IDEAS home Printed from https://ideas.repec.org/a/prg/jnlpol/vpreprintid1560.html

Portfolio Optimization Based on Fuzzy Investor Risk Classification Aligned with The Sri Framework

Author

Listed:
  • Juraj Pekár
  • Richard Martinus

Abstract

Choosing the right portfolio is challenging, especially for non-professional investors. In practice, investors are often classified into three risk profiles (conservative, balanced, dynamic), while investment products in the European Union are classified into seven categories using the Summary Risk Indicator (SRI). This mismatch may lead to investors with the same profile being recommended products with different risk levels. This paper proposes a methodology that aligns investor classification with the seven-level SRI scale. A fuzzy logic based investment questionnaire classifies investors into seven risk groups. For each group, a portfolio is constructed using Conditional Value at Risk optimization under undertakings for collective investment in transferable securities (UCITS) constraints. Empirical results based on Eurostoxx 50 data from 2020-2025 period show that the optimized portfolios achieved higher returns and lower downside risk than the benchmark. For example, the SRI 5 portfolio had an annual return of 16.12% compared to 11.3% for the benchmark.

Suggested Citation

  • Juraj Pekár & Richard Martinus, . "Portfolio Optimization Based on Fuzzy Investor Risk Classification Aligned with The Sri Framework," Politická ekonomie, Prague University of Economics and Business, vol. 0.
    • Handle: RePEc:prg:jnlpol:v:preprint:id:1560
    DOI: 10.18267/j.polek.1560
    as

    Download full text from publisher

    File URL: http://polek.vse.cz/doi/10.18267/j.polek.1560.html
    Download Restriction: free of charge
    File URL: https://libkey.io/10.18267/j.polek.1560?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    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:prg:jnlpol:v:preprint:id:1560. 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: Stanislav Vojir (email available below). General contact details of provider: https://edirc.repec.org/data/uevsecz.html .

    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.