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Convergence Rate of Markov Chains and Hybrid Numerical Schemes to Jump-Diffusion with Application to the Bates Model
SIAM Journal on Numerical Analysis ( IF 2.8 ) Pub Date : 2021-02-18 , DOI: 10.1137/18m1209416
Maya Briani , Lucia Caramellino , Giulia Terenzi

SIAM Journal on Numerical Analysis, Volume 59, Issue 1, Page 477-502, January 2021.
We study the rate of weak convergence of Markov chains to diffusion processes under quite general assumptions. We give an example in the financial framework, applying the convergence analysis to a multiple jumps tree approximation of the CIR process. Then, we combine the Markov chain approach with other numerical techniques in order to handle the different components in jump-diffusion coupled models. We study the analytical speed of convergence of this hybrid approach and provide an example in finance, applying our results to a tree-finite difference approximation in the Heston and Bates models.


中文翻译:

马尔可夫链的收敛速度和跳扩散的混合数值格式在贝茨模型中的应用

SIAM数值分析杂志,第59卷,第1期,第477-502页,2021年1月。
我们在相当笼统的假设下研究了马尔可夫链对扩散过程的弱收敛速度。我们以财务框架为例,将收敛性分析应用于CIR流程的多次跳跃树近似。然后,我们将马尔可夫链方法与其他数值技术相结合,以处理跳跃扩散耦合模型中的不同组成部分。我们研究了这种混合方法收敛的分析速度,并提供了一个财务示例,将我们的结果应用于Heston和Bates模型中的树有限差分近似。
更新日期:2021-02-19
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