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Our main result is the martingale representations for Markov additive processes where the modulator is a Levy process. These processes have three parts: the modulator, the jumps of the ordinate triggered by the modulator, and the…

Probability · Mathematics 2025-12-09 Celal Umut Yaran , Mine Çağlar

For a general Multidimensional L\'{e}vy process (satisfying some moment conditions), we introduce the Multidimensional power jump processes and the related Multidimensional Teugels martingales. Furthermore, we orthogonalize the…

Probability · Mathematics 2011-11-02 Jianzhong Lin

In the present paper, we study the chaotic representation property for certain families of square integrable martingales. For this purpose, we introduce the notion of compensated-covariation stability of such families. The chaotic…

Probability · Mathematics 2015-09-30 Paolo Di Tella , Hans-Jürgen Engelbert

An explicit formula for the chaotic representation of the powers of increments, (X_{t+t_0}-X_{t_0})^n, of a Levy process is presented. There are two different chaos expansions of a square integrable functional of a Levy process: one with…

Probability · Mathematics 2007-06-13 Wing Yan Yip , David Stephens , Sofia Olhede

We show the variational convergence of an irreversible Markov jump process describing a finite stochastic particle system to the solution of a countable infinite system of deterministic time-inhomogeneous quadratic differential equations…

Analysis of PDEs · Mathematics 2025-07-08 Jasper Hoeksema , Chun Yin Lam , André Schlichting

We consider a Markov jump process on a general state space to which we apply a time-dependent weak perturbation over a finite time interval. By martingale-based stochastic calculus, under a suitable exponential moment bound for the…

Probability · Mathematics 2024-05-14 Alessandra Faggionato , Vittoria Silvestri

Dunkl processes are martingales as well as c\`{a}dl\`{a}g homogeneous Markov processes taking values in $\mathbb{R}^d$ and they are naturally associated with a root system. In this paper we study the jumps of these processes, we describe…

Probability · Mathematics 2016-08-16 Léonard Gallardo , Marc Yor

The continuous-time random walk (CTRW) is a pure-jump stochastic process with several applications in physics, but also in insurance, finance and economics. A definition is given for a class of stochastic integrals driven by a CTRW, that…

Statistical Mechanics · Physics 2013-03-19 Guido Germano , Mauro Politi , Enrico Scalas , René L. Schilling

This paper concerns the Vertex Reinforced Jump Process (VRJP) and its representations as a Markov process in random environment. We show that all possible representations of the VRJP as a mixture of Markov processes can be expressed in a…

Probability · Mathematics 2019-03-26 Thomas Gerard

Starting from an iterative and hence numerically easily implementable representation of the thin set of jumps of a c\`{a}dl\`{a}g adapted stochastic process $X$ (including a few applications to the integration with respect to the jump…

Probability · Mathematics 2015-08-11 Frank Oertel

A well-known It\^o formula for finite dimensional processes, given in terms of stochastic integrals with respect to Wiener processes and Poisson random measures, is revisited and is revised. The revised formula, which corresponds to the…

Probability · Mathematics 2020-07-30 István Gyöngy , Sizhou Wu

We describe stochastic calculus in the context of processes that are driven by an adapted point process of locally finite intensity and are differentiable between jumps. This includes Markov chains as well as non-Markov processes. By…

Probability · Mathematics 2016-07-26 Eric Foxall

We consider a stochastic volatility model with jumps where the underlying asset price is driven by the process sum of a 2-dimensional Brownian motion and a 2-dimensional compensated Poisson process. The market is incomplete, resulting in…

Probability · Mathematics 2011-10-31 Youssef El-Khatib

Given a general It\^o semimartingale, its Markovian projection is an It\^o process, with Markovian differential characteristics, that matches the one-dimensional marginal laws of the original process. We construct Markovian projections for…

Probability · Mathematics 2024-03-26 Martin Larsson , Shukun Long

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

Let the process Y(t) be a Skorohod integral process with respect to Brownian motion. We use a recent result by Tudor (2004), to prove that Y(t) can be represented as the limit of linear combinations of processes that are products of forward…

Probability · Mathematics 2016-08-16 Giovanni Peccati , Michèle Thieullen , Ciprian A. Tudor

Markov jump processes are continuous-time stochastic processes with a wide range of applications in both natural and social sciences. Despite their widespread use, inference in these models is highly non-trivial and typically proceeds via…

Machine Learning · Computer Science 2023-06-01 Patrick Seifner , Ramses J. Sanchez

We consider a Markov process $X$ associated to a nonnecessarily symmetric Dirichlet form $\mathcal{E}$. We define a stochastic integral with respect to a class of additive functionals of zero quadratic variation and then we obtain an…

Probability · Mathematics 2013-12-18 Alexander Walsh

Piecewise-deterministic Markov processes form a general class of non-diffusion stochastic models that involve both deterministic trajectories and random jumps at random times. In this paper, we state a new characterization of the jump rate…

Methodology · Statistics 2017-05-03 Romain Azaïs , Alexandre Genadot

We study integral representations of random variables with respect to general H\"older continuous processes and with respect to two particular cases; fractional Brownian motion and mixed fractional Brownian motion. We prove that arbitrary…

Probability · Mathematics 2014-05-01 Georgiy Shevchenko , Lauri Viitasaari
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