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In this paper, we introduce a class of backward stochastic equations (BSEs) that extend classical BSDEs and include many interesting examples of generalized BSDEs as well as semimartingale backward equations. We show that a BSE can be…

Probability · Mathematics 2017-03-28 Patrick Cheridito , Kihun Nam

This paper is concerned with a linear quadratic (LQ, for short) optimal control problem for mean-field backward stochastic differential equations (MF-BSDE, for short) driven by a Poisson random martingale measure and a Brownian motion.…

Optimization and Control · Mathematics 2016-11-22 Maoning Tang , Qingxin Meng

The purpose of this paper is to explore the necessary conditions for optimality of mean-field forward-backward delay control systems. A new estimate is proved, which is a powerfultool to deal with the optimal control problems of mean-field…

Optimization and Control · Mathematics 2018-11-06 Tao Hao , Qingxin Meng

In this paper, we study a class of mean-field reflected backward stochastic differential equations (MF-RBSDEs) driven by a marked point process and also analyze MF-RBSDEs driven by a Poisson process. Based on a $g$-expectation…

Probability · Mathematics 2025-06-12 Yiqing Lin , Kun Xu

We study a class of backward stochastic differential equations (BSDEs) driven by a random measure or, equivalently, by a marked point process. Under appropriate assumptions we prove well-posedness and continuous dependence of the solution…

Probability · Mathematics 2012-05-24 Fulvia Confortola , Marco Fuhrman

We derive a Maximum Principle for optimal control problems with constraints given by the coupling of a system of ODEs and a PDE of Vlasov-type. Such problems arise naturally as ${\Gamma}$-limits of optimal control problems subject to ODE…

Optimization and Control · Mathematics 2015-04-10 Mattia Bongini , Massimo Fornasier , Francesco Rossi , Francesco Solombrino

The paper studies a multi-dimensional mean-field reflected backward stochastic differential equation (MF-RBSDE) with a reflection constraint depending on both the value process $Y$ and its distribution $[Y]$. We establish the existence,…

Probability · Mathematics 2023-09-20 Ruisen Qian

We study the well-posedness of a system of forward-backward stochastic differential equations (FBSDEs) corresponding to a degenerate mean field type control problem, when the diffusion coefficient depends on the state together with its…

Probability · Mathematics 2023-11-16 Alain Bensoussan , Ziyu Huang , Shanjian Tang , Sheung Chi Phillip Yam

This paper outlines a novel extension of the classical Pontryagin minimum (maximum) principle to stochastic optimal control problems. Contrary to the well-known stochastic Pontryagin minimum principle involving forward-backward stochastic…

Optimization and Control · Mathematics 2026-05-11 Manfred Opper , Sebastian Reich

The purpose of this paper is to study the following topics and the relation between them: (i) Optimal singular control of mean-field stochastic differential equations with memory, (ii) reflected advanced mean-field backward stochastic…

Optimization and Control · Mathematics 2018-10-26 Nacira Agram , Achref Bachouch , Bernt Øksendal , Frank Proske

In this paper, we consider the mean field game with a common noise and allow the state coefficients to vary with the conditional distribution in a nonlinear way. We assume that the cost function satisfies a convexity and a weak monotonicity…

Optimization and Control · Mathematics 2021-05-26 Ziyu Huang , Shanjian Tang

We study a stochastic optimal control problem for forward-backward control systems with quadratic generators. In order to establish the first and second-order variational and adjoint equations, we obtain a new estimate for one-dimensional…

Optimization and Control · Mathematics 2021-07-06 Mingshang Hu , Shaolin Ji , Rundong Xu

A splitting scheme for backward doubly stochastic differential equations is proposed. The main idea is to decompose a backward doubly stochastic differential equation into a backward stochastic differential equation and a stochastic…

Numerical Analysis · Mathematics 2021-03-17 Feng Bao , Yanzhao Cao , He Zhang

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 study a functional fully coupled forward-backward stochastic differential equations (FBSDEs). Under a new type of integral Lipschitz and monotonicity conditions, the existence and uniqueness of solutions for functional…

Probability · Mathematics 2013-09-30 Shaolin Ji , Shuzhen Yang

In this article, we are interested in solving numerically backward doubly stochastic differential equations (BDSDEs) with random terminal time tau. The main motivations are giving a probabilistic representation of the Sobolev's solution of…

Probability · Mathematics 2016-10-11 Anis Matoussi , Wissal Sabbagh

This paper considers the problem of partially observed optimal control for forward stochastic systems which are driven by Brownian motions and an independent Poisson random measure with a feature that the cost functional is of mean-field…

Probability · Mathematics 2014-03-19 Yaozhong Hu , David Nualart , Qing Zhou

We introduce a class of second order backward stochastic differential equations and show relations to fully non-linear parabolic PDEs. In particular, we provide a stochastic representation result for solutions of such PDEs and discuss Monte…

Probability · Mathematics 2007-05-23 Patrick Cheridito , H. Mete Soner , Nizar Touzi , Nicolas Victoir

In this paper, we investigate an optimal control problem for McKean-Vlasov stochastic partial differential equations, in which the coefficients depend on the law of the state process. For systems with nonconvex control sets, we establish a…

Probability · Mathematics 2026-03-09 Liangying Chen , Wilhelm Stannat

In this paper we consider a mean-field stochastic differential equation, also called Mc Kean-Vlasov equation, with initial data $(t,x)\in[0,T]\times R^d,$ which coefficients depend on both the solution $X^{t,x}_s$ but also its law. By…

Probability · Mathematics 2014-07-07 Rainer Buckdahn , Juan Li , Shige Peng , Catherine Rainer