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In this paper, we first derive some explicit formulas for the computation of the n-th order divergence operator in Malliavin calculus in the one-dimensional case. We then extend these results to the case of isonormal Gaussian space. Our…

Probability · Mathematics 2020-05-26 S. Levental , P. Vellaisamy

In this paper, we use the Malliavin calculus techniques to obtain an anticipative version of the change of variable formula for L\'evy processes. Here the coefficients are in the domain of the anihilation (gradient) operator in the "future…

Probability · Mathematics 2008-08-04 Elisa Alòs , Jorge A. León , Josep Vives

In this paper, based on a known formula, we use a simple idea to get a new representation for the density of Malliavin differentiable random variables. This new representation is particularly useful for finding lower bounds for the density.

Probability · Mathematics 2019-12-23 Nguyen Tien Dung

Malliavin calculus is implemented in the context of [M. Hairer, A theory of regularity structures, Invent. Math. 2014]. This involves some constructions of independent interest, notably an extension of the structure which accomodates a…

Probability · Mathematics 2018-08-08 Giuseppe Cannizzaro , Peter K. Friz , Paul Gassiat

For any strictly positive martingale $S = \exp(X)$ for which $X$ has a characteristic function, we provide an expansion for the implied volatility. This expansion is explicit in the sense that it involves no integrals, but only polynomials…

Computational Finance · Quantitative Finance 2014-06-26 Antoine Jacquier , Matthew Lorig

In this paper we develop a Malliavin-Skorohod type calculus for additive processes in the $L^0$ and $L^1$ settings, extending the probabilistic interpretation of the Malliavin-Skorohod operators to this context. We prove calculus rules and…

Probability · Mathematics 2016-01-11 Giulia Di Nunno , Josep Vives

On any denumerable product of probability spaces, we construct a Malliavin gradient and then a divergence and a number operator. This yields a Dirichlet structure which can be shown to approach the usual structures for Poisson and Brownian…

Probability · Mathematics 2018-07-30 Laurent Decreusefond , Hélène Halconruy

In this paper we derive tractable formulae for price sensitivities of two-dimensional spread options using Malliavin calculus. In particular, we consider spread options with asset dynamics driven by geometric Brownian motion and stochastic…

Optimization and Control · Mathematics 2021-06-10 Farai Julius Mhlanga , Shadrack Makwena Kgomo

We investigate the existence of densities for finite-dimensional distributions of Hermite processes of order \(q \ge 1\) and self-similarity parameter \(H\in(\frac12,1)\). Whereas the Gaussian case \(q=1\) (fractional Brownian motion) is…

Probability · Mathematics 2025-09-26 Laurent Loosveldt , Yassine Nachit , Ivan Nourdin , Ciprian Tudor

We introduce a new method for analyzing midpoint discretizations of stochastic differential equations (SDEs), which are frequently used in Markov chain Monte Carlo (MCMC) methods for sampling from a target measure $\pi \propto \exp(-V)$.…

Numerical Analysis · Mathematics 2025-07-18 Matthew S. Zhang

In this paper we investigate the regularity properties of strong solutions to SDEs driven by L\'evy processes with irregular drift coefficients. Under some mild conditions, we show that the singular SDE has a unique strong solution for each…

Probability · Mathematics 2021-03-17 Guohuan Zhao

Let $\Omega\subset{\mathbb R}^n$ be bounded with a smooth boundary $\Gamma$ and let $S$ be the symmetric operator in $L^2(\Omega)$ given by the minimal realization of a second order elliptic differential operator. We give a complete…

Analysis of PDEs · Mathematics 2014-06-27 Andrea Posilicano

The stochastic partial differential equation analyzed in this work, is motivated by a simplified mesoscopic physical model for phase separation. It describes pattern formation due to adsorption and desorption mechanisms involved in surface…

Probability · Mathematics 2018-02-20 D. C. Antonopoulou , D. Farazakis , G. D. Karali

We describe a class of explicit invariant measures for both finite and infinite dimensional Stochastic Differential Equations (SDE) driven by L\'evy noise. We first discuss in details the finite dimensional case with a linear, resp. non…

Probability · Mathematics 2014-07-16 Sergio Albeverio , Luca Di Persio , Elisa Mastrogiacomo , Boubaker Smii

By using the Malliavin calculus and finite-jump approximations, the Driver-type integration by parts formula is established for the semigroup associated to stochastic differential equations with noises containing a subordinate Brownian…

Probability · Mathematics 2013-08-28 Feng-Yu Wang

We consider the incompressible, two dimensional Navier Stokes equation with periodic boundary conditions under the effect of an additive, white in time, stochastic forcing. Under mild restrictions on the geometry of the scales forced, we…

Probability · Mathematics 2007-05-23 Jonathan C. Mattingly , Etienne Pardoux

In this paper, we extend recent work on the functions that we call Bernstein-gamma to the class of bivariate Bernstein-gamma functions. In the more general bivariate setting, we determine Stirling-type asymptotic bounds which generalise,…

Probability · Mathematics 2019-07-19 Adam Barker , Mladen Savov

We show that if $p_-\geq 2$, then a sufficient condition for the density of smooth functions with compact support, in the variable exponent Sobolev space $W^{1,p(\cdot)}(\mathbb R^n)$, is that the Riesz potentials of compactly supported…

Functional Analysis · Mathematics 2015-07-14 Thanasis Kostopoulos , Nikos Yannakakis

In this paper we study the existence of a unique solution to a general class of Young delay differential equations driven by a H\"older continuous function with parameter greater that 1/2 via the Young integration setting. Then some…

Probability · Mathematics 2009-12-14 Jorge A. Leon , Samy Tindel

We prove limit theorems for functionals of a Poisson point process using the Malliavin calculus on the Poisson space. The target distribution is conditionally either a Gaussian vector or a Poisson random variable. The convergence is stable…

Probability · Mathematics 2024-06-21 Ronan Herry