IDEAS home Printed from https://ideas.repec.org/a/taf/tjorxx/v71y2020i5p687-699.html
   My bibliography  Save this article

Sparse and robust portfolio selection via semi-definite relaxation

Author

Listed:
  • Yongjae Lee
  • Min Jeong Kim
  • Jang Ho Kim
  • Ju Ri Jang
  • Woo Chang Kim

Abstract

In investment management, especially for automated investment services, it is critical for portfolios to have a manageable number of assets and robust performance. First, portfolios should not contain too many assets in order to reduce the management fees, transaction costs, and taxes. Second, portfolios should be robust as investment environments change rapidly. In this study, therefore, we propose two convex portfolio selection models that provide portfolios that are sparse and robust. We first perform semi-definite relaxation to develop a sparse mean-variance portfolio selection model, and further extend the model by using L2-norm regularization and worst-case optimization to formulate two sparse and robust portfolio selection models. Empirical analyses with historical stock returns demonstrate the effectiveness of the proposed models in forming sparse and robust portfolios.

Suggested Citation

  • Yongjae Lee & Min Jeong Kim & Jang Ho Kim & Ju Ri Jang & Woo Chang Kim, 2020. "Sparse and robust portfolio selection via semi-definite relaxation," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(5), pages 687-699, May.
    • Handle: RePEc:taf:tjorxx:v:71:y:2020:i:5:p:687-699
    DOI: 10.1080/01605682.2019.1581408
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01605682.2019.1581408
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/01605682.2019.1581408?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 search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Mingming & Song, Wenwen & Liu, Liyun & Zhou, Dequn, 2024. "Optimal investment portfolio strategy for carbon neutrality of power enterprises," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    2. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    3. Michele Costola & Bertrand Maillet & Zhining Yuan & Xiang Zhang, 2024. "Mean–variance efficient large portfolios: a simple machine learning heuristic technique based on the two-fund separation theorem," Annals of Operations Research, Springer, vol. 334(1), pages 133-155, March.
    4. Ni, Xuanming & Zheng, Tiantian & Zhao, Huimin & Zhu, Shushang, 2023. "High-dimensional portfolio optimization based on tree-structured factor model," Pacific-Basin Finance Journal, Elsevier, vol. 81(C).
    5. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2022. "Robust portfolio selection problems: a comprehensive review," Operational Research, Springer, vol. 22(4), pages 3203-3264, September.
    6. Li, Xuepeng & Xu, Fengmin & Jing, Kui, 2022. "Robust enhanced indexation with ESG: An empirical study in the Chinese Stock Market," Economic Modelling, Elsevier, vol. 107(C).
    7. Tu, Xueyong & Li, Bin, 2024. "Robust portfolio selection with smart return prediction," Economic Modelling, Elsevier, vol. 135(C).
    8. Pier Francesco Procacci & Tomaso Aste, 2022. "Portfolio optimization with sparse multivariate modeling," Journal of Asset Management, Palgrave Macmillan, vol. 23(6), pages 445-465, October.
    9. Farshad Noravesh, 2022. "Sparse Non-Convex Optimization For Higher Moment Portfolio Management," Papers 2201.01227, arXiv.org, revised Jan 2022.
    10. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.
    11. Lioui, Abraham & Tarelli, Andrea, 2022. "Chasing the ESG factor," Journal of Banking & Finance, Elsevier, vol. 139(C).

    More about this item

    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:taf:tjorxx:v:71:y:2020:i:5:p:687-699. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjor .

    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.