IDEAS home Printed from https://ideas.repec.org/a/ahs/journl/v10y2025i1p27-43.html
   My bibliography  Save this article

Portfolio Construction with Postmodern Portfolio Theory Framework

Author

Listed:
  • Erdi BAYRAM
  • Rabia AKTAŞ

Abstract

This study includes alternative portfolio construction approaches consistent with the Modern Portfolio Theory (MPT) and Postmodern Portfolio Theory (PMPT). We propose a weighting strategy based on Sharpe and Sortino optimization, and unlike MPT, we create PMPT portfolios using downside metrics, such as downside risk, downside beta, and downside capital asset pricing model (D-CAPM). Portfolios consist of stocks in the Borsa Istanbul Participation 30 Index (XK030), with the stocks in the portfolio having been revised according to screening periods. In addition, we created an equally weighted portfolio and used XK030 as a benchmark for comparative analysis. The sample period covers 527 trading days between May 6, 2022, and June 28, 2024. The results show that the Sharpe portfolio consistently follows the benchmark index throughout the observation period. Sortino outperforms both the benchmark and conventional market index in some specific periods when the market has an upward trend, especially. This study provides evidence that the MPT and PMPT approaches and measures can be used in asset allocation and portfolio management. Investors can manage their assets and balance portfolio weights by implementing the models in different market conditions.

Suggested Citation

  • Erdi BAYRAM & Rabia AKTAŞ, 2025. "Portfolio Construction with Postmodern Portfolio Theory Framework," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 10(1), pages 27-43.
    • Handle: RePEc:ahs:journl:v:10:y:2025:i:1:p:27-43
    DOI: https://doi.org/10.30784/epfad.1576857
    as

    Download full text from publisher

    File URL: https://dergipark.org.tr/tr/download/article-file/4329315
    Download Restriction: no
    File URL: https://libkey.io/https://doi.org/10.30784/epfad.1576857?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
    ---><---

    References listed on IDEAS

    as
    1. Andrea Rigamonti, 2020. "Mean-Variance Optimization Is a Good Choice, But for Other Reasons than You Might Think," Risks, MDPI, vol. 8(1), pages 1-16, March.
    2. Syed Aziz Rasool & Adiqa Kausar Kiani & Noor Jehan, 2018. "The Myth of Downside Risk Based Capital Asset Pricing Model: Empirical Evidence from South Asian Countries," Global Social Sciences Review, Humanity Only, vol. 3(3), pages 265-280, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Khaki, Audil & Prasad, Mason & Al-Mohamad, Somar & Bakry, Walid & Vo, Xuan Vinh, 2023. "Re-evaluating portfolio diversification and design using cryptocurrencies: Are decentralized cryptocurrencies enough?," Research in International Business and Finance, Elsevier, vol. 64(C).
    2. Dasuni Nirmani Pandithasekara & Erabaddage Ayoma Gayathri Sumanasiri & Áron Perényi, 2023. "Exploring the Impact of Sustainability Control Systems on Employees’ Green Creativity: The Mediating Role of Psychological Empowerment and Sustainability Learning Capabilities," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    3. Andrea Rigamonti & Katarína Lučivjanská, 2024. "Mean-semivariance portfolio optimization using minimum average partial," Annals of Operations Research, Springer, vol. 334(1), pages 185-203, March.
    4. Anja Vinzelberg & Benjamin R. Auer, 2022. "Unprofitability of food market investments," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 2887-2910, October.
    5. Matteo Foglia & Maria Cristina Recchioni & Gloria Polinesi, 2021. "Smart Beta Allocation and Macroeconomic Variables: The Impact of COVID-19," Risks, MDPI, vol. 9(2), pages 1-25, February.

    More about this item

    Keywords

    Postmodern Portfolio Theory; Downside Risk; Portfolio Optimization; Participation Index;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:ahs:journl:v:10:y:2025:i:1:p:27-43. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Ersan Ersoy (email available below). General contact details of provider: https://epfjournal.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.