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We develop a theory of Hilbert-space valued stochastic integration with respect to cylindrical martingale-valued measures. As part of our construction, we expand the concept of quadratic variation, introduced by Veraar and Yaroslavtsev…

Probability · Mathematics 2025-06-17 Santiago Cambronero , David Campos , C. A. Fonseca-Mora , Darío Mena

In this paper we give necessary and sufficient conditions for a cylindrical continuous local martingale to be the stochastic integral with respect to a cylindrical Brownian motion. In particular we consider the class of cylindrical…

Probability · Mathematics 2018-11-07 Ivan S. Yaroslavtsev

In this paper we construct a theory of stochastic integration of processes with values in $\mathcal{L}(H,E)$, where $H$ is a separable Hilbert space and $E$ is a UMD Banach space (i.e., a space in which martingale differences are…

Probability · Mathematics 2007-08-22 J. M. A. M. van Neerven , M. C. Veraar , L. Weis

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 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

In this article we introduce cylindrical fractional Brownian motions in Banach spaces and develop the related stochastic integration theory. Here a cylindrical fractional Brownian motion is understood in the classical framework of…

Probability · Mathematics 2015-11-19 Elena Issoglio , Markus Riedle

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

Stochastic integrals are defined with respect to a collection $P = (P_i; \, i \in I)$ of continuous semimartingales, imposing no assumptions on the index set $I$ and the subspace of $\mathbb{R}^I$ where $P$ takes values. The integrals are…

Probability · Mathematics 2019-08-20 Constantinos Kardaras

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

In this work cylindrical Wiener processes on Banach spaces are defined by means of cylindrical stochastic processes, which are a well considered mathematical object. This approach allows a definition which is a simple straightforward…

Probability · Mathematics 2008-02-18 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

This paper is devoted to tangent martingales in Banach spaces. We provide the definition of tangency through local characteristics, basic $L^p$- and $\phi$-estimates, a precise construction of a decoupled tangent martingale, new estimates…

Probability · Mathematics 2020-09-22 Ivan S. Yaroslavtsev

Recently, a new approach in the fine analysis of stochastic processes sample paths has been developed to predict the evolution of the local regularity under (pseudo-)differential operators. In this paper, we study the sample paths of…

Probability · Mathematics 2013-08-29 Paul Balança , Erick Herbin

The purpose of this paper is to study certain set-valued integrals in UMD Banach spaces and provide a compatible form of the martingale representation theorem for set-valued martingales. Under specific conditions, these martingales can be…

Probability · Mathematics 2024-12-11 E. H. Essaky , M. Hassani , C. E. Rhazlane

This paper presents a brief survey of the theory of stochastic integration in Banach spaces. Expositions of the stochastic integrals in martingale type 2 spaces and UMD spaces are presented, as well as some applications of the latter to…

Probability · Mathematics 2014-05-28 Jan van Neerven , Mark Veraar , Lutz Weis

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

This article focuses on a new concept of quadratic variation for processes taking values in a Banach space $B$ and a corresponding covariation. This is more general than the classical one of M\'etivier and Pellaumail. Those notions are…

Probability · Mathematics 2013-08-02 Cristina Di Girolami , Giorgio Fabbri , Francesco Russo

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 paper we introduce a variant of Burkholder's martingale transform associated with two martingales with respect to different filtrations. Even though the classical martingale techniques cannot be applied, we show that the discussed…

Probability · Mathematics 2015-02-24 Vjekoslav Kovač , Kristina Ana Škreb

We provide a suitable framework for the concept of finite quadratic variation for processes with values in a separable Banach space $B$ using the language of stochastic calculus via regularizations, introduced in the case $B= \R$ by the…

Probability · Mathematics 2010-10-27 Cristina Di Girolami , Francesco Russo
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