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In this paper we develop a stochastic integration theory for processes with values in a quasi-Banach space. The integrator is a cylindrical Brownian motion. The main results give sufficient conditions for stochastic integrability. They are…

Probability · Mathematics 2018-11-01 Petru A. Cioica-Licht , Sonja G. Cox , Mark C. Veraar

This paper provides an existence-and-uniqueness theorem characterizing the stochastic integral with respect to a Wiener process. The integral is represented as a mapping from the space of measurable and adapted pathwise locally integrable…

Probability · Mathematics 2018-12-27 Lars Tyge Nielsen

We develop a Fourier approach to rough path integration, based on the series decomposition of continuous functions in terms of Schauder functions. Our approach is rather elementary, the main ingredient being a simple commutator estimate,…

Probability · Mathematics 2014-10-16 Massimiliano Gubinelli , Peter Imkeller , Nicolas Perkowski

In the article, integration of temporal functions in (possibly non-UMD) Banach spaces with respect to (possibly non-Gaussian) fractional processes from a finite sum of Wiener chaoses is treated. The family of fractional processes that is…

Probability · Mathematics 2020-12-18 Petr Čoupek , Bohdan Maslowski , Martin Ondreját

The solution of a (stochastic) differential equation (SDE) can be locally approximated by a stochastic expansion, a linear combination of iterated integrals. Quantities of interest, like moments, can then be approximated with the expansion.…

Probability · Mathematics 2010-08-25 Christophe Ladroue

We present the Walsh theory of stochastic integrals with respect to martingale measures, alongside of the Da Prato and Zabczyk theory of stochastic integrals with respect to Hilbert-space-valued Wiener processes and some other approaches to…

Probability · Mathematics 2010-01-07 Robert C. Dalang , Lluis Quer-Sardanyons

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

The partial stochastic realization of periodic processes from finite covariance data has recently been solved by Lindquist and Picci based on convex optimization of a generalized entropy functional. The meaning and the role of this…

Methodology · Statistics 2016-09-30 Giorgio Picci , Bin Zhu

This paper provides a numerical approach for solving the linear stochastic Volterra integral equation using Walsh function approximation and the corresponding operational matrix of integration. A convergence analysis and error analysis of…

Numerical Analysis · Mathematics 2024-09-02 Prit Pritam Paikaray , Sanghamitra Beuria , Nigam Chandra Parida

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

We consider a method for the approximation of iterated stochastic integrals of arbitrary multiplicity $k$ $(k\in \mathbb{N})$ with respect to the infinite-dimensional $Q$-Wiener process using the mean-square approximation method of iterated…

General Mathematics · Mathematics 2022-03-15 Dmitriy F. Kuznetsov

The Feynman integral is given a stochastic interpretation in the framework of Nelson's stochastic mechanics employing a time-symmetric variant of Nelson's kinematics recently developed by the author.

Quantum Physics · Physics 2015-06-26 Michele Pavon

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

In this note, we present a new numerical method for solving backward stochastic differential equations. Our method can be viewed as an analogue of the classical finite element method solving deterministic partial differential equations.

Probability · Mathematics 2011-06-07 Penghui Wang , Xu Zhang

We study a (relativistic) Wiener process on a complexified (pseudo-)Riemannian manifold. Using Nelson's stochastic quantization procedure, we derive three equivalent descriptions for this problem. If the process has a purely real quadratic…

Mathematical Physics · Physics 2022-05-17 Folkert Kuipers

In this paper we investigate the well-posedness of backward or forward stochastic differential equations whose law is constrained to live in an a priori given (smooth enough) set and which is reflected along the corresponding ''normal''…

Probability · Mathematics 2019-03-05 Philippe Briand , Pierre Cardaliaguet , Paul-Éric Chaudru de Raynal , Ying Hu

We develop a general framework for pathwise stochastic integration that extends F\"ollmer's classical approach beyond gradient-type integrands and standard left-point Riemann sums and provides pathwise counterparts of It\^o, Stratonovich,…

Probability · Mathematics 2025-07-24 Purba Das , Anna P. Kwossek , David J. Prömel

We consider a mixed stochastic differential equation driven by possibly dependent fractional Brownian motion and Brownian motion. Under mild regularity assumptions on the coefficients, it is proved that the equation has a unique solution.

Probability · Mathematics 2011-11-09 Yuliya Mishura , Georgiy Shevchenko

In this paper, we combine Hida distribution theory and Sobolev-Watanabe-Kree spaces in order to study finely the link between forward integrals obtained by regularization and Wick-It\^o integrals with respect to fractional Brownian motion…

Probability · Mathematics 2017-01-03 Benjamin Arras

The paper studies stochastic integration with respect to Gaussian processes and fields. It is more convenient to work with a field than a process: by definition, a field is a collection of stochastic integrals for a class of deterministic…

Probability · Mathematics 2007-10-15 S. V. Lototsky , K. Stemmann