IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v66y2025i2d10.1007_s10614-024-10734-x.html
   My bibliography  Save this article

American Option Valuation Under the Framework of CGMY Model with Regime-Switching Process

Author

Listed:
  • Congyin Fan

    (Guizhou University of Commerce)

  • Xian-Ming Gu

    (Southwestern University of Finance and Economics)

  • Shuhong Dong

    (Guizhou University of Commerce)

  • Hua Yuan

    (Guizhou University of Commerce)

Abstract

In this paper, the values and optimal exercise prices of American option under the CGMY model with regime-switching process are considered. For this case, the pricing mathematical model is a free boundary problem which includes d coupled fractional partial differential equations (PDEs) in one dimension with free boundary conditions, d denoting the number of regimes of financial market. The above problem is changed as a fixed one by adding a nonlinear penalty term to each fractional PDE. After the finite difference method is set to solve the transformed model, unlike the conventional method, the discretized coupling system is reformulated by expanding dimensions such that numerical results in all states can be calculated simultaneously. Finally, significant effects of the parameters in our model on the option exercise price are verified through our selected numerical results. Meanwhile, the curves of Delta and Gamma are reported to show feasibility of our model and the proposed numerical method.

Suggested Citation

  • Congyin Fan & Xian-Ming Gu & Shuhong Dong & Hua Yuan, 2025. "American Option Valuation Under the Framework of CGMY Model with Regime-Switching Process," Computational Economics, Springer;Society for Computational Economics, vol. 66(2), pages 1455-1479, August.
  • Handle: RePEc:kap:compec:v:66:y:2025:i:2:d:10.1007_s10614-024-10734-x
    DOI: 10.1007/s10614-024-10734-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-024-10734-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/s10614-024-10734-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

    for a different version of it.

    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:kap:compec:v:66:y:2025:i:2:d:10.1007_s10614-024-10734-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.