Unconditionally Stable Numerical Pricing of American Bond Options via the Hull-White Model
Indu Rani () and
Chandan Kumar Verma ()
Additional contact information
Indu Rani: Maulana Azad National Institute of Technology, Mathematics, Bioinformatics and Computer Applications
Chandan Kumar Verma: Maulana Azad National Institute of Technology, Mathematics, Bioinformatics and Computer Applications
SN Operations Research Forum, 2025, vol. 6, issue 4, 1-17
Abstract:
Abstract The present paper puts forward a novel and unconditionally stable numerical approach for valuing American options (AO) on zero-coupon bonds (ZCBs), considering the framework of the Hull-White (HW) model. By integrating a front-fixing (FF) transformation with the implicit finite difference (IFD) technique, the method facilitates the simultaneous determination of optimal exercise boundaries and option prices, effectively reformulating the problem of the original free boundary into a bounded one. Additionally, the proposed approach has demonstrated unconditional stability across all grid ratios, ensuring robustness for any step sizes. To enhance the reliability of the obtained results, numerical experiments are conducted to illustrate the efficiency and feasibility of the suggested approach. This study includes comparisons with existing approaches for solving the AO on zero-coupon bonds to affirm the numerical findings and show the effectiveness of the employed approach.
Keywords: American options; HW model; Front-fixing transformation; Finite difference method (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s43069-025-00586-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:snopef:v:6:y:2025:i:4:d:10.1007_s43069-025-00586-y
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/43069
DOI: 10.1007/s43069-025-00586-y
Access Statistics for this article
SN Operations Research Forum is currently edited by Marco Lübbecke
More articles in SN Operations Research Forum from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().