IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v18y2025i9p521-d1751325.html
   My bibliography  Save this article

Optimizing Investments in the Portfolio Intelligence (PI) Model

Author

Listed:
  • Nikolaos Loukeris

    (Department of Business Administration, University of West Attica, Petrou Ralli & Thivon Avenue, 12241 Athens, Greece)

  • Lysimachos Maltoudoglou

    (Department of Production Engineers and Management, Democritus University of Thrace, 67100 Xanthi, Greece)

  • Yannis Boutalis

    (Department of Electrical and Computer Engineers, Democritus University of Thrace, 67100 Xanthi, Greece)

  • Iordanis Eleftheriadis

    (Department of Business Administration, University of Macedonia, Egnatias 156, 54636 Thessaloniki, Greece)

Abstract

A new methodology is introduced that incorporates advanced higher moment evaluation in a new approach to the Portfolio Selection problem, supported by effective Computational Intelligence models. The Portfolio Intelligence (PI) model extracts hidden patterns from numerous accounting data and financial statements, filtering misleading effects such as noise or fraud offering an optimal portfolio selection method. The chaotic reflections of speculative behaviors of investors are analyzed in fractal distributions, as higher moments with fundamentals clear the turbulence of noise while the PI model, under its robust AI classifiers, provides optimal investment support.

Suggested Citation

  • Nikolaos Loukeris & Lysimachos Maltoudoglou & Yannis Boutalis & Iordanis Eleftheriadis, 2025. "Optimizing Investments in the Portfolio Intelligence (PI) Model," JRFM, MDPI, vol. 18(9), pages 1-20, September.
    • Handle: RePEc:gam:jjrfmx:v:18:y:2025:i:9:p:521-:d:1751325
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/18/9/521/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/18/9/521/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jjrfmx:v:18:y:2025:i:9:p:521-:d:1751325. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.