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 $(\Sigma)$ and the class $\mathcal{M}(H)$. In other words, we consider the stochastic processes $X$ which decompose as $X=m+v+A$, where $m$ is a local martingale, $v$ and $A$ are finite variation processes such that $dA$ is carried by $\{t\geq0:X_{t}=0\}$ and the support of $dv$ is $H$, the set of zeros of some continuous martingale $D$. First, we introduce a general framework. Thus, we provide some examples of elements of the new class and present some properties. Second, we provide a series of characterization r...
25 pagesWe study the notions of differentiating and non-differentiating sigma-fields in the general ...
This is a summary of the paper [FHS20]. The main result is the construction of bijections of the thr...
Realistic stochastic modeling is increasingly requiring the use of bounded noises. In this work, pro...
Stochastic processes are families of random variables; Lévy processes are families indexed by the po...
We propose a general framework for studying last passage times, suprema, and drawdowns of a large cl...
"This comprehensive guide to stochastic processes gives a complete overview of the theory and addres...
AbstractUsing the white noise space framework, we construct and study a class of Gaussian processes ...
In order to solve with a Monte Carlo method a parabolic (or elliptic) PDE with a transmission condit...
AbstractIn this paper, we consider the special class of positive local submartingales (Xt) of the fo...
This is a rigorous course on finite dimensional continuous Markov processes. Most top-ics covered wi...
International audienceIn this paper we introduce the concept of \textit{conic martingales}. This cla...
Le;vy processes form a wide and rich class of random process, and have many applications ranging fro...
Realistic stochastic modeling is increasingly requiring the use of bounded noises. In this work, pro...
We investigate a class of Hilbert space valued martingale-valued measures whose covariance structure...
We study Hilbert space valued Ornstein–Uhlenbeck processes (Y(t), t ≥ 0) which arise as weak solutio...
25 pagesWe study the notions of differentiating and non-differentiating sigma-fields in the general ...
This is a summary of the paper [FHS20]. The main result is the construction of bijections of the thr...
Realistic stochastic modeling is increasingly requiring the use of bounded noises. In this work, pro...
Stochastic processes are families of random variables; Lévy processes are families indexed by the po...
We propose a general framework for studying last passage times, suprema, and drawdowns of a large cl...
"This comprehensive guide to stochastic processes gives a complete overview of the theory and addres...
AbstractUsing the white noise space framework, we construct and study a class of Gaussian processes ...
In order to solve with a Monte Carlo method a parabolic (or elliptic) PDE with a transmission condit...
AbstractIn this paper, we consider the special class of positive local submartingales (Xt) of the fo...
This is a rigorous course on finite dimensional continuous Markov processes. Most top-ics covered wi...
International audienceIn this paper we introduce the concept of \textit{conic martingales}. This cla...
Le;vy processes form a wide and rich class of random process, and have many applications ranging fro...
Realistic stochastic modeling is increasingly requiring the use of bounded noises. In this work, pro...
We investigate a class of Hilbert space valued martingale-valued measures whose covariance structure...
We study Hilbert space valued Ornstein–Uhlenbeck processes (Y(t), t ≥ 0) which arise as weak solutio...
25 pagesWe study the notions of differentiating and non-differentiating sigma-fields in the general ...
This is a summary of the paper [FHS20]. The main result is the construction of bijections of the thr...
Realistic stochastic modeling is increasingly requiring the use of bounded noises. In this work, pro...