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In this paper, we study ergodic backward stochastic differential equations (EBSDEs for short), for which the underlying diffusion is assumed to be multiplicative and of at most linear growth. The fact that the forward process has an…

Probability · Mathematics 2018-01-08 Ying Hu , Florian Lemonnier

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

In this paper we look at ergodic BSDEs in the case where the forward dynamics are given by the solution to a non-autonomous (time-periodic coefficients) Ornstein-Uhlenbeck SDE with L\'evy noise, taking values in a separable Hilbert space.…

Probability · Mathematics 2015-11-11 Samuel N. Cohen , Victor Fedyashov

The present paper is devoted to the study of the asymptotic behavior of the value functions of both finite and infinite horizon stochastic control problems and to the investigation of their relation with suitable stochastic ergodic control…

Probability · Mathematics 2018-04-06 Andrea Cosso , Giuseppina Guatteri , Gianmario Tessitore

This paper introduces a geometric method for proving ergodicity of degenerate noise driven stochastic processes. The driving noise is assumed to be an arbitrary Levy process with non-degenerate diffusion component (but that may be applied…

Probability · Mathematics 2008-04-10 Nawaf Bou-Rabee , Houman Owhadi

We consider ergodic backward stochastic differential equations, in a setting where noise is generated by a countable state uniformly ergodic Markov chain. We show that for Lipschitz drivers such that a comparison theorem holds, these…

Probability · Mathematics 2012-07-25 Samuel N. Cohen , Ying Hu

We establish the existence (and in an appropriate sense uniqueness) of Markovian solutions for ergodic BSDEs under a novel monotonicity condition. Our monotonicity condition allows us to prove existence even when the driver f has arbitrary…

Probability · Mathematics 2022-12-19 Joe Jackson , Gechun Liang

We analyze the long-time behavior of numerical schemes for a class of monotone stochastic partial differential equations (SPDEs) driven by multiplicative noise. By deriving several time-independent a priori estimates for the numerical…

Numerical Analysis · Mathematics 2025-01-27 Zhihui Liu

In this note we review several situations in which stochastic PDEs exhibit ergodic properties. We begin with the basic dissipative conditions, as stated by Da Prato and Zabczyk in their classical monograph. Then we describe the singular…

Probability · Mathematics 2024-12-05 Le Chen , Cheng Ouyang , Samy Tindel , Panqiu Xia

Being concerned with ergodicity of McKean--Vlasov SDEs, we establish a general result on exponential ergodicity in the $L^1$-Wasserstein distance. The result is successfully applied to non-degenerate and multiplicative Brownian motion…

Probability · Mathematics 2025-01-23 Xing Huang , Huaiqian Li , Liying Mu

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 study the ergodic behaviour of the McKean-Vlasov equations driven by common, divergence-free transport noise. In particular, we show that in dimension $d\geq 2$, if the noise is mixing and sufficiently strong it can enforce the…

Probability · Mathematics 2026-01-30 Benjamin Gess , Rishabh S. Gvalani , Adrian Martini

We study backward stochastic differential equations (BSDEs) for time-changed L\'evy noises when the time-change is independent of the L\'evy process. We prove existence and uniqueness of the solution and we obtain an explicit formula for…

Probability · Mathematics 2013-12-19 Giulia Di Nunno , Steffen Sjursen

This article deals with the numerical resolution of Markovian backward stochastic differential equations (BSDEs) with drivers of quadratic growth with respect to $z$ and bounded terminal conditions. We first show some bound estimates on the…

Probability · Mathematics 2012-01-10 Adrien Richou

The solutions of SDEs with multiplicative noise are not Markovian. On a coarse-grained time scale they still are, but only in the "anti-Ito" case. This allows a simple computation of the most likely path. Any density peak moves along such a…

General Physics · Physics 2021-09-27 Dietrich Ryter

We study a fairly general class of time-homogeneous stochastic evolutions driven by noises that are not white in time. As a consequence, the resulting processes do not have the Markov property. In this setting, we obtain constructive…

Probability · Mathematics 2009-02-12 M. Hairer

We study the ergodic properties of finite-dimensional systems of SDEs driven by non-degenerate additive fractional Brownian motion with arbitrary Hurst parameter $H\in(0,1)$. A general framework is constructed to make precise the notions of…

Probability · Mathematics 2007-05-23 Martin Hairer

We prove that the any Markov solution to the 3D stochastic Navier-Stokes equations driven by a mildly degenerate noise (i.e.all but finitely many Fourier modes are forced) is uniquely ergodic. This follows by proving strong Feller…

Probability · Mathematics 2009-12-10 Lihu Xu , Marco Romito

The irreducibility is fundamental for the study of ergodicity of stochastic dynamical systems. The existing methods on the irreducibility of stochastic partial differential equations (SPDEs) and stochastic differential equations (SDEs)…

Probability · Mathematics 2025-05-27 Jian Wang , Hao Yang , Jianliang Zhai , Tusheng Zhang

We study stochastic delay differential equations (SDDE) where the coefficients depend on the moving averages of the state process. As a first contribution, we provide sufficient conditions under which a linear path functional of the…

Probability · Mathematics 2013-10-17 Salvatore Federico , Peter Tankov
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