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In this paper, we derive sufficient conditions for each component of the solution to a general backward stochastic differential equation to have a density for which upper and lower Gaussian estimates can be obtained.

Probability · Mathematics 2014-09-05 Omar Aboura , Solesne Bourguin

In this paper, we consider the Euler method for backward stochastic Volterra integral equations. First, we approximate the original equation by a family of backward stochastic equations (BSDEs, for short). Then we solve the BSDEs by the…

Numerical Analysis · Mathematics 2016-05-17 Yanqing Wang

In this paper we study ergodic backward stochastic differential equations (EBSDEs) dropping the strong dissipativity assumption needed in the previous work. In other words we do not need to require the uniform exponential decay of the…

Probability · Mathematics 2010-04-12 Arnaud Debussche , Ying Hu , Gianmario Tessitore

A new notion of stochastic transformation is proposed and applied to the study of both weak and strong symmetries of stochastic differential equations (SDEs). The correspondence between an algebra of weak symmetries for a given SDE and an…

Probability · Mathematics 2016-08-02 Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

We consider a class of multi-dimensional BSDEs on a finite time horizon (containing in particular Lipschitzian-quadratic BSDEs), whose terminal values are bounded as well as their corresponding Malliavin derivatives. We prove two results.…

Probability · Mathematics 2018-08-31 Shiqi Song

We present a theory of backward stochastic differential equations in continuous time with an arbitrary filtered probability space. No assumptions are made regarding the left continuity of the filtration, of the predictable quadratic…

Probability · Mathematics 2012-10-15 Samuel N. Cohen , Robert J. Elliott

We study one-dimensional stochastic integral equations with non-smooth dispersion coefficients, and with drift components that are not restricted to be absolutely continuous with respect to Lebesgue measure. In the spirit of Lamperti, Doss…

Probability · Mathematics 2016-02-04 Ioannis Karatzas , Johannes Ruf

Our study is dedicated to the probabilistic representation and numerical approximation of solutions to coupled systems of variational inequalities. The dynamics of each component of the solution is driven by a different linear parabolic…

Probability · Mathematics 2014-01-10 Romuald Elie , Idris Kharroubi

We represent an algorithm reducing the $(M+1)$-dimensional nonlinear partial differential equation (PDE) representable in the form of one-dimensional flow $u_t + w_{x_1}(u,u_{x},u_{xx},\dots)=0$, (where $w$ is an arbitrary local function of…

Exactly Solvable and Integrable Systems · Physics 2013-09-23 A. I. Zenchuk

We present a unified approach to $L^p$-solutions ($p > 1$) of multidimensional backward stochastic differential equations (BSDEs) driven by L\'evy processes and more general filtrations. New existence, uniqueness and comparison results are…

Probability · Mathematics 2020-11-03 Stefan Kremsner , Alexander Steinicke

The optimal stopping problem is one of the core problems in financial markets, with broad applications such as pricing American and Bermudan options. The deep BSDE method [Han, Jentzen and E, PNAS, 115(34):8505-8510, 2018] has shown great…

Probability · Mathematics 2023-08-28 Chengfan Gao , Siping Gao , Ruimeng Hu , Zimu Zhu

We introduce a class of backward stochastic differential equations (BSDEs) on the Wasserstein space of probability measures. This formulation extends the classical correspondence between BSDEs, stochastic control, and partial differential…

Probability · Mathematics 2025-07-01 Mao Fabrice Djete

We consider Backward Stochastic Differential Equations (BSDE) with generators that grow quadratically in the control variable. In a more abstract setting, we first allow both the terminal condition and the generator to depend on a vector…

Probability · Mathematics 2010-04-14 Stefan Ankirchner , Peter Imkeller , Goncalo Dos Reis

We perform scalable approximate inference in continuous-depth Bayesian neural networks. In this model class, uncertainty about separate weights in each layer gives hidden units that follow a stochastic differential equation. We demonstrate…

Machine Learning · Statistics 2022-02-01 Winnie Xu , Ricky T. Q. Chen , Xuechen Li , David Duvenaud

In this paper backward stochastic differential equations with interaction (shorter BSDEs with interaction) are introduced. Far to our knowledge, this type of equation is not seen in the literature before. Existence and uniqueness result for…

Probability · Mathematics 2022-12-29 Jasmina Đorđević , Andrey Dorogovtsev

In this paper, we continue in solving reflected generalized backward stochastic differential equations (RGBSDE for short) and fixed terminal time with use some new technical aspects of the stochastic calculus related to the reflected…

Probability · Mathematics 2009-07-14 Auguste Aman

We consider a backward stochastic differential equation with a generator that can be subjected to delay, in the sense that its current value depends on the weighted past values of the solutions, for instance a distorted recent average.…

Probability · Mathematics 2015-09-08 Peng Luo , Ludovic Tangpi

High-dimensional partial differential equations (PDEs) pose significant challenges for numerical computation due to the curse of dimensionality, which limits the applicability of traditional mesh-based methods. Since 2017, the Deep BSDE…

Numerical Analysis · Mathematics 2025-05-26 Jiequn Han , Arnulf Jentzen , Weinan E

The present paper is devoted to investigating the existence and uniqueness of solutions to a class of non-Lipschitz scalar valued backward stochastic differential equations driven by $G$-Brownian motion ($G$-BSDEs). In fact, when the…

Probability · Mathematics 2020-12-03 Falei Wang , Guoqiang Zheng

In this article, we deal with a multiple dimensional coupled Markovian BSDEs system with stochastic linear growth generators with respect to volatility processes. An existence result is provided by using approximation techniques.

Probability · Mathematics 2015-01-14 Rui Mu , Zhen Wu
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