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Related papers: Ergodic BSDEs under weak dissipative assumptions

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Since the celebrated paper by El Karoui, Peng and Quenez [Mathematical Finance, 7 (1997), 1--71], backward stochastic differential equations have found wide applications in stochastic control, financial technology and machine learning. In…

Probability · Mathematics 2026-02-12 Shengjun Fan , Ying Hu , Shanjian Tang

We prove well-posedness results for backward stochastic differential equations (BSDEs) and reflected BSDEs with an optional obstacle process in the case of appropriately weighted $\mathbb{L}^2$-data when the generator is integrated with…

Probability · Mathematics 2024-12-13 Dylan Possamaï , Marco Rodrigues

In this work, we extend deep learning-based numerical methods to fully coupled forward-backward stochastic differential equations (FBSDEs) within a non-Markovian framework. Error estimates and convergence are provided. In contrast to the…

Mathematical Finance · Quantitative Finance 2025-11-25 Hasib Uddin Molla , Matthew Backhouse , Ankit Banarjee , Jinniao Qiu

In this paper, we consider backward stochastic differential equations driven by $G$-Brownian motion (GBSDEs) under quadratic assumptions on coefficients. We prove the existence and uniqueness of solution for such equations. On the one hand,…

Probability · Mathematics 2016-03-18 Ying Hu , Yiqing Lin , Abdoulaye Soumana Hima

In this paper we study the class of backward doubly stochastic differential equations (BDSDEs, for short) whose terminal value depends on the history of forward diffusion. We first establish a probabilistic representation for the spatial…

Probability · Mathematics 2008-11-12 Auguste Aman

In this paper we investigate two-player zero-sum stochastic differential games with an ergodic payoff, in which the diffusion coefficient does not need to be non-degenerate. We first establish the existence of a viscosity solution to the…

Optimization and Control · Mathematics 2026-01-21 Juan Li , Wenqiang Li , Yanwei Li , Huaizhong Zhao

We study (backward) stochastic differential equations with noise coming from a finite state Markov chain. We show that, for the solutions of these equations to be `Markovian', in the sense that they are deterministic functions of the state…

Probability · Mathematics 2011-11-28 Samuel N. Cohen , Lukasz Szpruch

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

We study ergodic properties of nonlinear Markov chains and stochastic McKean-Vlasov equations. For nonlinear Markov chains we obtain sufficient conditions for existence and uniqueness of an invariant measure and uniform ergodicity. We also…

Probability · Mathematics 2013-11-26 Oleg Butkovsky

In this work, we study the numerical approximation of a class of singular fully coupled forward backward stochastic differential equations. These equations have a degenerate forward component and non-smooth terminal condition. They are…

Numerical Analysis · Mathematics 2022-08-17 Jean-François Chassagneux , Mohan Yang

Motivated from time-inconsistent stochastic control problems, we introduce a new type of coupled forward-backward stochastic systems, namely, flows of forward-backward stochastic differential equations. They are systems consisting of a…

Probability · Mathematics 2020-04-28 Yushi Hamaguchi

In this paper, we initiate the study of backward doubly stochastic differential equations (BDSDEs, for short) with quadratic growth. The existence, comparison, and stability results for one-dimensional BDSDEs are proved when the generator…

Probability · Mathematics 2022-05-12 Ying Hu , Jiaqiang Wen , Jie Xiong

This paper considers a class of scalar backward stochastic differential equations (BSDEs) with $L\exp(\mu\sqrt{2\log(1+L)})$-integrable terminal values. We associate these BSDEs with BSDEs with integrable parameters through Girsanov change.…

Probability · Mathematics 2019-09-04 Hun O , Mun-Chol Kim , Chol-Gyu Pak

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 article, we propose a wellposedness theory for a class of second order backward doubly stochastic differential equation (2BDSDE). We prove existence and uniqueness of the solution under a Lipschitz type assumption on the generator,…

Probability · Mathematics 2016-10-14 Anis Matoussi , Dylan Possamai , Wissal Sabbagh

We discuss a class of Backward Stochastic Differential Equations(BSDEs) with no driving martingale. When the randomness of the driver depends on a general Markov process $X$, those BSDEs are denominated Markovian BSDEs and can be associated…

Probability · Mathematics 2017-12-29 Adrien Barrasso , Francesco Russo

The existence of stationary distributions to distribution dependent stochastic differential equations are investigated by using the ergodicity of the associated decoupled equation and the Schauder fixed point theorem. By using Zvonkin's…

Probability · Mathematics 2021-05-14 Shao-Qin Zhang

In this paper, we first prove existence and uniqueness of the solution of a backward doubly stochastic differential equation (BDSDE) and of the related stochastic partial differential equation (SPDE) under monotonicity assumption on the…

Probability · Mathematics 2015-05-19 A. Matoussi , Lambert Piozin , A. Popier

In this paper we present a unified approach to establish gradient type formulas and Bismut type formulas for backward stochastic differential equations (BSDEs). This approach relies on a mix of derivative formulas with respect to the…

Probability · Mathematics 2021-03-12 Xiliang Fan , Michael Röckner , Shao-Qin Zhang

Constructions of numerous approximate sampling algorithms are based on the well-known fact that certain Gibbs measures are stationary distributions of ergodic stochastic differential equations (SDEs) driven by the Brownian motion. However,…

Probability · Mathematics 2020-07-07 Lu-Jing Huang , Mateusz B. Majka , Jian Wang
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