IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i6p964-d1612548.html
   My bibliography  Save this article

Capital Allocation Rules and Generalized Collapse to the Mean: Theory and Practice

Author

Listed:
  • Francesca Centrone

    (Department of Economics and Business Studies, University of Eastern Piedmont, 28100 Novara, Italy)

  • Emanuela Rosazza Gianin

    (Department of Statistics and Quantitative Methods, University of Milano-Bicocca, 20126 Milano, Italy)

Abstract

In this paper, we focus on capital allocation methods based on marginal contributions. In particular, concerning the relation between linear capital allocation rules and the well-known Gradient (or Euler) allocation, we investigate an extension to the convex and non-differentiable case of the result above and its link with the “generalized collapse to the mean” problem. This preliminary result goes in the direction of applying the popular marginal contribution method, which fosters the diversification of risk, to the case of more general risk measures. In this context, we will also discuss and point out some numerical issues linked to marginal methods and some future research directions.

Suggested Citation

  • Francesca Centrone & Emanuela Rosazza Gianin, 2025. "Capital Allocation Rules and Generalized Collapse to the Mean: Theory and Practice," Mathematics, MDPI, vol. 13(6), pages 1-14, March.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:6:p:964-:d:1612548
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/6/964/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/13/6/964/
    Download Restriction: no
    ---><---

    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:gam:jmathe:v:13:y:2025:i:6:p:964-:d:1612548. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.