From rough path estimates to multilevel Monte Carlo

Discrete approximations to solutions of stochastic differential equations are well-known to converge with strong rate 1=2. Such rates have played a key-role in Giles multilevel Monte Carlo method [Giles, Oper. Res. 2008] which gives a substantial reduction of the computational effort necessary for the evaluation of diffusion functionals. In the present article similar results are established for large classes of rough differential equations driven by Gaussian processes (including fractional Brownian motion with H > 1=4 as special case).

URI

https://doi.org/10.34657/2409
https://oa.tib.eu/renate/handle/123456789/1677

Citation

Bayer, C., Friz, P. K., Riedel, S., & Schoenmakers, J. G. M. (2013). From rough path estimates to multilevel Monte Carlo. Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik.

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