/s10710-017-9304-1

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