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In this work, we present a comprehensive theory of stochastic integration with respect to arbitrary cylindrical L\'evy processes in Hilbert spaces. Since cylindrical L\'evy processes do not enjoy a semi-martingale decomposition, our…

Probability · Mathematics 2024-03-18 Gergely Bodó , Markus Riedle

In this work, we introduce a theory of stochastic integration with respect to symmetric $\alpha$-stable cylindrical L\'evy processes. Since $\alpha$-stable cylindrical L\'evy processes do not enjoy a semi-martingale decomposition, our…

Probability · Mathematics 2022-11-21 Gergely Bodó , Markus Riedle

A cylindrical Levy process does not enjoy a cylindrical version of the semi-martingale decomposition which results in the need to develop a completely novel approach to stochastic integration. In this work, we introduce a stochastic…

Probability · Mathematics 2016-08-25 Adam Jakubowski , Markus Riedle

There are given sufficient conditions under which mixtures of dilations of L\'evy spectral measures, on a Hilbert space, are L\'evy measures again. We introduce some random integrals with respect to infinite dimensional L\'evy processes,…

Probability · Mathematics 2012-06-15 Zbigniew J. Jurek

We derive explicit integrability conditions for stochastic integrals taken over time and space driven by a random measure. Our main tool is a canonical decomposition of a random measure which extends the results from the purely temporal…

Probability · Mathematics 2016-08-11 Carsten Chong , Claudia Klüppelberg

In this work we introduce a theory of stochastic integration with respect to general cylindrical semimartingales defined on a locally convex space $\Phi$. Our construction of the stochastic integral is based on the theory of tensor products…

Probability · Mathematics 2021-12-06 C. A. Fonseca-Mora

We propose a method to construct the stochastic integral simultaneously under a non-dominated family of probability measures. Path-by-path, and without referring to a probability measure, we construct a sequence of Lebesgue-Stieltjes…

Probability · Mathematics 2012-06-21 Marcel Nutz

In this work we introduce a theory of stochastic integration for operator-valued integrands with respect to some classes of cylindrical martingale-valued measures in Hilbert spaces. The integral is constructed via the radonification of…

Probability · Mathematics 2021-12-06 A. E. Alvarado-Solano , C. A. Fonseca-Mora

In this paper, we present a comprehensive theory of generalized and weak generalized convolutions, illustrate it by a large number of examples, and discuss the related infinitely divisible distributions. We consider L\'{e}vy and additive…

Probability · Mathematics 2016-08-11 M. Borowiecka-Olszewska , B. H. Jasiulis-Gołdyn , J. K. Misiewicz , J. Rosiński

A distributional equation as a criterion for invariant measures of Markov processes associated to L\'evy-type operators is established. This is obtained via a characterization of infinitesimally invariant measures of the associated…

Probability · Mathematics 2022-08-17 Anita Behme , David Oechsler

For any real-valued stochastic process $X$ with c\'rdl\'rg paths we define non-empty family of processes which have locally finite total variation, have jumps of the same order as the process $X$ and uniformly approximate its paths on…

Probability · Mathematics 2017-06-26 Rafał M. Łochowski

The purpose of these notes is to distribute, mostly without proofs, fundamental definitions and results concerning the theory of semimartingales and stochastic integration. The material serves as a foundational guide for those interested in…

Probability · Mathematics 2025-01-03 Mark van den Bosch

Stochastic optimal control problems have a long tradition in applied probability, with the questions addressed being of high relevance in a multitude of fields. Even though theoretical solutions are well understood in many scenarios, their…

Statistics Theory · Mathematics 2024-05-28 Sören Christensen , Claudia Strauch , Lukas Trottner

This paper presents a continuous and discrete Lagrangian theory for stochastic Hamiltonian systems on manifolds. The main result is to derive stochastic governing equations for such systems from a critical point of a stochastic action.…

Probability · Mathematics 2009-06-02 Nawaf Bou-Rabee , Houman Owhadi

The aim of this paper is to present an elementary computable theory of probability, random variables and stochastic processes. The probability theory is baed on existing approaches using valuations and lower integrals. Various approaches to…

Probability · Mathematics 2015-10-14 Pieter Collins

We study the extremal behavior of a stochastic integral driven by a multivariate L\'{e}vy process that is regularly varying with index $\alpha>0$. For predictable integrands with a finite $(\alpha+\delta)$-moment, for some $\delta>0$, we…

Probability · Mathematics 2007-05-23 Henrik Hult , Filip Lindskog

Distributional properties -including Laplace transforms- of integrals of Markov processes received a lot of attention in the literature. In this paper, we complete existing results in several ways. First, we provide the analytical solution…

Probability · Mathematics 2016-05-09 Frédéric Vrins

We introduce a stochastic integral with respect to cylindrical L\'evy processes with finite $p$-th weak moment for $p\in [1,2]$. The space of integrands consists of $p$-summing operators between Banach spaces of martingale type $p$. We…

Probability · Mathematics 2019-12-10 Tomasz Kosmala , Markus Riedle

This paper develops a theory for completely random measures in the framework of free probability. A general existence result for free completely random measures is established, and in analogy to the classical work of Kingman it is proved…

Probability · Mathematics 2020-07-13 Francesca Collet , Fabrizio Leisen , Steen Thorbjørnsen

This papers develops a stochastic integration theory with respect to volatility modulated L\'{e}vy-driven Volterra (VMLV) processes. It extends recent results in the literature to allow for stochastic volatility and pure jump processes in…

Probability · Mathematics 2012-05-16 Ole E. Barndorff-Nielsen , Fred Espen Benth , Jan Pedersen , Almut E. D. Veraart
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