IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v21y2021i9p1475-1490.html
   My bibliography  Save this article

Optimal portfolio allocation and asset centrality revisited

Author

Listed:
  • Jose Olmo

Abstract

This paper revisits the relationship between eigenvector asset centrality and optimal asset allocation in a minimum variance portfolio. We show that the standard definition of eigenvector centrality is misleading when the adjacency matrix in a network can take negative values. This is, for example, the case when the network topology is induced by the correlation matrix between assets in a portfolio. To correct for this, we introduce the concept of positive and negative eigenvector centrality. Our results show that the loss function associated to the minimum variance portfolio is positively/negatively related to the positive and negative eigenvector centrality under short-selling constraints but cannot be generalized beyond that. Furthermore, in contrast to what is claimed in the related literature, this relationship does not imply any monotonic relationship between the centrality of an asset and its optimal portfolio allocation. These theoretical insights are illustrated empirically in a portfolio allocation exercise with assets from U.S. and U.K. financial markets.

Suggested Citation

  • Jose Olmo, 2021. "Optimal portfolio allocation and asset centrality revisited," Quantitative Finance, Taylor & Francis Journals, vol. 21(9), pages 1475-1490, September.
    • Handle: RePEc:taf:quantf:v:21:y:2021:i:9:p:1475-1490
    DOI: 10.1080/14697688.2021.1937298
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14697688.2021.1937298
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/14697688.2021.1937298?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. Christis Katsouris, 2023. "Statistical Estimation for Covariance Structures with Tail Estimates using Nodewise Quantile Predictive Regression Models," Papers 2305.11282, arXiv.org, revised Jul 2023.
    2. Agathe Sadeghi & Zachary Feinstein, 2024. "Statistical Validation of Contagion Centrality in Financial Networks," Papers 2404.14337, arXiv.org.
    3. Jilber Urbina & Miguel Santolino & Montserrat Guillen, 2021. "Covariance Principle for Capital Allocation: A Time-Varying Approach," Mathematics, MDPI, vol. 9(16), pages 1-13, August.
    4. Christis Katsouris, 2021. "Optimal Portfolio Choice and Stock Centrality for Tail Risk Events," Papers 2112.12031, arXiv.org.
    5. Wang, Yifu & Lu, Wanbo & Lin, Min-Bin & Ren, Rui & Härdle, Wolfgang Karl, 2024. "Cross-exchange crypto risk: A high-frequency dynamic network perspective," International Review of Financial Analysis, Elsevier, vol. 94(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:quantf:v:21:y:2021:i:9:p:1475-1490. 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/RQUF20 .

    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.