A transformed jump-adapted backward Euler method for jump-extended CIR and CEV models

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• 作者：Xu Yang ; Xiaojie Wang
• 关键词：Jump ; extended CIR and CEV models ; Jump ; adapted method ; Strong convergence rates ; Non ; Lipschitz coefficients
• 刊名：Numerical Algorithms
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：74
• 期：1
• 页码：39-57
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Numeric Computing; Algorithms; Algebra; Theory of Computation; Numerical Analysis;
• 出版者：Springer US
• ISSN：1572-9265
• 卷排序：74

文摘

A novel time-stepping scheme, called transformed jump-adapted backward Euler method, is developed in this paper to simulate a class of jump-extended CIR and CEV models. The proposed scheme is able to preserve the positivity of the underlying problems. Furthermore, its strong convergence rate of order one is recovered for the considered models with non-Lipschitz diffusion coefficients. Numerical examples are finally reported to confirm our theoretical findings.