On the simulation of iterated Itô integrals

TOBIAS RYDÉN & MAGNUS WIKTORSSON

Centre for Mathematical Sciences Lund University Box 118 221 00 Lund, Sweden

Abstract

We consider algorithms for simulation of iterated Itô integrals with
application to simulation of stochastic differential equations. The
fact that the iterated Itô integral
I_{ij}(t_n,t_n+h)=\int_{t_n}^{t_n+h} \int_{t_n}^{s} dW_{i}(u)dW_{j}(s)
conditioned on W_i(t_n+h)-W_i(t_n) and W_j(t_n+h)-W_j(t_n), has an
infinitely divisible distribution is utilised for the simultaneous
simulation of $I_{ij}(t_n,t_n+h)$,W_{i}(t_n+h)-W_{i}(t_n) and
W_j(t_n+h)-W_j(t_n). Different simulation methods for the  iterated
Itô integrals are investigated. We show mean square convergence rates
for approximations of shot-noise type and asymptotic normality of the
remainder of the approximations. This together with the fact that the
conditional distribution of I_{ij}(t_n,t_n+h), apart from an additive
constant, is a Gaussian variance mixture is used  to achieve an
improved convergence rate. This is done by a coupling method for the
remainder of the approximation.