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Nicolas Victoir

Publications and source records attributed to Nicolas Victoir.

15 recordsLinked to original sources
arXiv2011

A note on higher dimensional $p$-variation

We discuss $p$-variation regularity of real-valued functions defined on $[0,T]^2$, based on rectangular increments. When $p>1$, there are two slightly different notions of $p$-variation; both of which are useful in the context of Gaussian rough paths. Unfortunately, these concepts were blurred in previous works; the purpose of this note is to show that the aforementioned notions of $p$-variations are "$ε$-close". In particular, all arguments relevant for Gaussian rough paths go through with minor notational changes.

math.PR↗
arXiv2007

Non-degeneracy of Wiener functionals arising from rough differential equations

Malliavin Calculus is about Sobolev-type regularity of functionals on Wiener space, the main example being the Ito map obtained by solving stochastic differential equations. Rough path analysis is about strong regularity of solution to (possibly stochastic) differential equations. We combine arguments of both theories and discuss existence of a density for solutions to stochastic differential equations driven by a general class of non-degenerate Gaussian processes, including processes with sample path regularity worse than Brownian motion.

math.PR↗
arXiv2007

Differential Equations Driven by Gaussian Signals II

Large classes of multi-dimensional Gaussian processes can be enhanced with stochastic Levy area(s). In a previous paper, we gave sufficient and essentially necessary conditions, only involving variational properties of the covariance. Following T. Lyons, the resulting lift to a "Gaussian rough path" gives a robust theory of (stochastic) differential equations driven by Gaussian signals with sample path regularity worse than Brownian motion. The purpose of this sequel paper is to establish convergence of Karhunen-Loeve approximations in rough path metrics. Particular care is necessary since martingale arguments are not enough to deal with third iterated integrals. An abstract support criterion for approximately continuous Wiener functionals then gives a description of the support of Gaussian rough paths as the closure of the (canonically lifted) Cameron-Martin space.

math.PR↗
arXiv2007

On Uniformly Subelliptic Operators and Stochastic Area

We consider uniformly subelliptic operators on certain unimodular Lie groups of polynomial growth. It was shown by Saloff-Coste and Stroock that classical results of De Giorgi, Nash, Moser, Aronson extend to this setting. It was then observed by Sturm that many proofs extend naturally to the setting of locally compact Dirichlet spaces. We relate these results to what is known as rough path theory by showing that they provide a natural and powerful analytic machinery for construction and study of (random) geometric Hoelder rough paths. (In particular, we obtain a simple construction of the Lyons-Stoica stochastic area for a diffusion process with uniformly elliptic generator in divergence form.) Our approach then enables us to establish a number of far-reaching generalizations of classical theorems in diffusion theory including Wong-Zakai approximations, Freidlin-Wentzell sample path large deviations and the Stroock-Varadhan support theorem. The latter was conjectured by T. Lyons in his recent St. Flour lecture.

math.PR↗
arXiv2007

Good rough path sequences and applications to anticipating stochastic calculus

We consider anticipative Stratonovich stochastic differential equations driven by some stochastic process lifted to a rough path. Neither adaptedness of initial point and vector fields nor commuting conditions between vector field is assumed. Under a simple condition on the stochastic process, we show that the unique solution of the above SDE understood in the rough path sense is actually a Stratonovich solution. We then show that this condition is satisfied by the Brownian motion. As application, we obtain rather flexible results such as support theorems, large deviation principles and Wong--Zakai approximations for SDEs driven by Brownian motion along anticipating vectorfields. In particular, this unifies many results on anticipative SDEs.

math.PR↗
arXiv2007

Differential Equations Driven by Gaussian Signals I

We consider multi-dimensional Gaussian processes and give a new condition on the covariance, simple and sharp, for the existence of stochastic area(s). Gaussian rough paths are constructed with a variety of weak and strong approximation results. Together with a new RKHS embedding, we obtain a powerful - yet conceptually simple - framework in which to analysize differential equations driven by Gaussian signals in the rough paths sense.

math.PR↗
arXiv2006

Large Deviation Principle for Enhanced Gaussian Processes

We study large deviation principles for Gaussian processes lifted to the free nilpotent group of step N. We apply this to a large class of Gaussian processes lifted to geometric rough paths. A large deviation principle for enhanced (fractional) Brownian motion, in Hoelder- or modulus topology, appears as special case.

math.PR↗
arXiv2006

The Burkholder-Davis-Gundy Inequality for Enhanced Martingales

Multi-dimensional continuous local martingales, enhanced with their stochastic area process, give rise to geometric rough paths with a.s. finite homogenous p-variation, p>2. Here we go one step further and establish quantitative bounds of the p-variation norm in the form of a BDG inequality. Our proofs are based on old ideas by Lepingle. We also discuss geodesic and piecewise linear approximations.

math.PR↗
arXiv2006

Weak approximation of stochastic differential equations and application to derivative pricing

The authors present a new simple algorithm to approximate weakly stochastic differential equations in the spirit of [1] and [2]. They apply it to the problem of pricing Asian options under the Heston stochastic volatility model, and compare it with other known methods. It is shown that the combination of the suggested algorithm and quasi-Monte Carlo methods makes computations extremely fast. [1] Shigeo Kusuoka, ``Approximation of Expectation of Diffusion Process and Mathematical Finance,'' Advanced Studies in Pure Mathematics, Proceedings of Final Taniguchi Symposium, Nara 1998 (T. Sunada, ed.), vol. 31 2001, pp. 147--165. [2] Terry Lyons and Nicolas Victoir, ``Cubature on Wiener Space,'' Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences 460 (2004), pp. 169--198.

math.PR↗
arXiv2006

Euler Estimates of Rough Differential Equations

We consider controlled differential equations and give new estimates for higher order Euler schemes. Our proofs are inspired by recent work of A. M. Davie who considers first and second order schemes. In order to implement the general case we make systematic use of geodesic approximations in the free nilpotent group. As application, we can control moments of solutions to rough path differential equations (RDEs) driven by random rough paths with sufficient integrability and have a criteria for L^q - convergence in the Universal Limit Theorem. We also obtain Azencott type estimates and asymptotic expansions for random RDE solution. When specialized to RDEs driven by Enhanced Brownian motion, we (mildly) improve classic estimates for diffusions in the small time limit.

math.CA↗
arXiv2005

A Variation Embedding Theorem and Applications

Fractional Sobolev spaces, also known as Besov or Slobodetzki spaces, arise in many areas of analysis, stochastic analysis in particular. We prove an embedding into certain q-variation spaces and discuss a few applications. First we show q-variation regularity of Cameron-Martin paths associated to fractional Brownian motion and other Volterra processes. This is useful, for instance, to establish large deviations for enhanced fractional Brownian motion. Second, the q-variation embedding, combined with results of rough path theory, provides a different route to a regularity result for stochastic differential equations by Kusuoka. Third, the embedding theorem works in a non-commutative setting and can be used to establish Hoelder/variation regularity of rough paths.

math.PR↗
arXiv2005

Good Rough Path Sequences and Applications to Anticipating & Fractional Stochastic Calculus

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 stochastic process, we show that the unique solution of the above SDE understood in the rough path sense is actually a Stratonovich solution. This condition is satisfied by the Brownian motion and the fractional Brownian motion with Hurst parameter greater than 1/4. As application, we obtain rather flexible results such as support theorems, large deviation principles and Wong-Zakai approximations for SDEs driven by fractional Brownian Motion along anticipating vectorfields. In particular, this unifies many results on anticipative SDEs.

math.PR↗
arXiv2004

A Note on the Notion of Geometric Rough Paths

We use simple sub-Riemannian techniques to prove that an arbitrary geometric p-rough path in the sense of Lyons (98) is the limit in sup-norm of a sequence of canonically lifted smooth paths, which are uniformly bounded in p-variation, clarifying the two different definitions of a geometric p-rough path, Lyons (98), Lyons/Qian (02). Our proofs are based on fine estimates in terms of control functions and are sufficiently general to include the case of Hoelder- and modulus-type regularity, Friz/Victoir (03). This allows us to extend a few classical results on Hoelder-spaces (Ciesielski, Musielak/Semadeni) and p-variation spaces (Wiener,Dudley) to the non-commutative setting necessary for the theory of rough paths.

math.FA↗
arXiv2003

Approximations of the Brownian Rough Path with Applications to Stochastic Analysis

A geometric p-rough path can be seen to be a genuine path of finite p-variation with values in a Lie group equipped with a natural distance. The group and its distance lift (R^{d},+,0) and its Euclidean distance. This approach allows us to easily get a precise modulus of continuity for the Enhanced Brownian Motion (the Brownian Motion and its Levy Area). As a first application, extending an idea due to Millet & Sanz-Sole, we characterize the support of the Enhanced Brownian Motion (without relying on correlation inequalities). Secondly, we prove Schilder's theorem for this Enhanced Brownian Motion. As all results apply in Hoelder (and stronger) topologies, this extends recent work by Ledoux, Qian, Zhang (2002). Lyons' fine estimates in terms of control functions allow us to show that the Ito map is still continuous in the topologies we introduced. This provides new and simplified proofs of the Stroock-Varadhan support theorem and the Freidlin-Wentzell theory. It also provides a short proof of modulus of continuity for diffusion processes along old results by Baldi.

math.PR↗