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Given a stochastic differential equation with path-dependent coefficients driven by a multidimensional Wiener process, we show that the support of the law of the solution is given by the image of the Cameron-Martin space under the flow of…

Probability · Mathematics 2019-09-05 Rama Cont , Alexander Kalinin

In this paper, we consider a complex-valued d-dimensional fractional Brownian motion defined on the closure of the complex upper half-plane, called analytic fractional Brownian motion. This process has been introduced by the second author…

Probability · Mathematics 2011-11-10 Samy Tindel , Jérémie Unterberger

We show that if a random variable is the final value of an adapted log-H\"{o}lder continuous process, then it can be represented as a stochastic integral with respect to a fractional Brownian motion with adapted integrand. In order to…

Probability · Mathematics 2015-10-08 Taras Shalaiko , Georgiy Shevchenko

Markov-modulated Brownian motion is a popular tool to model continuous-time phenomena in a stochastic context. The main quantity of interest is the invariant density, which satisfies a differential equation associated with the quadratic…

Probability · Mathematics 2016-05-06 Giang T. Nguyen , Federico Poloni

Despite the success of fractional Brownian motion (fBm) in modeling systems that exhibit anomalous diffusion due to temporal correlations, recent experimental and theoretical studies highlight the necessity for a more comprehensive approach…

Statistical Mechanics · Physics 2024-07-02 Adrian Pacheco-Pozo , Diego Krapf

We propose a new algorithm to generate a fractional Brownian motion, with a given Hurst parameter, 1/2<H<1 using the correlated Bernoulli random variables with parameter p; having a certain density. This density is constructed using the…

Computation · Statistics 2019-05-15 Buket Coskun , Ceren Vardar-Acar , Hakan Demirtas

A systematic procedure is proposed for deriving all the gauge symmetries of the general, not necessarily variational, equations of motion. For the variational equations, this procedure reduces to the Dirac-Bergmann algorithm for the…

Mathematical Physics · Physics 2015-05-13 S. L. Lyakhovich , A. A. Sharapov

The purpose of this paper is to provide a more general Cameron-Storvick theorem for the generalized analytic Feynman integral associated with Gaussian process $\mathcal Z_k$ on a very general Wiener space $C_{a,b}[0,T]$. The general Wiener…

Probability · Mathematics 2021-04-19 Jae Gil Choi

Fractional Brownian motion (fBm) is an experimentally-relevant, non-Markovian Gaussian stochastic process with long-ranged correlations between the increments, parametrised by the so-called Hurst exponent $H$; depending on its value the…

Statistical Mechanics · Physics 2023-10-04 O. Benichou , G. Oshanin

Let R be a symmetric a-stable Riemann-Liouville process with Hurst parameter H > 0. Consider ||.|| a translation invariant, b-self-similar, and p-pseudo-additive functional semi-norm. We show that if H > (b + 1/p) and c = (H - b - 1/p),…

Probability · Mathematics 2015-06-26 Mikhail. A. Lifshits , Thomas Simon

The Wiener's path integral plays a central role in the studies of Brownian motion. Here we derive exact path-integral representations for the more general \emph{fractional} Brownian motion (fBm) and for its time derivative process -- the…

Statistical Mechanics · Physics 2022-12-28 Baruch Meerson , Olivier Bénichou , Gleb Oshanin

This paper gives a brief introduction to some important fractional and multifractional Gaussian processes commonly used in modelling natural phenomena and man-made systems. The processes include fractional Brownian motion (both standard and…

Mathematical Physics · Physics 2014-07-01 S. C. Lim , C. H. Eab

We show that a pathwise stochastic integral with respect to fractional Brownian motion with an adapted integrand $g$ can have any prescribed distribution, moreover, we give both necessary and sufficient conditions when random variables can…

Probability · Mathematics 2013-03-22 Yuliya Mishura , Georgiy Shevchenko , Esko Valkeila

The purpose of this paper is to study the convergence in distribution of two subsequences of the signed cubic variation of the fractional Brownian motion with Hurst parameter $H=1/6$. We prove that, under some conditions on both…

Probability · Mathematics 2012-10-05 Krzysztof Burdzy , David Nualart , Jason Swanson

We consider equidistant approximations of stochastic integrals driven by H\"older continuous Gaussian processes of order $H>\frac12$ with discontinuous integrands involving bounded variation functions. We give exact rate of convergence in…

Probability · Mathematics 2022-09-15 Ehsan Azmoodeh , Pauliina Ilmonen , Nourhan Shafik , Tommi Sottinen , Lauri Viitasaari

We extend to the vector-valued situation some earlier work of Ciesielski and Roynette on the Besov regularity of the paths of the classical Brownian motion. We also consider a Brownian motion as a Besov space valued random variable. It…

Probability · Mathematics 2008-01-21 Tuomas Hytonen , Mark Veraar

We propose discrete random-field models that are based on random partitions of $\mathbb{N}^2$. The covariance structure of each random field is determined by the underlying random partition. Functional central limit theorems are established…

Probability · Mathematics 2018-02-13 Olivier Durieu , Yizao Wang

The stochastic rotational invariance of an integration by parts formula inspired by the Bismut approach to Malliavin calculus is proved in the framework of the Lie symmetry theory of stochastic differential equations. The non-trivial effect…

Probability · Mathematics 2025-06-16 Susanna Dehò , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

We study the two-dimensional fractional Brownian motion with Hurst parameter $H>{1/2}$. In particular, we show, using stochastic calculus, that this process admits a skew-product decomposition and deduce from this representation some…

Probability · Mathematics 2007-05-23 Fabrice Baudoin , David Nualart

We consider continuous-time diffusion models driven by fractional Brownian motion. Observations are assumed to possess a non-trivial likelihood given the latent path. Due to the non-Markovianity and high-dimensionality of the latent paths,…

Methodology · Statistics 2015-03-25 Alexandros Beskos , Joseph Dureau , Konstantinos Kalogeropoulos
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