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In this paper, we study a collection of mean-reflected backward stochastic differential equations driven by $G$-Brownian motions ($G$-BSDEs), where $G$-expectations are constrained in some time-dependent intervals. To establish…

Probability · Mathematics 2024-07-26 Zihao Gu , Hui Zhao

In this paper, we study backward stochastic differential equations driven by G-Brownian motion where the generator has time-varying monotonicity with respect to y and Lipsitz property with respect to z. Through the Yosida approximation, we…

Probability · Mathematics 2026-03-10 Renxing Li , Xue Zhang

This paper is devoted to study the asymptotic properties for the solution of decoupled forward backward stochastic differential equations with delayed generator. As an application, we establish a large deviation principe for solution of the…

Probability · Mathematics 2022-02-16 Clément Manga , Auguste Aman , Navegué Tuo

In this paper, we focus on the mean-field backward stochastic differential equations (BSDEs) driven by a fractional Brownian motion with Hurst parameter H greater then 1/2. First, the existence and uniqueness of these equations are…

Probability · Mathematics 2017-05-30 Jiaqiang Wen , Yufeng Shi

This paper discusses a new type of anticipated backward stochastic differential equation with a time-delayed generator (DABSDEs, for short) driven by fractional Brownian motion, also known as fractional BSDEs, with Hurst parameter…

Probability · Mathematics 2023-05-24 Pei Zhang , Nur Anisah Mohamed , Adriana Irawati Nur Ibrahim

Distribution dependent stochastic differential equations have been a very hot subject with extensive studies. On the other hand, under the $G$-expectation framework, stochastic differential equations driven by $G$-Brownian motion (in short…

Probability · Mathematics 2023-02-27 De Sun , Jiang-Lun Wu , Panyu Wu

In this note, we prove the Freidlin-Wentzell's large deviation principle for BSDEs with one-sided reflection.

Probability · Mathematics 2011-12-01 Liangquan Zhang

The aim is to prove the well-posedness of infinite horizon backward stochastic differential equations driven by $G$-Brownian motion ($G$-BSDEs) with quadratic generators. To this end, we provide a full construction of explicit solutions to…

Probability · Mathematics 2025-09-09 Yiqing Lin , Yifan Sun , Falei Wang

In this paper, we focus on mean-field anticipated backward stochastic differential equations (MF-BSDEs, for short) driven by fractional Brownian motion with Hurst parameter H>1/2. First, the existence and uniqueness of this new type of…

Probability · Mathematics 2018-05-23 Soukaina Douissi , Jiaqiang Wen , Yufeng Shi

In this paper, we are concerned with multi-scale distribution dependent stochastic differential equations driven by fractional Brownian motion (with Hurst index $H>\frac12$ and standard Brownian motion, simultaneously. Our aim is to…

Probability · Mathematics 2023-06-12 Shen Gunagjun , Zhou Huan , Wu Jianglun

The present paper is devoted to the study of sample paths of G-Brownian motion and stochastic differential equations (SDEs) driven by G-Brownian motion from the view of rough path theory. As the starting point, we show that quasi-surely,…

Probability · Mathematics 2013-06-11 Xi Geng , Zhongmin Qian , Danyu Yang

In this paper, we present a sufficient condition for the large deviation criteria of Budhiraja, Dupuis and Maroulas for functionals of Brownian motions. We then establish a large deviation principle for obstacle problems of quasi-linear…

Probability · Mathematics 2017-12-07 Anis Matoussi , Wissal Sabbagh , Tusheng Zhang

We establish a large deviation principle for the solutions of a class of stochastic partial differential equations with non-Lipschitz continuous coefficients. As an application, the large deviation principle is derived for super-Brownian…

Probability · Mathematics 2012-05-11 Parisa Fatheddin , Jie Xiong

The aim of this paper is to present the analysis for the solutions of nonlinear stochastic functional differential equation driven by G-Brownian motion with infinite delay (G-SFDEwID). Under some useful assumptions, we have proved that the…

Probability · Mathematics 2018-06-12 Faiz Faizullah

This paper provides a large deviation principle for Non-Markovian, Brownian motion driven stochastic differential equations with random coefficients. Similar to Gao and Liu \cite{GL}, this extends the corresponding results collected in…

Probability · Mathematics 2014-07-22 Jin Ma , Zhenjie Ren , Nizar Touzi , Jianfeng Zhang

In this paper we are concerned with distribution dependent backward stochastic differential equations (DDBSDEs) driven by Gaussian processes. We first show the existence and uniqueness of solutions to this type of equations. This is done by…

Probability · Mathematics 2023-02-08 Xiliang Fan , Jiang-Lun Wu

Explicit solutions for a class of linear backward stochastic differential equations (BSDE) driven by Gaussian Volterra processes are given. These processes include the multifractional brownian motion and the multifractional…

Probability · Mathematics 2019-12-03 Habiba Knani , Marco Dozzi

In this paper, we study the reflected stochastic differential equations driven by G-Brownian motion (reflected G-SDEs) with two nonlinear constraints. With the help of the Skorokhod problem with nonlinear constraints, we first study the…

Probability · Mathematics 2026-04-27 Hanwu Li

The asymptotic analysis of a class of stochastic partial differential equations (SPDEs) with fully locally monotone coefficients covering a large variety of physical systems, a wide class of quasilinear SPDEs and a good number of fluid…

Probability · Mathematics 2022-12-13 Ankit Kumar , Manil T. Mohan

We first state a special type of It\^o formula involving stochastic integrals of both standard and fractional Brownian motions. Then we use Doss-Sussman transformation to establish the link between backward doubly stochastic differential…

Probability · Mathematics 2011-03-18 Shuai Jing