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There exists a diversity of weak Local Linearization (LL) schemes for the integration of stochastic differential equations with additive noise, which differ with respect to the algorithm that is employed in the numerical implementation of…

Numerical Analysis · Mathematics 2013-12-23 J. C. Jimenez , F. Carbonell

We investigate the problem of the rate of convergence to equilibrium for ergodic stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H\in (1/3,1)$ and multiplicative noise component $\sigma$. When…

Probability · Mathematics 2016-10-05 Aurélien Deya , Fabien Panloup , Samy Tindel

We consider finite element approximations for a one dimensional second order stochastic differential equation of boundary value type driven by a fractional Brownian motion with Hurst index $H\le 1/2$. We make use of a sequence of…

Numerical Analysis · Mathematics 2020-06-08 Yanzhao Cao , Jialin Hong , Zhihui Liu

We consider the rough differential equations driven by tempered fractional Brownian motion with Hurst index $H\in (\frac{1}{4}, \frac{1}{3})$ and tempered parameter $\lambda>0$. First, by means of piecewise linear approximation, we…

Dynamical Systems · Mathematics 2026-03-10 Lijuan Zhang , Jianhua Huang

We consider a Brownian functional $F=g\bigl(\int_0^T \eta(s) dW_s\bigr)$ with $g \in L_2(\gamma)$ and a singular deterministic $\eta$. We deduce the $L_2$-convergence rate for the approximation $F^{(n)} = E F + \int_0^T \phi^{(n)}(s) dW_s$…

Probability · Mathematics 2016-03-16 Dario Gasbarra , Anni Laitinen

We present an error analysis of weak convergence of one-step numerical schemes for stochastic differential equations (SDEs) with super-linearly growing coefficients. Following Milstein's weak error analysis on the one-step approximation of…

Numerical Analysis · Mathematics 2023-03-29 Xiaojie Wang , Yuying Zhao , Zhongqiang Zhang

We present an error analysis of weak convergence of one-step numerical schemes for stochastic differential equations (SDEs) with super-linearly growing coefficients. Following Milstein's weak error analysis on the one-step approximation of…

Numerical Analysis · Mathematics 2023-03-29 Xiaojie Wang , Yuying Zhao , Zhongqiang Zhang

This work focuses on moderate deviations for two-time scale systems with mixed fractional Brownian motion. Our proof uses the weak convergence method which is based on the variational representation formula for mixed fractional Brownian…

Dynamical Systems · Mathematics 2024-03-13 Xiaoyu Yang , Yuzuru Inahama , Yong Xu

In this paper, the weak convergence about the discretization error of stochastic iterated integrals in the Skorohod sense are studied, while the integrands and integrators of iterated integrals are supposed to be semimartingales with jumps.…

Probability · Mathematics 2017-06-06 Yuping Song , Hanchao Wang

For equidistant discretizations of fractional Brownian motion (fBm), the probabilities of ordinal patterns of order d=2 are monotonically related to the Hurst parameter H. By plugging the sample relative frequency of those patterns…

Probability · Mathematics 2008-01-11 Mathieu Sinn , Karsten Keller

We study the estimation of the invariant density of additive fractional stochastic differential equations with Hurst parameter $H \in (0,1)$. We first focus on continuous observations and develop a kernel-based estimator achieving faster…

Statistics Theory · Mathematics 2025-12-23 Chiara Amorino , Eulalia Nualart , Fabien Panloup , Julian Sieber

This paper proves joint convergence of the approximation error for several stochastic integrals with respect to local Brownian semimartingales, for nonequidistant and random grids. The conditions needed for convergence are that the Lebesgue…

Probability · Mathematics 2013-09-24 Carl Lindberg , Holger Rootzén

We introduce a simulation scheme for Brownian semistationary processes, which is based on discretizing the stochastic integral representation of the process in the time domain. We assume that the kernel function of the process is regularly…

Probability · Mathematics 2018-09-24 Mikkel Bennedsen , Asger Lunde , Mikko S. Pakkanen

This paper is concerned with the numerical analysis of the explicit upwind finite volume scheme for numerically solving continuity equations. We are interested in the case where the advecting velocity field has spatial Sobolev regularity…

Analysis of PDEs · Mathematics 2020-06-04 André Schlichting , Christian Seis

We estimate the Hurst parameter $H$ of a fractional Brownian motion from discrete noisy data observed along a high frequency sampling scheme. The presence of systematic experimental noise makes recovery of $H$ more difficult since relevant…

Statistics Theory · Mathematics 2007-12-18 Arnaud Gloter , Marc Hoffmann

We present an abstract framework for analyzing the weak error of fully discrete approximation schemes for linear evolution equations driven by additive Gaussian noise. First, an abstract representation formula is derived for sufficiently…

Numerical Analysis · Mathematics 2013-07-17 M. Kovács , S. Larsson , F. Lindgren

In this paper, we study two variations of the time discrete Taylor schemes for rough differential equations and for stochastic differential equations driven by fractional Brownian motions. One is the incomplete Taylor scheme which excludes…

Probability · Mathematics 2015-10-30 Yaozhong Hu , Yanghui Liu , David Nualart

In this work we study rough differential equations driven by a fractional Brownian motion with Hurst parameter H>1/4 and establish Varadhan's small time estimates for the density of solutions of such equations under Hormander's type…

Probability · Mathematics 2013-04-30 Fabrice Baudoin , Cheng Ouyang , Xuejing Zhang

Rough volatility models are known to reproduce the behavior of historical volatility data while at the same time fitting the volatility surface remarkably well, with very few parameters. However, managing the risks of derivatives under…

Mathematical Finance · Quantitative Finance 2017-03-16 Omar El Euch , Mathieu Rosenbaum

Many fractional processes can be represented as an integral over a family of Ornstein-Uhlenbeck processes. This representation naturally lends itself to numerical discretizations, which are shown in this paper to have strong convergence…

Mathematical Finance · Quantitative Finance 2020-08-06 Philipp Harms