English

Formulae for mixed moments of Wiener processes and a stochastic area integral

Probability 2023-07-12 v1 Numerical Analysis Numerical Analysis

Abstract

This paper deals with the expectation of monomials with respect to the stochastic area integral A1,2(t,t+h)=tt+htsdW1(r)dW2(s)tt+htsdW2(r)dW1(s)A_{1,2}(t,t+h)=\int_{t}^{t+h}\int_{t}^{s}{\rm d} W_{1}(r){\rm d} W_{2}(s) -\int_{t}^{t+h}\int_{t}^{s}{\rm d} W_{2}(r){\rm d} W_{1}(s) and the increments of two Wiener processes, ΔWi(t,t+h)=Wi(t+h)Wi(t), i=1,2\Delta{W}_{i}(t,t+h)=W_{i}(t+h)-W_{i}(t),\ i=1,2. In a monomial, if the exponent of one of the Wiener increments or the stochastic area integral is an odd number, then the expectation of the monomial is zero. However, if the exponent of any of them is an even number, then the expectation is nonzero and its exact value is not known in general. In the present paper, we derive formulae to give the value in general. As an application of the formulae, we will utilize the formulae for a careful stability analysis on a Magnus-type Milstein method. As another application, we will give some mixed moments of the increments of Wiener processes and stochastic double integrals.

Keywords

Cite

@article{arxiv.2303.11659,
  title  = {Formulae for mixed moments of Wiener processes and a stochastic area integral},
  author = {Yoshio Komori and Guoguo Yang and Kevin Burrage},
  journal= {arXiv preprint arXiv:2303.11659},
  year   = {2023}
}

Comments

This is a preprint of a paper, which has been accepted for publication in SIAM Journal on Numerical Analysis