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We consider anticipative Stratonovich stochastic differential equations driven by some stochastic process (not necessarily a semi-martingale). No adaptedness of initial point or vector fields is assumed. Under a simple condition on the…

Probability · Mathematics 2007-05-23 Laure Coutin , Peter Friz , Nicolas Victoir

In the setting of stochastic Volterra equations, and in particular rough volatility models, we show that conditional expectations are the unique classical solutions to path-dependent PDEs. The latter arise from the functional It\^o formula…

Probability · Mathematics 2026-05-27 Ofelia Bonesini , Antoine Jacquier , Alexandre Pannier

We consider additive functionals of stationary Markov processes and show that under Kipnis-Varadhan type conditions they converge in rough path topology to a Stratonovich Brownian motion, with a correction to the Levy area that can be…

Probability · Mathematics 2019-12-23 Jean-Dominique Deuschel , Tal Orenshtein , Nicolas Perkowski

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

We pursue our investigations, initiated in [8], about stochastic integration with respect to the non-commutative fractional Brownian motion (NC-fBm). Our main objective in this paper is to compare the pathwise constructions of [8] with a…

Probability · Mathematics 2020-12-02 Aurélien Deya , René Schott

We develop efficient numerical integration methods for computing an integral whose integrand is a product of a smooth function and the Gaussian function with a small standard deviation. Traditional numerical integration methods applied to…

Numerical Analysis · Mathematics 2018-04-12 Yunyun Ma , Yuesheng Xu

In this article we study existence of pathwise stochastic integrals with respect to a general class of $n$-dimensional Gaussian processes and a wide class of adapted integrands. More precisely, we study integrands which are functions that…

Probability · Mathematics 2014-11-25 Zhe Chen , Lauri Viitasaari

Optimal sample path properties of stochastic processes often involve generalized H\"{o}lder- or variation norms. Following a classical result of Taylor, the exact variation of Brownian motion is measured in terms of $\psi (x) \equiv $…

Probability · Mathematics 2007-11-02 Peter Friz , Harald Oberhauser

Let $\tilde{N}\_{t}$ be a standard compensated Poisson process on $[0,1]$. We prove a new characterization of anticipating integrals of the Skorohod type with respect to $\tilde{N}$, and use it to obtain several counterparts to well…

Probability · Mathematics 2007-05-23 Giovanni Peccati , Ciprian A. Tudor

The purpose of this paper is to establish the convergence in law of the sequence of "midpoint" Riemann sums for a stochastic process of the form f'(W), where W is a Gaussian process whose covariance function satisfies some technical…

Probability · Mathematics 2013-07-26 Daniel Harnett , David Nualart

In the framework of vector measures and the combinatorial approach to stochastic multiple integral introduced by Rota and Wallstrom [Ann. Probab. 25 (1997) 1257--1283], we present an It\^{o} multiple integral and a Stratonovich multiple…

Probability · Mathematics 2010-11-11 Mercè Farré , Maria Jolis , Frederic Utzet

We derive a generalised It\=o formula for stochastic processes which are constructed by a convolution of a deterministic kernel with a centred L\'evy process. This formula has a unifying character in the sense that it contains the classical…

Probability · Mathematics 2015-03-03 Christian Bender , Robert Knobloch , Philip Oberacker

We develop a stochastic calculus for processes which are built by convoluting a pure jump, zero expectation L\'{e}vy process with a Volterra-type kernel. This class of processes contains, for example, fractional L\'{e}vy processes as…

Probability · Mathematics 2008-12-18 Christian Bender , Tina Marquardt

For any real-valued stochastic process $X$ with c\'rdl\'rg paths we define non-empty family of processes which have locally finite total variation, have jumps of the same order as the process $X$ and uniformly approximate its paths on…

Probability · Mathematics 2017-06-26 Rafał M. Łochowski

We consider stochastic differential equations of the form $dY_t=V(Y_t)\,dX_t+V_0(Y_t)\,dt$ driven by a multi-dimensional Gaussian process. Under the assumption that the vector fields $V_0$ and $V=(V_1,\ldots,V_d)$ satisfy H\"{o}rmander's…

Probability · Mathematics 2015-01-21 Thomas Cass , Martin Hairer , Christian Litterer , Samy Tindel

The solution of rough differential equation, driven by the It\^o signature of a continuous local martingale, exists uniquely a.s. when the vector field is Lip(\beta) for \beta > 1, and coincides a.s. with the It\^o signature of the solution…

Probability · Mathematics 2013-11-04 Terry J. Lyons , Danyu Yang

We treat a stochastic integration theory for a class of Hilbert-valued, volatility-modulated, conditionally Gaussian Volterra processes. We apply techniques from Malliavin calculus to define this stochastic integration as a sum of a…

Probability · Mathematics 2016-03-18 Fred Espen Benth , André Süß

Based on the recent development of the framework of Volterra rough paths, we consider here the probabilistic construction of the Volterra rough path associated to the fractional Brownian motion with $H>\frac{1}{2}$ and for the standard…

Probability · Mathematics 2022-02-11 Fabian Harang , Samy Tindel , Xiaohua Wang

We derive the optimal rate of convergence for the mean squared error at the terminal point for anticipating linear stochastic differential equations, where the integral is interpreted in Skorohod sense. Although alternative proof techniques…

Probability · Mathematics 2022-08-02 Peter Parczewski

We consider a rough differential equation of the form \(dY_t=\sum_i V_i(Y_t)d\boldsymbol{X}^i_t+V_0(Y_t)dt \), where \(\boldsymbol{X}_t \) is a Markovian rough path. We demonstrate that if the vector fields \((V_i)_{0\leq i\leq d} \)…

Probability · Mathematics 2022-02-03 Guang Yang