Approximation of continuous time stochastic processes by a local linearization method

Abstract

This paper investigates the rate of convergence of an alternative approximation method for stochastic differential equations. The rates of convergence of the one-step and multi-step approximation errors are proved to be O ( ( Δ t ) 2 ) O((\Delta t)^2) and O ( Δ t ) O(\Delta t) in the L p L_p sense respectively, where Δ t \Delta t is discrete time interval. The rate of convergence of the one-step approximation error is improved as compared with methods assuming the value of Brownian motion to be known only at discrete time. Through numerical experiments, the rate of convergence of the multi-step approximation error is seen to be much faster than in the conventional method.