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This paper contributes to the study of relative martingales. Specifically, for a closed random set $H$, they are processes null on $H$ which decompose as $M=m+v$, where $m$ is a c\`adl\`ag uniformly integrable martingale and, $v$ is a…

Probability · Mathematics 2022-10-04 Fulgence Eyi Obiang , Paule Joyce Mbenangoya , Ibrahima Faye , Octave Moutsinga

We develop a general method for extending Markov processes to a larger state space such that the added points form a polar set. The so obtained extension is an improvement on the standard trivial extension in which case the process is made…

Probability · Mathematics 2019-09-06 Lucian Beznea , Iulian Cîmpean , Michael Röckner

We produce uniform and decaying bounds in time for derivatives of the solution to the backwards Kolmogorov equation associated to a stochastic processes governed by a time dependent dynamics. These hold under assumptions over the…

Probability · Mathematics 2022-07-27 Maria Lefter , David Šiška , Łukasz Szpruch

In this paper we discuss existence and uniqueness for a one-dimensional time inhomogeneous stochastic differential equation directed by an $\mathbb{F}$-semimartingale $M$ and a finite cubic variation process $\xi$ which has the structure…

Probability · Mathematics 2007-05-23 Rosanna Coviello , Francesco Russo

Let $\mathfrak{z}$ be a stochastic exponential, i.e., $\mathfrak{z}_t=1+\int_0^t\mathfrak{z}_{s-}dM_s$, of a local martingale $M$ with jumps $\triangle M_t>-1$. Then $\mathfrak{z}$ is a nonnegative local martingale with $\E\mathfrak{z}_t\le…

Probability · Mathematics 2014-01-24 F. Klebaner , R. Liptser

We introduce a transform on the class of stochastic exponentials for d-dimensional Brownian motions. Each stochastic exponential generates another stochastic exponential under the transform. The new exponential process is often merely a…

Probability · Mathematics 2007-05-23 Victor Goodman

In this paper, we study reflected generalized backward doubly stochastic differential equations driven by Teugels martingales associated with L\'evy process (RGBDSDELs, in short) with one continuous barrier. Under uniformly Lipschitz…

Probability · Mathematics 2010-11-15 Auguste Aman

In this paper, we develop necessary and sufficient conditions for the validity of a martingale approximation for the partial sums of a stationary process in terms of the maximum of consecutive errors. Such an approximation is useful for…

Probability · Mathematics 2011-02-11 Mikhail Gordin , Magda Peligrad

We investigate aspects of semimartingale decompositions, approximation and the martingale representation for multidimensional correlated Markov processes. A new interpretation of the dependence among processes is given using the martingale…

Statistics Theory · Mathematics 2015-02-24 Antonio Dalessandro , Gareth W. Peters

In a preceding article, we have studied a generalization of the problem of finding a martingale on a manifold whose terminal value is known. This article completes the results obtained in the first article by providing uniqueness and…

Probability · Mathematics 2007-05-23 Fabrice Blache

The paper concerns itself with establishing large deviation principles for a sequence of stochastic integrals and stochastic differential equations driven by general semimartingales in infinite-dimensional settings. The class of…

Probability · Mathematics 2017-08-25 Arnab Ganguly

In this paper, we present a general framework for solving stochastic functional differential equations in infinite dimensions in the sense of martingale solutions, which can be applied to a large class of SPDE with finite delays, e.g.…

Probability · Mathematics 2014-07-25 Michael Rockner , Rongchan Zhu , Xiangchan Zhu

In this paper, a class of reflected generalized backward doubly stochastic differential equations (reflected GBDSDEs in short) driven by Teugels martingales associated with L\'{e}vy process and the integral with respect to an adapted…

Probability · Mathematics 2009-07-14 Auguste Aman

We address a class of backward stochastic differential equations on a bounded interval, where the driving noise is a marked, or multivariate, point process. Assuming that the jump times are totally inaccessible and a technical condition…

Probability · Mathematics 2016-06-28 Fulvia Confortola , Marco Fuhrman , Jean Jacod

We show stability and locality of the minimal supersolution of a forward backward stochastic differential equation with respect to the underlying forward process under weak assumptions on the generator. The forward process appears both in…

Probability · Mathematics 2016-06-13 Samuel Drapeau , Christoph Mainberger

The present paper is devoted to the study of backward stochastic differential equations with mean reflection formulated by Briand et al. [7]. We investigate the solvability of a generalized mean reflected BSDE, whose driver also depends on…

Probability · Mathematics 2022-11-03 Ying Hu , Remi Moreau , Falei Wang

In this paper we study backward stochastic differential equations (BSDEs) driven by the compensated random measure associated to a given pure jump Markov process X on a general state space K. We apply these results to prove well-posedness…

Probability · Mathematics 2013-02-05 Fulvia Confortola , Marco Fuhrman

In this paper, we obtain stability results for martingale representations in a very general framework. More specifically, we consider a sequence of martingales each adapted to its own filtration, and a sequence of random variables…

Probability · Mathematics 2022-06-06 Antonis Papapantoleon , Dylan Possamai , Alexandros Saplaouras

Motivated by applications to SPDEs we extend the It\^o formula for the square of the norm of a semimartingale $y(t)$ from Gy\"ongy and Krylov (Stochastics 6(3):153-173, 1982) to the case \begin{equation*} \sum_{i=1}^m \int_{(0,t]}…

Probability · Mathematics 2017-03-22 István Gyöngy , David Šiška

Linear fractional Galton-Watson branching processes in i.i.d.~random environment are, on the quenched level, intimately connected to random difference equations by the evolution of the random parameters of their linear fractional marginals.…

Probability · Mathematics 2021-10-01 Gerold Alsmeyer