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In this paper we study the optimal stochastic control problem for stochastic differential systems reflected in a domain. The cost functional is a recursive one, which is defined via generalized backward stochastic differential equations…

Probability · Mathematics 2013-08-26 Juan Li , Shanjian Tang

In this paper, we consider the fully coupled forward-backward stochastic functional differential equations (FBSFDEs) with stochastic functional differential equations as the forward equations and the generalized anticipated backward…

Probability · Mathematics 2013-12-05 Xiaoming Xu

We study an optimal control problem on infinite horizon for a controlled stochastic differential equation driven by Brownian motion, with a discounted reward functional. The equation may have memory or delay effects in the coefficients,…

Optimization and Control · Mathematics 2017-10-19 F. Confortola , A. Cosso , M. Fuhrman

We address a general optimal switching problem over finite horizon for a stochastic system described by a differential equation driven by Brownian motion. The main novelty is the fact that we allow for infinitely many modes (or regimes,…

Optimization and Control · Mathematics 2019-08-07 Marco Fuhrman , Marie-Amélie Morlais

Two novel numerical estimators are proposed for solving forward-backward stochastic differential equations (FBSDEs) appearing in the Feynman-Kac representation of the value function in stochastic optimal control problems. In contrast to the…

Optimization and Control · Mathematics 2021-10-01 Kelsey P. Hawkins , Ali Pakniyat , Panagiotis Tsiotras

This paper is concerned with linear quadratic optimal control problems for mean-field backward stochastic differential equations (MF-BSDEs, for short) with deterministic coefficients. The optimality system, which is a linear mean-field…

Optimization and Control · Mathematics 2016-10-11 Xun Li , Jingrui Sun , Jie Xiong

Backward doubly stochastic Volterra integral equations (BDSVIEs, for short) are introduced and studied systematically. Well-posedness of BDSVIEs in the sense of introduced M-solutions is established. A comparison theorem for BDSVIEs is…

Probability · Mathematics 2019-06-26 Yufeng Shi , Jiaqiang Wen , Jie Xiong

This paper is concerned with optimal control of stochastic fully coupled forward-backward linear quadratic (FBLQ) problems with indefinite control weight costs. In order to obtain the state feedback representation of the optimal control, we…

Optimization and Control · Mathematics 2019-02-27 Mingshang Hu , Shaolin Ji , Xiaole Xue

In this paper, we focus on a class of time-inconsistent stochastic control problems, where the objective function includes the mean and several higher-order central moments of the terminal value of state. To tackle the time-inconsistency,…

Mathematical Finance · Quantitative Finance 2025-05-08 Yike Wang , Jingzhen Liu , Alain Bensoussan , Ka-Fai Cedric Yiu , Jiaqin Wei

In this introductory paper, we discuss how quantitative finance problems under some common risk factor dynamics for some common instruments and approaches can be formulated as time-continuous or time-discrete forward-backward stochastic…

Computational Finance · Quantitative Finance 2019-11-29 Bernhard Hientzsch

In this paper, we study non-homogeneous stochastic linear-quadratic (LQ) optimal control problems with multi-dimensional state and regime switching. We focus on the corresponding stochastic Riccati equation, which is the same as that one in…

Optimization and Control · Mathematics 2024-04-02 Yuyang Chen , Peng Luo

In this paper, our primary focus lies in the thorough investigation of a specific category of nonlinear fully coupled forward-backward stochastic differential equations involving time delays and advancements with the incorporation of…

Optimization and Control · Mathematics 2023-10-23 Maozhong Xu , Maoning Tang , Qingxin Meng

This paper is concerned with a general linear quadratic (LQ) control problem of mean-field backward stochastic differential equation (BSDE). Here, the weighting matrices in the cost functional are allowed to be indefinite. Necessary and…

Optimization and Control · Mathematics 2024-12-31 Wencan Wang , Huanjun Zhang

In this paper, we explore a new class of stochastic control problems characterized by specific control constraints. Specifically, the admissible controls are subject to the ratcheting constraint, meaning they must be non-decreasing over…

Optimization and Control · Mathematics 2024-12-17 Mingxin Guo , Zuo Quan Xu

We study the stochastic control-stopping problem when the data are of polynomial growth. The approach is based on backward stochastic dierential equations (BSDEs for short). The problem turns into the study of a specic reected BSDE with a…

Optimization and Control · Mathematics 2020-05-15 Brahim Asri , Said Hamadène , Khalid Oufdil

In this paper we are concerned with a class of stochastic Volterra integro-differential problems with completely monotone kernels, where we assume that the noise enters the system when we introduce a control. We start by reformulating the…

Probability · Mathematics 2011-12-19 Fulvia Confortola , Elisa Mastrogiacomo

In this paper,we mainly focus on the numerical solution of high-dimensional stochastic optimal control problem driven by fully-coupled forward-backward stochastic differential equations (FBSDEs in short) through deep learning. We first…

Optimization and Control · Mathematics 2024-08-21 Shaolin Ji , Shige Peng , Ying Peng , Xichuan Zhang

A time-inconsistent optimal control problem is formulated and studied for a controlled linear ordinary differential equation with quadratic cost functional. A notion of equilibrium control is introduced, which can be regarded as a…

Optimization and Control · Mathematics 2012-04-10 Jiongmin Yong

We study the time-inconsistent linear quadratic optimal control problem for forward-backward stochastic differential equations with potentially indefinite cost weighting matrices for both the state and the control variables. Our research…

Optimization and Control · Mathematics 2023-12-15 Qi Lü , Bowen Ma

This paper proposes two algorithms for solving stochastic control problems with deep learning, with a focus on the utility maximisation problem. The first algorithm solves Markovian problems via the Hamilton Jacobi Bellman (HJB) equation.…

Computational Finance · Quantitative Finance 2024-10-15 Ashley Davey , Harry Zheng