Convergence rate of Markov chains and hybrid numerical schemes to jump-diffusions with application to the Bates model
| Autor: | Maya Briani, Lucia Caramellino, Giulia Terenzi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
tree methods
Jump diffusion Convergence (routing) FOS: Mathematics Applied mathematics Diffusion (business) stochastic volatility jump-diffusion processes PIDEs weak convergence finite-difference European options Mathematics Numerical Analysis Stochastic volatility Markov chain Weak convergence finite difference Applied Mathematics Probability (math.PR) Finite difference jump-diffusion processes: PIDES Computational Mathematics Rate of convergence Settore MAT/06 60H35 65C20 91G60 Mathematics - Probability |
| Zdroj: | SIAM journal on numerical analysis (2021). info:cnr-pdr/source/autori:M. Briani, L. Caramellino, G. Terenzi/titolo:Convergence rate of Markov chains and hybrid numerical schemes to jump-diffusions with application to the Bates model/doi:/rivista:SIAM journal on numerical analysis (Print)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume |
| Popis: | 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. © 2021 Society for Industrial and Applied Mathematics. |
| Databáze: | OpenAIRE |
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