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Backward stochastic differential equations (BSDEs) appear in numeruous applications. Classical approximation methods suffer from the curse of dimensionality and deep learning-based approximation methods are not known to converge to the BSDE…

Probability · Mathematics 2022-04-20 Martin Hutzenthaler , Tuan Anh Nguyen

We propose new numerical schemes for decoupled forward-backward stochastic differential equations (FBSDEs) with jumps, where the stochastic dynamics are driven by a $d$-dimensional Brownian motion and an independent compensated Poisson…

Numerical Analysis · Mathematics 2015-08-06 Weidong Zhao , Wei Zhang , Guannan Zhang

We introduce a predictor-corrector discretisation scheme for the numerical integration of a class of stochastic differential equations and prove that it converges with weak order 1.0. The key feature of the new scheme is that it builds up…

Computation · Statistics 2024-02-01 Deniz Akyildiz , Dan Crisan , Joaquin Miguez

We establish upper bounds for the $L^p$-quantization error, p in (1, 2+d), induced by the recursive Markovian quantization of a d-dimensional diffusion discretized via the Euler scheme. We introduce a hybrid recursive quantization scheme,…

Probability · Mathematics 2021-05-18 Rancy El Nmeir , Gilles Pagès

In this article we propose a new explicit Euler-type approximation method for stochastic differential equations (SDEs). In this method, Brownian increments in the recursion of the Euler method are replaced by suitable bounded functions of…

Probability · Mathematics 2022-04-27 Martin Hutzenthaler , Kai Kisker

In this paper we consider the Euler-Maruyama scheme for a class ofstochastic delay differential equations driven by a fractional Brownian motion with index $H\in(0,1)$. We establish the consistency of the scheme and study the rate of…

Probability · Mathematics 2025-06-27 Orimar Sauri

In this paper, we derive error estimates of the backward Euler-Maruyama method applied to multi-valued stochastic differential equations. An important example of such an equation is a stochastic gradient flow whose associated potential is…

Numerical Analysis · Mathematics 2022-05-10 Monika Eisenmann , Mihály Kovács , Raphael Kruse , Stig Larsson

In this paper we present a numerical scheme for stochastic differential equations based upon the Wiener chaos expansion. The approximation of a square integrable stochastic differential equation is obtained by cutting off the infinite chaos…

Probability · Mathematics 2019-06-05 Tony Huschto , Mark Podolskij , Sebastian Sager

We consider linearizations of stochastic differential equations with additive noise using the Karhunen-Lo\`eve expansion. We obtain our linearizations by truncating the expansion and writing the solution as a series of matrix-vector…

Numerical Analysis · Mathematics 2020-04-14 Antti Koskela , Samuel D. Relton

This paper deals with asymptotic errors, limit theorems for errors between numerical and exact solutions of stochastic differential equation (SDE) driven by one-dimensional fractional Brownian motion (fBm). The Euler-Maruyama, higher-order…

Numerical Analysis · Mathematics 2024-10-01 Kento Ueda

In this paper, we prove convergence for contractive time discretisation schemes for semi-linear stochastic evolution equations with irregular Lipschitz nonlinearities, initial values, and additive or multiplicative Gaussian noise on…

Numerical Analysis · Mathematics 2024-05-13 Katharina Klioba , Mark Veraar

A high-accuracy time discretization is discussed to numerically solve the nonlinear fractional diffusion equation forced by a space-time white noise. The main purpose of this paper is to improve the temporal convergence rate by modifying…

Numerical Analysis · Mathematics 2021-05-04 Xing Liu

In this paper, the a posteriori error estimates of the exponential midpoint method for time discretization are studied for linear and semilinear parabolic equations. Using the exponential midpoint approximation defined by a continuous and…

Numerical Analysis · Mathematics 2024-06-13 Xianfa Hu , Wansheng Wang , Mengli Mao , Jiliang Cao

Two discretizations of a class of locally Lipschitz Markovian backward stochastic differential equations (BSDEs) are studied. The first is the classical Euler scheme which approximates a projection of the processes Z, and the second a novel…

Probability · Mathematics 2014-08-21 Plamen Turkedjiev

In this work, the uncertainty associated with the finite element discretization error is modeled following the Bayesian paradigm. First, a continuous formulation is derived, where a Gaussian process prior over the solution space is updated…

Numerical Analysis · Mathematics 2024-03-11 Anne Poot , Pierre Kerfriden , Iuri Rocha , Frans van der Meer

We address the problem of approximating the moments of the solution, $\boldsymbol{X}(t)$, of an It\^o stochastic differential equation (SDE) with drift and a diffusion terms over a time-grid $t_0, t_1, \ldots, t_n$. In particular, we assume…

Numerical Analysis · Mathematics 2021-06-14 Albert López-Yela , Joaquin Miguez

In the present article we study strong approximation of solutions of scalar stochastic differential equations (SDEs) with bounded and $\alpha$-H\"older continuous drift coefficient and constant diffusion coefficient at time point $1$.…

Probability · Mathematics 2025-04-30 Simon Ellinger , Thomas Müller-Gronbach , Larisa Yaroslavtseva

We consider a class of backward stochastic differential equations (BSDEs) with singular terminal condition and develop a numerical scheme to approximate their solution. To this end, we extend an asymptotic development of the BSDE solution…

Optimization and Control · Mathematics 2026-03-03 Thomas Kruse , Julia Ackermann , Alexandre Popier

This paper gives the exact solution in terms of the Karhunen-Lo\`{e}ve expansion to a fractional stochastic partial differential equation on the unit sphere $\mathbb{S}^{2}\subset \mathbb{R}^{3}$ with fractional Brownian motion as driving…

Statistics Theory · Mathematics 2018-03-05 Vo V. Anh , Philip Broadbridge , Andriy Olenko , Yu Guang Wang

We consider a general class of high order weak approximation schemes for stochastic differential equations driven by L\'evy processes with infinite activity. These schemes combine a compound Poisson approximation for the jump part of the…

Probability · Mathematics 2012-04-24 Arturo Kohatsu-Higa , Salvador Ortiz-Latorre , Peter Tankov