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Immunology-Based Sustainable Portfolio Management

Author

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  • Sarunas Raudys

    (Institute of Informatics, Vilnius University, 01513 Vilnius, Lithuania)

  • Aistis Raudys

    (Institute of Informatics, Vilnius University, 01513 Vilnius, Lithuania)

  • Zidrina Pabarskaite

    (Institute of Informatics, Vilnius University, 01513 Vilnius, Lithuania)

  • Ausra Liubaviciute

    (Faculty of Medicine, Vilnius University, 01513 Vilnius, Lithuania)

Abstract

Immunological principles can be used to build a sustainable investment portfolio. The theory of immunology states that information about recognized pathogens is stored in the memory of the immune system. Information about previous illnesses can be helpful when the pathogen re-enters the body. Real-time analysis of 11 automated financial trading datasets confirmed this phenomenon in financial time series. Therefore, in order to increase the sustainability of the portfolio, we propose to train the portfolio with the most similar segments of historical data. The segment size and offset may vary depending on the data set and time.

Suggested Citation

  • Sarunas Raudys & Aistis Raudys & Zidrina Pabarskaite & Ausra Liubaviciute, 2022. "Immunology-Based Sustainable Portfolio Management," Sustainability, MDPI, vol. 14(5), pages 1-11, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2531-:d:755831
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    References listed on IDEAS

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    1. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    2. Sarunas Raudys & Aistis Raudys & Zidrina Pabarskaite, 2018. "Dynamically Controlled Length of Training Data for Sustainable Portfolio Selection," Sustainability, MDPI, vol. 10(6), pages 1-14, June.
    3. Todor Stoilov & Krasimira Stoilova & Miroslav Vladimirov, 2021. "Explicit Value at Risk Goal Function in Bi-Level Portfolio Problem for Financial Sustainability," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
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