Multilevel Path Simulation to Jump-Diffusion Process with Superlinear Drift
Numerical Analysis
2018-10-30 v1 Probability
Abstract
In this work, we will show strong convergence of the Multilevel Monte-Carlo (MLMC) algorithm with split-step backward Euler (SSBE) and backward (drift-implicit) Euler (BE) schemes for nonlinear jump-diffusion stochastic differential equations (SDEs) when the coefficient drift is globally one-sided Lipschitz and the test function is only locally Lipschitz. We also confirm these theoretical results by numerical experiments for the jump-diffusion processes.
Cite
@article{arxiv.1810.11790,
title = {Multilevel Path Simulation to Jump-Diffusion Process with Superlinear Drift},
author = {Azadeh Ghasemifard and Mahdieh Tahmasebi},
journal= {arXiv preprint arXiv:1810.11790},
year = {2018}
}