Abstract

Abstract This paper aims to present a new pathwise approximation method, which gives approximate solutions of order $\begin{array}{} \displaystyle \frac{3}{2} \end{array}$ for stochastic differential equations (SDEs) driven by multidimensional Brownian motions. The new method, which assumes the diffusion matrix non-degeneracy, employs the Runge-Kutta method and uses the Itô-Taylor expansion, but the generating of the approximation of the expansion is carried out as a whole rather than individual terms. The new idea we applied in this paper is to replace the iterated stochastic integrals Iα by random variables, so implementing this scheme does not require the computation of the iterated stochastic integrals Iα. Then, using a coupling which can be found by a technique from optimal transport theory would give a good approximation in a mean square. The results of implementing this new scheme by MATLAB confirms the validity of the method.

Highlights

  • The purpose of this paper is to develop a new pathwise approximation to numerical solutions of stochastic di erential equations (SDEs) driven by multidimensional Brownian motion

  • This paper aims to present a new pathwise approximation method, which gives approximate solutions of order for stochastic di erential equations (SDEs) driven by multidimensional Brownian motions

  • The new idea we applied in this paper is to replace the iterated stochastic integrals Iα by random variables, so implementing this scheme does not require the computation of the iterated stochastic integrals Iα

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Summary

Introduction

The purpose of this paper is to develop a new pathwise approximation to numerical solutions of SDEs driven by multidimensional Brownian motion. There is a standard approach, which described in [1], approximates solutions of SDEs to the required order using stochastic Taylor expansion at each time step. Applying this method would be di cult when the deriving Brownian motion dimension is greater than to get higher order than , due to hardness of generating the iterated stochastic integrals Iα. We aim to present a new pathwise approximation scheme that can be used to get a higherorder approximation for Brownian motion in dimension greater than It is based on using a coupling and a version of the perturbation method. This paper, organized as follows: section , gives a background material, and section , shows the implementation of the scheme

Background
Approximate Solution x1 Approximate Solution x2
Conclusion
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