CRANK-NICOLSON SCHEME FOR STOCHASTIC DIFFERENTIAL EQUATIONS DRIVEN BY FRACTIONAL BROWNIAN MOTIONS

• 成果类型: Article
• 署名作者: Hu, Yaozhong; Liu, Yanghui; Nualart, David
• 署名单位: University of Alberta; City University of New York (CUNY) System; Baruch College (CUNY); University of Kansas
• 刊物名称: ANNALS OF APPLIED PROBABILITY
• ISSN/ISSBN: 1050-5164
• DOI: 10.1214/20-AAP1582
• 发表日期: 2021
• 页码: 39-83
• 关键词: sdes driven; approximation schemes; LIMIT-THEOREMS; CONVERGENCE

摘要

We study the Crank-Nicolson scheme for stochastic differential equations (SDEs) driven by a multidimensional fractional Brownian motion with Hurst parameterH > 1/2. It is well known that for ordinary differential equations with proper conditions on the regularity of the coefficients, the Crank-Nicolson scheme achieves a convergence rate of n(-2), regardless of the dimension. In this paper we show that, due to the interactions between the driving processes, the corresponding Crank-Nicolson scheme for m-dimensional SDEs has a slower rate than for one-dimensional SDEs. Precisely, we shall prove that when the fBm is one-dimensional and when the drift term is zero, the Crank-Nicolson scheme achieves the convergence rate n(-2H), and when the drift term is nonzero, the exact rate turns out to be n(-1/2-H). In the general multidimensional case the exact rate equals n(-1/2-2H). In all these cases the asymptotic error is proved to satisfy some linear SDE. We also consider the degenerated cases when the asymptotic error equals zero.