IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v47y2016i2p255-274.html
   My bibliography  Save this article

The Stability Analysis of Predictor–Corrector Method in Solving American Option Pricing Model

Author

Listed:
  • R. Kalantari
  • S. Shahmorad
  • D. Ahmadian

Abstract

In this paper, a new technique is investigated to speed up the order of accuracy for American put option pricing under the Black–Scholes (BS) model. First, we introduce the mathematical modeling of American put option, which leads to a free boundary problem. Then the free boundary is removed by adding a small and continuous penalty term to the BS model that cause American put option problem to be solvable on a fixed domain. In continuation we construct the method of lines (MOL) in space and reach a non-linear problem and we show that the proposed MOL is more stable than the other kinds. To deal with the non-linear problem, an algorithm is used based on the predictor–corrector method which corresponds to two parameters, $$\theta $$ θ and $$\phi $$ ϕ . These parameters are chosen optimally using a rational approximation to determine the order of time convergence. Finally in numerical results a second order convergence is shown in both space and time variables. Copyright Springer Science+Business Media New York 2016

Suggested Citation

  • R. Kalantari & S. Shahmorad & D. Ahmadian, 2016. "The Stability Analysis of Predictor–Corrector Method in Solving American Option Pricing Model," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 255-274, February.
  • Handle: RePEc:kap:compec:v:47:y:2016:i:2:p:255-274
    DOI: 10.1007/s10614-015-9483-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-015-9483-x
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10614-015-9483-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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ahmadian, D. & Farkhondeh Rouz, O. & Ivaz, K. & Safdari-Vaighani, A., 2020. "Robust numerical algorithm to the European option with illiquid markets," Applied Mathematics and Computation, Elsevier, vol. 366(C).

    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:47:y:2016:i:2:p:255-274. 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.