粗糙路径驱动下随机微分方程解的Taylor展开和Castell估计

Qi Feng, Xuejing Zhang
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引用次数: 2

摘要

研究了$p$-粗糙路径驱动的微分方程解的泰勒展开式。在以初始点为中心的球上,如果向量场是解析的,则证明了泰勒展开在非空区间上的收敛性的一般定理。我们还推导了一些准则,使我们能够研究泰勒展开的收敛速度。最后,也是本文最主要和最具独创性的部分,我们证明了具有有限$2D~\rho-$变化和带有Hurst参数$H>1/4$分数阶布朗运动的连续中心高斯过程驱动的随机微分方程解的余项的Castell展开式和带指数衰减的尾估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Taylor Expansions and Castell Estimates for Solutions of Stochastic Differential Equations Driven by Rough Paths
We study the Taylor expansion for the solutions of differential equations driven by $p$-rough paths with $p>2$. We prove a general theorem concerning the convergence of the Taylor expansion on a nonempty interval provided that the vector fields are analytic on a ball centered at the initial point. We also derive criteria that enable us to study the rate of convergence of the Taylor expansion. Finally and this is also the main and the most original part of this paper, we prove Castell expansions and tail estimates with exponential decays for the remainder terms of the solutions of the stochastic differential equations driven by continuous centered Gaussian process with finite $2D~\rho-$variation and fractional Brownian motion with Hurst parameter $H>1/4$.
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