IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v330y2023i1d10.1007_s10479-022-04574-x.html
   My bibliography  Save this article

Practice-relevant model validation: distributional parameter risk analysis in financial model risk management

Author

Listed:
  • Mark Cummins

    (Dublin City University)

  • Fabian Gogolin

    (Leeds University Business School, University of Leeds)

  • Fearghal Kearney

    (Queen’s University Belfast)

  • Greg Kiely

    (Gazprom Marketing and Trading Limited)

  • Bernard Murphy

    (University of Limerick)

Abstract

An objective of model validation within organisations is to provide guidance on model selection decisions that balance the operational effectiveness and structural complexity of competing models. We consider a practice-relevant model validation scenario where a financial quantitative analysis team seeks to decide between incumbent and alternative models on the basis of parameter risk. We devise a model risk management methodology that gives a meaningful distributional assessment of parameter risk in a setting where market calibration and historical estimation procedures must be jointly applied. Such a scenario is typically driven by data constraints that preclude market calibration only. We demonstrate our proposed methodology in a natural gas storage modelling context, where model usage is necessary to support profit and loss reporting, and to inform trading and hedging strategy. We leverage our distributional parameter risk approach to devise an accessible technique to support model selection decisions.

Suggested Citation

  • Mark Cummins & Fabian Gogolin & Fearghal Kearney & Greg Kiely & Bernard Murphy, 2023. "Practice-relevant model validation: distributional parameter risk analysis in financial model risk management," Annals of Operations Research, Springer, vol. 330(1), pages 431-455, November.
    • Handle: RePEc:spr:annopr:v:330:y:2023:i:1:d:10.1007_s10479-022-04574-x
    DOI: 10.1007/s10479-022-04574-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-022-04574-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-022-04574-x?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.

    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:annopr:v:330:y:2023:i:1:d:10.1007_s10479-022-04574-x. 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.