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We obtain weighted uniform estimates for the gradient of the solutions to a class of linear parabolic Cauchy problems with unbounded coefficients. Such estimates are then used to prove existence and uniqueness of the mild solution to a…

Analysis of PDEs · Mathematics 2014-02-04 Davide Addona

This paper studies the stochastic optimal control of jump-diffusion processes and the associated fully nonlinear backward stochastic Hamilton--Jacobi--Bellman (BSHJB) equations. We establish the dynamic programming principle (DPP) via…

Optimization and Control · Mathematics 2026-05-21 Dunxiang Liang , Qingxin Meng

We study the forward investment performance process (FIPP) in an incomplete semimartingale market model with closed and convex portfolio constraints, when the investor's risk preferences are of the power form. We provide necessary and…

Probability · Mathematics 2022-01-27 Lijun Bo , Agostino Capponi , Chao Zhou

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

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

This paper is devoted to a stochastic differential game of functional forward-backward stochastic differential equation (FBSDE, for short). The associated upper and lower value functions of the stochastic differential game are defined by…

Optimization and Control · Mathematics 2013-01-03 Shaolin Ji , Qingmeng Wei

In this paper, we propose a novel data-driven framework for discovering probabilistic laws underlying the Feynman-Kac formula. Specifically, we introduce the first stochastic SINDy method formulated under the risk-neutral probability…

Mathematical Finance · Quantitative Finance 2025-11-13 Qi Feng , Guang Lin , Purav Matlia , Denny Serdarevic

We consider a class of backward stochastic differential equations (BSDEs) driven by Brownian motion and Poisson random measure, and subject to constraints on the jump component. We prove the existence and uniqueness of the minimal solution…

Probability · Mathematics 2016-08-14 Idris Kharroubi , Jin Ma , Huyên Pham , Jianfeng Zhang

This work is devoted to the study of optimal control of stochastic functional differential equations (SFDEs) and its application to mathematical finance. By using the Dynkin formula and solution of the Dirichlet-Poisson problem, the…

Optimization and Control · Mathematics 2014-04-04 Edson A. Coayla-Teran , Anatoly Swishchuk

The paper is devoted to the construction of a probabilistic particle algorithm. This is related to nonlin-ear forward Feynman-Kac type equation, which represents the solution of a nonconservative semilinear parabolic Partial Differential…

Probability · Mathematics 2017-09-15 Anthony Le Cavil , Nadia Oudjane , Francesco Russo

We consider a stochastic functional delay differential equation, namely an equation whose evolution depends on its past history as well as on its present state, driven by a pure diffusive component plus a pure jump Poisson compensated…

Probability · Mathematics 2017-02-17 Francesco Cordoni , Luca Di Persio , Immacolata Oliva

In this paper, we guarantee the existence and uniqueness (in the almost everywhere sense) of the solution to a Hamilton-Jacobi-Bellman (HJB) equation with gradient constraint and a partial integro-differential operator whose L\'evy measure…

Analysis of PDEs · Mathematics 2019-03-26 Mark Kelbert , Harold A. Moreno-Franco

In this work we study the numerical approximation of a class of ergodic Backward Stochastic Differential Equations. These equations are formulated in an infinite horizon framework and provide a probabilistic representation for elliptic…

Numerical Analysis · Mathematics 2024-09-11 Emmanuel Gobet , Adrien Richou , Lukasz Szpruch

Stochastic optimal principle leads to the resolution of a partial differential equation (PDE), namely the Hamilton-Jacobi-Bellman (HJB) equation. In general, this equation cannot be solved analytically, thus numerical algorithms are the…

Numerical Analysis · Mathematics 2021-09-14 Christelle Dleuna Nyoumbi , Antoine Tambue

In this paper, we study forward-backward doubly stochastic differential equations driven by Brownian motions and Poisson process (FBDSDEP in short). Both the probabilistic interpretation for the solutions to a class of quasilinear…

Probability · Mathematics 2010-05-17 Qingfeng Zhu , Yufeng Shi

We develop algorithms for the numerical computation of the quadratic hedging strategy in incomplete markets modeled by pure jump Markov process. Using the Hamilton-Jacobi-Bellman approach, the value function of the quadratic hedging problem…

Risk Management · Quantitative Finance 2013-12-12 Carmine De Franco , Peter Tankov , Xavier Warin

We study linear-quadratic stochastic optimal control problems with bilinear state dependence for which the underlying stochastic differential equation (SDE) consists of slow and fast degrees of freedom. We show that, in the same way in…

Dynamical Systems · Mathematics 2018-03-21 Omar Kebiri , Lara Neureither , Carsten Hartmann

The Feynman-Kac formulae (FKF) express local solutions of partial differential equations (PDEs) as expectations with respect to some complementary stochastic differential equation (SDE). Repeatedly sampling paths from the complementary SDE…

Methodology · Statistics 2016-03-15 Jake Carson , Murray Pollock , Mark Girolami

In this paper, we study an optimal control problem of linear backward stochastic differential equation (BSDE) with quadratic cost functional under partial information. This problem is solved completely and explicitly by using a stochastic…

Optimization and Control · Mathematics 2020-12-16 Guangchen Wang , Wencan Wang , Zhiguo Yan

We present a computational alternative to probabilistic simulations for non-smooth stochastic dynamical systems that are prevalent in engineering mechanics. As examples, we target (1) stochastic elasto-plastic problems, which involve…

Probability · Mathematics 2019-05-23 Laurent Mertz , Georg Stadler , Jonathan Wylie