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Let $X$ be a point process and let $\mathbb{X}$ denote the filtration generated by $X$. In this paper we study martingale representation theorems in the filtration $\mathbb{G}$ obtained as an initial and progressive enlargement of the…

Probability · Mathematics 2020-09-09 Paolo Di Tella , Monique Jeanblanc

We study the predictable representation property in the progressive enlargement F^\tau of a reference filtration F by a random time \tau. Our approach is based on the decomposition of any random time into two parts, one overlapping…

Probability · Mathematics 2024-06-21 Antonella Calzolari , Barbara Torti

Using results from our companion article [arXiv:1112.4824v2] on a Schauder approach to existence of solutions to a degenerate-parabolic partial differential equation, we solve three intertwined problems, motivated by probability theory and…

Probability · Mathematics 2016-04-08 Paul M. N. Feehan , Camelia Pop

A Brownian time process is a Markov process subordinated to the absolute value of an independent one-dimensional Brownian motion. Its transition densities solve an initial value problem involving the square of the generator of the original…

Probability · Mathematics 2009-06-25 Boris Baeumer , Mark M. Meerschaert , Erkan Nane

Martingale representation theorem for set-valued martingales was proposed by M. Kisielewicz [J. Math. Anal. Appl. 2014]. We shall prove that the result holds only for very special case: the set-valued martingale degenerates to the…

Probability · Mathematics 2020-12-15 Jinping Zhang , Kouji Yano

In this paper, by using a Taylor development type formula, we show how it is possible to associate differential operators with stochastic differential equations driven by a fractional Brownian motion. As an application, we deduce that…

Probability · Mathematics 2007-05-23 Fabrice Baudoin , Laure Coutin

Many applications require stochastic processes specified on two- or higher-dimensional domains; spatial or spatial-temporal modelling, for example. In these applications it is attractive, for conceptual simplicity and computational…

Statistics Theory · Mathematics 2017-02-21 Jonathan Rougier

We deal with complex spatial diffusion equations with time-fractional derivative and study their stochastic solutions. In particular, we complexify the integral operator solution to the heat-type equation where the time derivative is…

Probability · Mathematics 2021-12-20 Luisa Beghin , Alessandro De Gregorio

We construct a pathwise calculus for functionals of integer-valued measures and use it to derive an martingale representation formula with respect to a large class of integer-valued random measures. Using these results, we extend the…

Probability · Mathematics 2020-02-28 Pierre M. Blacque-Florentin , Rama Cont

The martingale part in the semimartingale decomposition of a Brownian motion with respect to an enlargement of its filtration, is an anticipative mapping of the given Brownian motion. In analogy to optimal transport theory, we define causal…

Probability · Mathematics 2017-12-13 Beatrice Acciaio , Julio Backhoff Veraguas , Anastasiia Zalashko

We introduce an elliptic extension of Dyson's Brownian motion model, which is a temporally inhomogeneous diffusion process of noncolliding particles defined on a circle. Using elliptic determinant evaluations related to the reduced affine…

Probability · Mathematics 2015-08-18 Makoto Katori

The cumulant generating function of time-averaged current is studied from an operational viewpoint. Specifically, for interacting Brownian particles under non-equilibrium conditions, we show that the first derivative of the cumulant…

Statistical Mechanics · Physics 2015-05-30 Takahiro Nemoto , Shin-ichi Sasa

In this paper we generalize a representation formula for the local time of a function of a semimartingale due to Coquet and Ouknine \cite{Ouknine} , our formula being a pointwise equality between two processes we show in addition that the…

Probability · Mathematics 2021-04-29 Anass Ben Taleb

We extend to quantum mechanics the technique of stochastic subordination, by means of which one can express any semi-martingale as a time-changed Brownian motion. As examples, we considered two versions of the q-deformed Harmonic oscillator…

High Energy Physics - Theory · Physics 2008-11-26 Claudio Albanese , Stephan Lawi

This paper is the first part of our survey on various results about the distribution of exponential type Brownian functionals defined as an integral over time of geometric Brownian motion. Several related topics are also mentioned.

Probability · Mathematics 2007-05-23 Hiroyuki Matsumoto , Marc Yor

In this paper we study dynamic backward problems, with the computation of conditional expectations as a main objective, in a framework where the (forward) state process satisfies a Volterra type SDE, with fractional Brownian motion as a…

Probability · Mathematics 2018-10-09 Frederi Viens , Jianfeng Zhang

We describe the classes of functions $f=(f(x), x\in R)$, for which processes $f(W_t)-Ef(W_t)$ and $f(W_t)/Ef(W_t)$ are martingales. We apply these results to give a martingale characterization of general solutions of the quadratic and the…

Probability · Mathematics 2021-08-17 M. Mania , R. Tevzadze

In this paper we extend the notion of ``filtration-consistent nonlinear expectation" (or "${\cal F}$-consistent nonlinear expectation") to the case when it is allowed to be dominated by a $g$-expectation that may have a quadratic growth. We…

Probability · Mathematics 2007-05-23 Ying Hu , Jin Ma , Shige Peng , Song Yao

We introduce polynomial processes taking values in an arbitrary Banach space $B$ via their infinitesimal generator $L$ and the associated martingale problem. We obtain two representations of the (conditional) moments in terms of solutions…

Probability · Mathematics 2019-11-11 Christa Cuchiero , Sara Svaluto-Ferro

In classical optimal transport, the contributions of Benamou-Brenier and McCann regarding the time-dependent version of the problem are cornerstones of the field and form the basis for a variety of applications in other mathematical areas.…

Probability · Mathematics 2019-01-16 Julio Backhoff-Veraguas , Mathias Beiglböck , Martin Huesmann , Sigrid Källblad