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This paper is concerned with solution in H\"{o}lder spaces of the Cauchy problem for linear and semi-linear backward stochastic partial differential equations (BSPDEs) of super-parabolic type. The pair of unknown variables are viewed as…

Analysis of PDEs · Mathematics 2016-02-10 Shanjian Tang , Wenning Wei

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

The full history recursive multilevel Picard approximation method for semilinear parabolic partial differential equations (PDEs) is the only method which provably overcomes the curse of dimensionality for general time horizons if the…

Numerical Analysis · Mathematics 2022-04-29 Martin Hutzenthaler , Tuan Anh Nguyen

In this paper, we suggest a useful technique based on time change to be effective for dealing with the backward stochastic differential equations. We show the relation between the BSDEs with stochastic Lipschtz coeffecients and the ones…

Probability · Mathematics 2019-03-26 Hun O , Mun-chol Kim , Chol-kyu Pak

In this paper we show the existence and uniqueness of strong solutions for a large class of backward SPDE where the coefficients satisfy a specific type Lyapunov condition instead of the classical coercivity condition. Moreover, based on…

Probability · Mathematics 2019-10-08 Wei Liu , Rongchan Zhu

In this paper, our goal is solving backward doubly stochastic differential equation (BDSDE for short) under weak assumptions on the data. The first part of the paper is devoted to the development of some new technical aspects of stochastic…

Probability · Mathematics 2009-07-14 Auguste Aman

We formulate a new class of stochastic partial differential equations (SPDEs), named high-order vector backward SPDEs (B-SPDEs) with jumps, which allow the high-order integral-partial differential operators into both drift and diffusion…

Probability · Mathematics 2011-05-05 Wanyang Dai

In this paper we deal with the utility maximization problem with a general utility function. We derive a new approach in which we reduce the utility maximization problem with general utility to the study of a fully-coupled Forward-Backward…

Probability · Mathematics 2011-10-13 Ulrich Horst , Ying Hu , Peter Imkeller , Anthony Réveillac , Jianing Zhang

This paper presents a partial state of the art about the topic of representation of generalized Fokker-Planck Partial Differential Equations (PDEs) by solutions of McKean Feynman-Kac Equations (MFKEs) that generalize the notion of McKean…

Probability · Mathematics 2019-12-09 Lucas Izydorczyk , Nadia Oudjane , Francesco Russo

In Liang et al (2009), the current authors demonstrated that BSDEs can be reformulated as functional differential equations, and as an application, they solved BSDEs on general filtered probability spaces. In this paper the authors continue…

Probability · Mathematics 2010-11-22 G. Liang , T. Lyons , Z. Qian

We propose a time-space discretization scheme for quasi-linear parabolic PDEs. The algorithm relies on the theory of fully coupled forward--backward SDEs, which provides an efficient probabilistic representation of this type of equation.…

Probability · Mathematics 2016-08-16 François Delarue , Stéphane Menozzi

This paper is to investigate if the solution of a hybrid stochastic functional differential equation (SFDE) with infinite delay can be approximated by the solution of the corresponding hybrid SFDE with finite delay. A positive result is…

Probability · Mathematics 2025-12-23 Guozhen Li , Xiaoyue Li , Xuerong Mao , Guoting Song

We study reflected solutions of one-dimensional backward doubly stochastic differential equations (BDSDEs in short). The "reflected" keeps the solution above a given stochastic process. We get the uniqueness and existence by penalization.…

Probability · Mathematics 2009-06-08 Weiqiang Yang , Yufeng Shi , Yangling Gu

Novel multi-step predictor-corrector numerical schemes have been derived for approximating decoupled forward-backward stochastic differential equations (FBSDEs). The stability and high order rate of convergence of the schemes are rigorously…

Numerical Analysis · Mathematics 2021-02-12 Qiang Han , Shaolin Ji

We prove an $L^2$-regularity result for the solutions of Forward Backward Doubly Stochastic Differentiel Equations (FBDSDEs in short) under globally Lipschitz continuous assumptions on the coefficients. Therefore, we extend the well known…

Probability · Mathematics 2017-09-25 Achref Bachouch , Anis Matoussi

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

We prove strong well-posedness for a class of stochastic evolution equations in Hilbert spaces H when the drift term is Holder continuous. This class includes examples of semilinear stochastic damped wave equations which describe elastic…

Probability · Mathematics 2023-06-01 Davide Addona , Federica Masiero , Enrico Priola

The Feynman-Kac formula implies that every suitable classical solution of a semilinear Kolmogorov partial differential equation (PDE) is also a solution of a certain stochastic fixed point equation (SFPE). In this article we study such and…

Probability · Mathematics 2021-07-14 Christian Beck , Lukas Gonon , Martin Hutzenthaler , Arnulf Jentzen

Developing efficient and stable approximations for high dimensional PDEs is of key importance for numerous applications. The language of Forward-Backward Stochastic Differential Equations (FBSDE), with its nonlinear Feynman-Kac formula,…

Numerical Analysis · Mathematics 2017-08-11 Arnaud Lionnet , Gonçalos dos Reis , Lukasz Szpruch

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
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