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Fractional Brownian motion is a non-Markovian Gaussian process indexed by the Hurst exponent $H\in [0,1]$, generalising standard Brownian motion to account for anomalous diffusion. Functionals of this process are important for practical…

Statistical Mechanics · Physics 2021-11-24 Tridib Sadhu , Kay Jörg Wiese

We study the Kardar-Parisi-Zhang equation on the half-line $x \geqslant 0$ with Neumann type boundary condition. Stationary measures of the KPZ dynamics were characterized in recent work: they depend on two parameters, the boundary…

Statistical Mechanics · Physics 2022-07-12 Guillaume Barraquand , Alexandre Krajenbrink , Pierre Le Doussal

In this paper, we study Bessel processes of dimension $\delta\equiv2(1-\mu)$, with $0<\delta<2$, and some related martingales and random times. Our approach is based on martingale techniques and the general theory of stochastic processes…

Probability · Mathematics 2011-11-09 Ashkan Nikeghbali

We propose a continuous time model for financial markets with proportional transactions costs and a continuum of risky assets. This is motivated by bond markets in which the continuum of assets corresponds to the continuum of possible…

Pricing of Securities · Quantitative Finance 2013-02-05 Bruno Bouchard , Emmanuel Lepinette , Erik Taflin

This article presents a weak law of large numbers and a central limit theorem for the scaled realised covariation of a bivariate Brownian semistationary process. The novelty of our results lies in the fact that we derive the suitable…

Probability · Mathematics 2017-07-27 Andrea Granelli , Almut E. D. Veraart

The linear fractional stable motion generalizes two prominent classes of stochastic processes, namely stable L\'evy processes, and fractional Brownian motion. For this reason it may be regarded as a basic building block for continuous time…

Statistics Theory · Mathematics 2022-08-17 Fabian Mies , Mark Podolskij

This paper studies quasi Bayesian estimation and uncertainty quantification for an unknown function that is identified by a nonparametric conditional moment restriction. We derive contraction rates for a class of Gaussian process priors.…

Econometrics · Economics 2023-11-08 Sid Kankanala

A semi-martingale reflecting Brownian motion is a popular process for diffusion approximations of queueing models including their networks. In this paper, we are concerned with the case that it lives on the nonnegative half-line, but the…

Probability · Mathematics 2024-08-13 Masakiyo Miyazawa

In this paper we find a pathwise decomposition of a certain class of Brownian semistationary processes ($\mathcal{BSS}$) in terms of fractional Brownian motions. To do this, we specialize in the case when the kernel of the $\mathcal{BSS}$…

Probability · Mathematics 2017-10-17 Orimar Sauri

In this paper we study the convergence to fractional Brownian motion for long memory time series having independent innovations with infinite second moment. For the sake of applications we derive the self-normalized version of this theorem.…

Methodology · Statistics 2016-11-25 Magda Peligrad , Hailin Sang

Approximations to sums of stationary and ergodic sequences by martingales are investigated. Necessary and sufficient conditions for such sums to be asymptotically normal conditionally given the past up to time 0 are obtained. It is first…

Probability · Mathematics 2007-05-23 Wei Biao Wu , Michael Woodroofe

A conditioned stochastic process can display a very different behavior from the unconditioned process. In particular, a conditioned process can exhibit non-Gaussian fluctuations even if the unconditioned process is Gaussian. In this work,…

Statistical Mechanics · Physics 2021-03-18 Tristan Gautié , Naftali R. Smith

A subordinate Brownian motion is a L\'evy process which can be obtained by replacing the time of the Brownian motion by an independent subordinator. The infinitesimal generator of a subordinate Brownian motion is $-\phi(-\Delta)$, where…

Probability · Mathematics 2014-02-26 Panki Kim , Renming Song , Zoran Vondracek

We introduce a variational theory for processes adapted to the multi-dimensional Brownian motion filtration. The theory provides a differential structure which describes the infinitesimal evolution of Wiener functionals at very small…

Probability · Mathematics 2017-07-13 Alberto Ohashi , Dorival Leão , Alexandre B. Simas

This paper contributes to the study of stochastic processes of the class $(\Sigma)$. First, we extend the notion of the above-mentioned class to c\`adl\`ag semi-martingales, whose finite variational part is considered c\`adl\`ag instead of…

Probability · Mathematics 2020-08-27 Fulgence Eyi Obiang , Octave Moutsinga , Youssef Ouknine

Starting from the seventies mathematicians face the question whether a non-negative local martingale is a true or a strict local martingale. In this article we answer this question from a semimartingale perspective. We connect the…

Probability · Mathematics 2016-06-10 David Criens , Kathrin Glau

We introduce a simulation scheme for Brownian semistationary processes, which is based on discretizing the stochastic integral representation of the process in the time domain. We assume that the kernel function of the process is regularly…

Probability · Mathematics 2018-09-24 Mikkel Bennedsen , Asger Lunde , Mikko S. Pakkanen

Inspired by Dai et al. [2023], we develop a novel multi-scaling asymptotic regime for semimartingale reflecting Brownian motion (SRBM). In this regime, we establish the steady-state convergence of SRBM to a product-form limit with…

Probability · Mathematics 2025-06-16 Jin Guang , Xinyun Chen , J. G. Dai , Peter W. Glynn

In this paper, we contribute to the study of the class $(\Sigma)$. In the first part of the paper, we provide new ways to characterize stochastic processes of the above mentioned class and we derive some new properties. For instance, we…

Probability · Mathematics 2018-03-28 Fulgence Eyi Obiang , Octave Moutsinga , Youssef Youssef

Statistically self-similar measures on $[0,1]$ are limit of multiplicative cascades of random weights distributed on the $b$-adic subintervals of $[0,1]$. These weights are i.i.d, positive, and of expectation $1/b$. We extend these cascades…

Probability · Mathematics 2009-02-18 Julien Barral , Benoit Mandelbrot