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We investigate the properties of the solutions of scaled Volterra equations (i.e. with an affine mean-reverting drift) in terms of stationarity at both a finite horizon and on the long run. In particular we prove that such an equation never…

Probability · Mathematics 2025-08-28 Gilles Pagès

In this work we study the smoothing effect of rough differential equations driven by a fractional Brownian motion with parameter $H>1/4$. The regularization estimates we obtain generalize to the fractional Brownian motion previous results…

Probability · Mathematics 2013-04-18 Fabrice Baudoin , Cheng Ouyang , Xuejing Zhang

We study solutions of a class of one-dimensional continuous reflected backward stochastic Volterra integral equations driven by Brownian motion, where the reflection keeps the solution above a given stochastic process (lower obstacle). We…

Probability · Mathematics 2020-04-27 Nacira Agram , Boualem Djehiche

This paper develops an It\^o-type fractional pathwise integration theory for fractional Brownian motion with Hurst parameters \( H \in (\frac{1}{3}, \frac{1}{2}] \), using the Lyons' rough path framework. This approach is designed to fill…

Probability · Mathematics 2025-11-10 Zhongmin Qian , Xingcheng Xu

This paper is devoted to the study of numerical approximation schemes for a class of parabolic equations on (0, 1) perturbed by a non-linear rough signal. It is the continuation of [8, 7], where the existence and uniqueness of a solution…

Probability · Mathematics 2016-03-01 Aurélien Deya

We survey existing results concerning the study in small times of the density of the solution of a rough differential equation driven by fractional Brownian motions. We also slightly improve existing results and discuss some possible…

Probability · Mathematics 2014-03-05 Fabrice Baudoin , Cheng Ouyang

A theory of differential equations driven by a non-differentiable path has recently been developed by Lyons. We develop an alternative approach to this theory, using (modified Euler approximations), and investigate its applicability to…

Probability · Mathematics 2007-10-04 A. M. Davie

In this paper stochastic Volterra equations admitting exponentially bounded resolvents are studied. After obtaining convergence of resolvents, some properties of stochastic convolutions are given. The paper provides a sufficient condition…

Probability · Mathematics 2011-11-09 Anna Karczewska , Carlos Lizama

The existence of weak solutions is established for stochastic Volterra equations with time-inhomogeneous coefficients allowing for general kernels in the drift and convolutional or bounded kernels in the diffusion term. The presented…

Probability · Mathematics 2023-11-21 David J. Prömel , David Scheffels

We study the regular conditional law of mixed Gaussian Volterra processes under the influence of model disturbances. More precisely, we study prediction of Gaussian Volterra processes driven by a Brownian motion in a case where the Brownian…

Probability · Mathematics 2019-04-23 Tommi Sottinen , Lauri Viitasaari

We develop a GMM approach for estimation of log-normal stochastic volatility models driven by a fractional Brownian motion with unrestricted Hurst exponent. We show that a parameter estimator based on the integrated variance is consistent…

Statistical Finance · Quantitative Finance 2026-01-16 Anine E. Bolko , Kim Christensen , Mikko S. Pakkanen , Bezirgen Veliyev

The $d$-dimensional fractional Brownian motion (FBM for short) $B_t=((B_t^{(1)},...,B_t^{(d)}),t\in\mathbb{R})$ with Hurst exponent $\alpha$, $\alpha\in(0,1)$, is a $d$-dimensional centered, self-similar Gaussian process with covariance…

Probability · Mathematics 2009-06-23 Jérémie Unterberger

We establish the existence of solutions to path-dependent rough differential equations with non-anticipative coefficients. Regularity assumptions on the coefficients are formulated in terms of horizontal and vertical derivatives.

Probability · Mathematics 2020-01-30 Anna Ananova

This paper deals with an extension of the so-called Black-Scholes model in which the volatility is modeled by a linear combination of the components of the solution of a differential equation driven by a fractional Brownian motion of Hurst…

Probability · Mathematics 2016-08-30 Nicolas Marie

In this paper, we consider the extended stochastic Navier-Stokes equations with Caputo derivative driven by fractional Brownian motion. We firstly derive the pathwise spatial and temporal regularity of the generalized Ornstein-Uhlenbeck…

Numerical Analysis · Mathematics 2017-09-18 Guang-an Zou , Guangying Lv , Jiang-Lun Wu

In this paper, we focus on the estimation of historical volatility of asset prices from high-frequency data. Stochastic volatility models pose a major statistical challenge: since in reality historical volatility is not observable, its…

Computational Finance · Quantitative Finance 2023-02-27 Camilla Damian , Rüdiger Frey

We consider a rough differential equation indexed by a small parameter $\varepsilon>0$. When the rough differential equation is driven by fractional Brownian motion with Hurst parameter $H$ ($1/4<H<1/2$), we prove the Laplace-type…

Probability · Mathematics 2013-02-05 Yuzuru Inahama

In this paper, we study two variations of the time discrete Taylor schemes for rough differential equations and for stochastic differential equations driven by fractional Brownian motions. One is the incomplete Taylor scheme which excludes…

Probability · Mathematics 2015-10-30 Yaozhong Hu , Yanghui Liu , David Nualart

We consider the problem of Hurst index estimation for solutions of stochastic differential equations driven by an additive fractional Brownian motion. Using techniques of the Malliavin calculus, we analyze the asymptotic behavior of the…

Probability · Mathematics 2019-03-07 Jan Gairing , Peter Imkeller , Radomyra Shevchenko , Ciprian A. Tudor

This paper is devoted to studying the averaging principle for fast-slow system of rough differential equations driven by mixed fractional Brownian rough path. The fast component is driven by Brownian motion, while the slow component is…

Probability · Mathematics 2023-03-15 Bin Pei , Yuzuru Inahama , Yong Xu
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