IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v72y2024i4p1630-1653.html
   My bibliography  Save this article

Unified Moment-Based Modeling of Integrated Stochastic Processes

Author

Listed:
  • Ioannis Kyriakou

    (Faculty of Actuarial Science & Insurance, Bayes Business School (formerly Cass), City, University of London, London EC1Y 8TZ, United Kingdom)

  • Riccardo Brignone

    (Department of Quantitative Finance, Faculty of Economics and Behavioural Science, University of Freiburg, 79098 Freiburg im Breisgau, Germany)

  • Gianluca Fusai

    (Dipartimento di Studi per l’Economia e l’Impresa, Università del Piemonte Orientale, 28100 Novara, Italy; Faculty of Finance, Bayes Business School (formerly Cass), City, University of London, London EC1Y 8TZ, United Kingdom)

Abstract

In this paper, we present a new method for simulating integrals of stochastic processes. We focus on the nontrivial case of time integrals, conditional on the state variable levels at the endpoints of a time interval through a moment-based probability distribution construction. We present different classes of models with important uses in finance, medicine, epidemiology, climatology, bioeconomics, and physics. The method is generally applicable in well-posed moment problem settings. We study its convergence, point out its advantages through a series of numerical experiments, and compare its performance against existing schemes.

Suggested Citation

  • Ioannis Kyriakou & Riccardo Brignone & Gianluca Fusai, 2024. "Unified Moment-Based Modeling of Integrated Stochastic Processes," Operations Research, INFORMS, vol. 72(4), pages 1630-1653, July.
    • Handle: RePEc:inm:oropre:v:72:y:2024:i:4:p:1630-1653
    DOI: 10.1287/opre.2022.2422
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.2022.2422
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.2022.2422?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
    ---><---

    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:inm:oropre:v:72:y:2024:i:4:p:1630-1653. 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 Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.