Pricing a resettable convertible bond based on decomposition method and PDE models

IF 1.4 Q2 MATHEMATICS, APPLIED
Zhongdi Cen, Jian Huang, Anbo Le, Aimin Xu
{"title":"Pricing a resettable convertible bond based on decomposition method and PDE models","authors":"Zhongdi Cen,&nbsp;Jian Huang,&nbsp;Anbo Le,&nbsp;Aimin Xu","doi":"10.1016/j.rinam.2023.100423","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, a partial differential equation approach based on the underlying stock price path decomposition is developed to price an American-style resettable convertible bond. The American-style resettable convertible bond is viewed as a mixture of three simple securities, which can be used to replicate the feature of payoffs of the resettable convertible bond completely. The partial differential equations under the Black–Scholes framework are established to price these simple securities. An implicit Euler method is used to discretize the first-order time derivative while a central finite difference method on a piecewise uniform mesh is used to discretize the spatial derivatives. The error estimates are developed by using the maximum principle in two mesh sets both for the time semi-discretization scheme and the spatial discretization scheme, respectively. It is proved that the scheme is first-order convergent for the time variable and second-order convergent for the spatial variable. Numerical experiments support these theoretical results.</p></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"21 ","pages":"Article 100423"},"PeriodicalIF":1.4000,"publicationDate":"2023-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590037423000699/pdfft?md5=1af11324900574ccc0c55f966ffd11ba&pid=1-s2.0-S2590037423000699-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Results in Applied Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590037423000699","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0

Abstract

In this paper, a partial differential equation approach based on the underlying stock price path decomposition is developed to price an American-style resettable convertible bond. The American-style resettable convertible bond is viewed as a mixture of three simple securities, which can be used to replicate the feature of payoffs of the resettable convertible bond completely. The partial differential equations under the Black–Scholes framework are established to price these simple securities. An implicit Euler method is used to discretize the first-order time derivative while a central finite difference method on a piecewise uniform mesh is used to discretize the spatial derivatives. The error estimates are developed by using the maximum principle in two mesh sets both for the time semi-discretization scheme and the spatial discretization scheme, respectively. It is proved that the scheme is first-order convergent for the time variable and second-order convergent for the spatial variable. Numerical experiments support these theoretical results.

基于分解法和 PDE 模型的可重置可转债定价方法
本文采用基于标的股价路径分解的偏微分方程方法对美式可重置可转换债券进行定价。美国式的可重置可转换债券被看作是三种简单证券的混合体,可以完全复制可重置可转换债券的偿付特征。建立了Black-Scholes框架下的偏微分方程对这些简单证券进行定价。采用隐式欧拉法对一阶时间导数进行离散,采用分段均匀网格上的中心有限差分法对空间导数进行离散。分别对时间半离散化方案和空间离散化方案在两个网格集上采用极大值原理进行误差估计。证明了该格式对时间变量是一阶收敛的,对空间变量是二阶收敛的。数值实验支持这些理论结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Results in Applied Mathematics
Results in Applied Mathematics Mathematics-Applied Mathematics
CiteScore
3.20
自引率
10.00%
发文量
50
审稿时长
23 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信