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We define a fractional Ito stochastic integral with respect to a randomly scaled fractional Brownian motion via an $S$-transform approach. We investigate the properties of this stochastic integral, prove the Ito formula for functions of…

Probability · Mathematics 2026-03-05 Yana A. Butko , Merten Mlinarzik

In this work we study rough differential equations driven by a fractional Brownian motion with Hurst parameter H>1/4 and establish Varadhan's small time estimates for the density of solutions of such equations under Hormander's type…

Probability · Mathematics 2013-04-30 Fabrice Baudoin , Cheng Ouyang , Xuejing Zhang

The non-Markovian nature of rough volatility processes makes Monte Carlo methods challenging and it is in fact a major challenge to develop fast and accurate simulation algorithms. We provide an efficient one for stochastic Volterra…

Probability · Mathematics 2023-11-14 Blanka Horvath , Antoine Jacquier , Aitor Muguruza , Andreas Sojmark

We construct and study branching fractional Brownian motion with Hurst parameter $H\in(1/2,1)$. The construction relies on a generalization of the discrete approximation of fractional Brownian motion (Hammond and Sheffield, Probability…

Probability · Mathematics 2024-04-24 Adrián González Casanova , Jan Lukas Igelbrink

We study how to construct a stochastic process on a finite interval with given `roughness' and finite joint moments of marginal distributions. We first extend Ciesielski's isomorphism along a general sequence of partitions, and provide a…

Probability · Mathematics 2025-04-28 Erhan Bayraktar , Purba Das , Donghan Kim

In this paper we consider a n-dimensional stochastic differential equation driven by a fractional Brownian motion with Hurst parameter H>1/3. After solving this equation in a rather elementary way, following the approach of Gubinelli, we…

Probability · Mathematics 2013-10-24 Andreas Neuenkirch , Ivan Nourdin , Andreas Rößler , Samy Tindel

The well-posedness is investigated for distribution dependent stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H\in (\ff {\sq 5-1} 2,1)$ and distribution dependent multiplicative noise. To this…

Probability · Mathematics 2024-11-13 Xiliang Fan , Shao-Qin Zhang

We study statistical inference for small-noise-perturbed multiscale dynamical systems where the slow motion is driven by fractional Brownian motion. We develop statistical estimators for both the Hurst index as well as a vector of unknown…

Statistics Theory · Mathematics 2021-03-26 Solesne Bourguin , Siragan Gailus , Konstantinos Spiliopoulos

Sensitivity analysis w.r.t. the long-range/memory noise parameter for probability distributions of functionals of solutions to stochastic differential equations is an important stochastic modeling issue in many applications. In this paper…

Probability · Mathematics 2024-08-30 Alexandre Richard , Denis Talay

This paper begins by giving an historical context to fractional Brownian Motion and its development. Section 2 then introduces the fractional calculus, from the Riemann-Liouville perspective. In Section 3, we introduce Brownian motion and…

Probability · Mathematics 2014-01-14 Benjamin McGonegal

We derive an Ito-type change-of-variables formula for Volterra Gaussian processes (including fractional Brownian motion with any Hurst parameter), based on the operator factorization framework. The Ito correction is expressed as a Stieltjes…

Probability · Mathematics 2026-02-18 Ramiro Fontes

This paper is devoted to study a class of stochastic Volterra equations associated with fractional Brownian motion. We first prove the Driver type integration by parts formula and the shift Harnack type inequalities. As a direct…

Probability · Mathematics 2014-07-24 XiLiang Fan

Uncertainties are abundant in complex systems. Mathematical models for these systems thus contain random effects or noises. The models are often in the form of stochastic differential equations, with some parameters to be determined by…

Numerical Analysis · Mathematics 2015-03-13 Jiarui Yang , Jinqiao Duan

We study the anticipative backward stochastic differential equations (BSDEs, for short) driven by fractional Brownian motion with Hurst parameter H greater than 1/2. The stochastic integral used throughout the paper is the divergence…

Probability · Mathematics 2016-11-29 Jiaqiang Wen , Yufeng Shi

We derive estimates for the solutions to differential equations driven by a H\"older continuous function of order $\beta>1/2$. As an application we deduce the existence of moments for the solutions to stochastic partial differential…

Probability · Mathematics 2007-05-23 Yaozhong Hu David Nualart

In this study, we develop a new theory of estimating Hurst parame- ter using conic multivariate adaptive regression splines (CMARS) method. We concentrate on the strong solution of stochastic differentional equations (SDEs) driven by…

A stochastic calculus is given for processes described by stochastic integrals with respect to fractional Brownian motions and Rosenblatt processes somewhat analogous to the stochastic calculus for It\^{o} processes. These processes for…

Probability · Mathematics 2019-08-02 Petr Čoupek , Tyrone E. Duncan , Bozenna Pasik-Duncan

In [Han \& Schied, 2023, \textit{arXiv 2307.02582}], an easily computable scale-invariant estimator $\widehat{\mathscr{R}}^s_n$ was constructed to estimate the Hurst parameter of the drifted fractional Brownian motion $X$ from its…

Statistical Finance · Quantitative Finance 2025-09-09 Xiyue Han , Alexander Schied

In this article we study a class of singular stochastic differential equations driven by fractional Brownian motion with Hurst parameter H<1/2. The solution is constructed as the limit of a family of approximating processes, and its…

Probability · Mathematics 2026-04-14 Xiaoming Song , Alexander Tortoriello

We consider the problem of estimating the roughness of the volatility process in a stochastic volatility model that arises as a nonlinear function of fractional Brownian motion with drift. To this end, we introduce a new estimator that…

Statistical Finance · Quantitative Finance 2026-04-17 Xiyue Han , Alexander Schied