Antithetic multilevel Monte-Carlo estimation without Lévy area simulation: limit theorems
We introduce our method $\sigma$-antithetic multilevel Monte Carlo for multi-dimensional stochastic differential equations driven by Brownian motions with drifts. Here $\sigma$ is a specific permutation of order $m$, with $m\in\mathbb{N}\backslash\{0,1\}$. Following the spirit of Giles and Szpruch in [b], we consider the Milstein scheme without Lévy area. Our aim is to prove the stable convergence for the $\sigma$-antithetic multilevel error between two consecutive levels. To do so, we chose the triangular array approach using the limit theorem of Jacod [c].




