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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

We consider partial differential equations (PDEs) characterized by an upper barrier that depends on the solution itself and a fixed lower barrier, while accommodating a non-local driver. First, we show a Feynman-Kac representation for the…

Probability · Mathematics 2024-09-04 Magnus Perninge

The Feynman-Kac equations are a type of partial differential equations describing the distribution of functionals of diffusive motion. The probability density function (PDF) of Brownian functionals satisfies the Feynman-Kac formula, being a…

Computational Physics · Physics 2015-02-03 Weihua Deng , Minghua Chen , Eli Barkai

We extend the wellposedness results for second order backward stochastic differential equations introduced by Soner, Touzi and Zhang \cite{stz} to the case of a bounded terminal condition and a generator with quadratic growth in the $z$…

Probability · Mathematics 2014-04-14 Dylan Possamaï , Chao Zhou

In this paper, we address the problem of existence and uniqueness of a global classical solution to a multidimensional stochastic Burgers equation without gradient-type assumptions on the force or the initial condition. The equation is…

Probability · Mathematics 2019-04-22 Alberto Ohashi , Evelina Shamarova

We consider stochastic PDEs \[dY_t = L(Y_t)\, dt + A(Y_t).\, dB_t, t > 0\] and associated PDEs \[du_t = L u_t\, dt, t > 0\] with regular initial conditions. Here, $L$ and $A$ are certain partial differential operators involving…

Probability · Mathematics 2023-08-22 Suprio Bhar , Rajeev Bhaskaran , Arvind Kumar Nath

In this paper we investigate classical solution of a semi-linear system of backward stochastic integral partial differential equations driven by a Brownian motion and a Poisson point process. By proving an It\^{o}-Wentzell formula for jump…

Probability · Mathematics 2010-07-20 Shaokuan Chen , Shanjian Tang

The existence and uniqueness of measure-valued solutions to stochastic nonlinear, non-local Fokker-Planck equations is proven. This type of stochastic PDE is shown to arise in the mean field limit of weakly interacting diffusions with…

Probability · Mathematics 2021-03-30 Michele Coghi , Benjamin Gess

Suppose $N$ is a compact Riemannian manifold, in this paper we will introduce the definition of $N$-valued BSDE and $L^2(\mathbb{T}^m;N)$-valued BSDE for which the solution are not necessarily staying in only one local coordinate. Moreover,…

Probability · Mathematics 2020-10-07 Xin Chen , Wenjie Ye

We first establish the existence of an unbounded solution to a backward stochastic differential equation (BSDE) with generator $g$ allowing a general growth in the state variable $y$ and a sub-quadratic growth in the state variable $z$,…

Probability · Mathematics 2019-10-21 Shengjun Fan , Ying Hu

It is known that Markovian forward-backward stochastic differential equations provide nonlinear Feynman-Kac representation formulae for semilinear parabolic PDEs. We show that non-Markovian forward-backward stochastic differential equations…

Probability · Mathematics 2013-06-19 Andrea Cosso

This paper continues our previous work (Part I, arXiv:2504.18632v3) on the well-posedness of backward stochastic differential equations (BSDEs) involving a nonlinear Young integral of the form $\int_{t}^{T}g(Y_{r})\eta(dr,X_{r})$, with…

Probability · Mathematics 2025-09-08 Jian Song , Huilin Zhang , Kuan Zhang

Discrete Differential Equations (DDEs) are functional equations that relate polynomially a power series $F(t,u)$ in $t$ with polynomial coefficients in a "catalytic" variable $u$ and the specializations, say at $u=1$, of $F(t,u)$ and of…

Symbolic Computation · Computer Science 2023-05-01 Alin Bostan , Hadrien Notarantonio , Mohab Safey El Din

In this work, we present a novel forward differential deep learning-based algorithm for solving high-dimensional nonlinear backward stochastic differential equations (BSDEs). Motivated by the fact that differential deep learning can…

Numerical Analysis · Mathematics 2024-08-13 Lorenc Kapllani , Long Teng

This paper investigates solvability of fully coupled systems of forward-backward stochastic differential equations (FBSDEs) with irregular coefficients. In particular, we assume that the coefficients of the FBSDEs are merely measurable and…

Probability · Mathematics 2020-04-02 Peng Luo , Olivier Menoukeu-Pamen , Ludovic Tangpi

In this paper, we introduce a new type of backward stochastic differential equations (BSDEs) with infinite anticipation, where the generator depends on the entire future values of the solution in infinite horizon. We show that the new BSDEs…

Probability · Mathematics 2025-11-20 Guanwei Cheng , Shuzhen Yang

We obtain an existence and uniqueness theorem for fully coupled forward-backward SDEs (FBSDEs) with jumps via the classical solution to the associated quasilinear parabolic partial integro-differential equation (PIDE), and provide the…

Probability · Mathematics 2019-11-18 Evelina Shamarova , Rui Sá Pereira

In this paper we introduce a multilevel Picard approximation algorithm for semilinear parabolic partial integro-differential equations (PIDEs). We prove that the numerical approximation scheme converges to the unique viscosity solution of…

Numerical Analysis · Mathematics 2025-03-13 Ariel Neufeld , Sizhou Wu

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

In this paper we consider a mean-field backward stochastic differential equation (BSDE) driven by a Brownian motion and an independent Poisson random measure. Translating the splitting method introduced by Buckdahn, Li, Peng and Rainer [6]…

Probability · Mathematics 2017-02-20 Juan Li
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