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This paper contributes to the study of a new and remarkable family of stochastic processes that we will term class $\Sigma^{r}(H)$. This class is potentially interesting because it unifies the study of two known classes: the class…

This paper contributes to the study of stochastic processes of the class $(\Sigma)$. First, we extend the notion of the above-mentioned class to c\`adl\`ag semi-martingales, whose finite variational part is considered c\`adl\`ag instead of…

Probability · Mathematics 2020-08-27 Fulgence Eyi Obiang , Octave Moutsinga , Youssef Ouknine

In this paper we introduce the concept of conic martingales}. This class refers to stochastic processes having the martingale property, but that evolve within given (possibly time-dependent) boundaries. We first review some results about…

Probability · Mathematics 2016-03-25 Frédéric Vrins , Monique Jeanblanc

We discuss a class of Backward Stochastic Differential Equations(BSDEs) with no driving martingale. When the randomness of the driver depends on a general Markov process $X$, those BSDEs are denominated Markovian BSDEs and can be associated…

Probability · Mathematics 2017-12-29 Adrien Barrasso , Francesco Russo

In this paper, we contribute to the study of the class $(\Sigma)$. In the first part of the paper, we provide new ways to characterize stochastic processes of the above mentioned class and we derive some new properties. For instance, we…

Probability · Mathematics 2018-03-28 Fulgence Eyi Obiang , Octave Moutsinga , Youssef Youssef

We investigate the well-posedness of stochastic differential equations driven by fractional Brownian motion, focusing on the long-range dependent case $H \in (\frac{1}{2}, 1)$. While existing results on regularization by such noise…

Probability · Mathematics 2025-07-01 Maximilian Buthenhoff , Ercan Sönmez

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

Contributions of the present paper consist of two parts. In the first one, we contribute to the theory of stochastic calculus for signed measures. For instance, we provide some results permitting to characterize martingales and Brownian…

Probability · Mathematics 2019-08-28 Fulgence Eyi Obiang

Let us consider a signed measure $\Qv$ and a probability measure $\Pv$ such that $\Qv<<\Pv$. Let $D$ be the density of $\Qv$ with respect to $\Pv$. $H$ represents the set of zeros of $D$, $\bar{g}=0\vee\sup{H}$. In this paper, we shall…

Probability · Mathematics 2012-07-11 Fulgence Eyi Obiang , Youssef Ouknine , Octave Moutsinga

We present a new approach to noncommutative stochastic calculus that is, like the classical theory, based primarily on the martingale property. Using this approach, we introduce a general theory of stochastic integration and quadratic…

Operator Algebras · Mathematics 2025-10-28 David A. Jekel , Todd A. Kemp , Evangelos A. Nikitopoulos

In this note we prove that the local martingale part of a convex function f of a d-dimensional semimartingale X = M + A can be written in terms of an It^o stochastic integral \int H(X)dM, where H(x) is some particular measurable choice of…

Probability · Mathematics 2011-04-01 Nastasiya F Grinberg

In this paper we are concerned with backward stochastic differential equations with random default time and their applications to default risk. The equations are driven by Brownian motion as well as a mutually independent martingale…

Computational Finance · Quantitative Finance 2009-10-13 Shige Peng , Xiaoming Xu

In this paper, we study a class of backward stochastic Volterra integral equations driven by Teugels martingales associated with an independent L\'{e}vy process and an independent Brownian motion (BSVIELs). We prove the existence and…

Probability · Mathematics 2016-03-11 Wen Lu

In this article we study a class of singular stochastic differential equations driven by fractional Brownian motion with Hurst parameter H<1/2. The solution is constructed as the limit of a family of approximating processes, and its…

Probability · Mathematics 2026-04-14 Xiaoming Song , Alexander Tortoriello

We show that a substantial portion of stochastic calculus can be developed along similar lines to ordinary calculus, with derivative-based concepts driving the development. We define a notion of stopping derivative, which is a form of right…

Probability · Mathematics 2026-02-06 Alex Simpson

In this paper we study general nonlinear stochastic differential equations, where the usual Brownian motion is replaced by a L\'evy process. We also suppose that the coefficient multiplying the increments of this process is merely Lipschitz…

Probability · Mathematics 2007-07-19 Benjamin Jourdain , Sylvie Méléard , Wojbor Woyczynski

In this paper, we extend the results of Elliott and Yang \cite{elliott3} and discuss the control of a stochastic process for which the driving noise is provided by a martingale associated with a semi-Markov Chain. An existence and a…

Probability · Mathematics 2025-12-23 Robert J. Elliott , Zhe Yang

In this paper, we study linear backward stochastic differential equations driven by a class of centered Gaussian non-martingales, including fractional Brownian motion with Hurst parameter $H\in (0,1)\setminus \{\frac12\}$. We show that, for…

Probability · Mathematics 2016-01-20 Christian Bender , Lauri Viitasaari

Stochastic symmetries and related invariance properties of finite dimensional SDEs driven by general c\`adl\`ag semimartingales taking values in Lie groups are defined and investigated. In order to enlarge the class of possible symmetries…

Probability · Mathematics 2017-08-08 Sergio Albeverio , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

We consider a branching Brownian motion in $\mathbb{R}^d$. We prove that there exists a random subset $\Theta$ of $\mathbb{S}^{d-1}$ such that the limit of the derivative martingale exists simultaneously for all directions $\theta \in…

Probability · Mathematics 2020-11-20 Roman Stasiński , Julien Berestycki , Bastien Mallein
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