IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-031-64273-9_38.html

Portfolio Volatility Contributions of Risk Factors in the Presence of Risk Factors Multi-collinearity

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Andrea Mecchina

    (University of Trieste, Department of Mathematics, Informatics and Geosciences)

  • Enrico Regolin

    (Generali Asset Management SGR S.p.A.)

  • Nicola Torelli

    (University of Trieste, Department of Economics, Business, Mathematics and Statistics)

  • Luca Bortolussi

    (University of Trieste, Department of Mathematics, Informatics and Geosciences)

Abstract

Attributing the volatility of a portfolio to some exogenous risk factors which are not directly invested in by the portfolio may be a topic of interest to asset managers. Without any restriction on the nature of risk factors, we must take into account that their returns may exhibit strong correlations. Risk factor returns multi-collinearity causes severe problems in estimating their portfolio volatility contributions. In order to solve this issue, we propose a risk attributing pipeline that applies an orthogonalisation algorithm to risk factor returns. Most importantly, the risk factors interpretability is preserved, in the sense that the orthogonalised risk factors are the ones attaining the least Frobenius norm of the matrix of deviations from the original risk factors.

Suggested Citation

  • Andrea Mecchina & Enrico Regolin & Nicola Torelli & Luca Bortolussi, 2024. "Portfolio Volatility Contributions of Risk Factors in the Presence of Risk Factors Multi-collinearity," Springer Books, in: Marco Corazza & Frédéric Gannon & Florence Legros & Claudio Pizzi & Vincent Touzé (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 229-234, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-64273-9_38
    DOI: 10.1007/978-3-031-64273-9_38
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:sprchp:978-3-031-64273-9_38. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.