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Consider stochastic functional differential equations, whose coefficients depend on past histories. The solution determines a non-Markov process. In the present paper, we shall obtain the existence of smooth densities for joint…

Probability · Mathematics 2016-01-07 Atsushi Takeuchi

We close an unexpected gap in the literature of stochastic differential equations (SDEs) with drifts of super linear growth (and random coefficients), namely, we prove Malliavin and Parametric Differentiability of such SDEs. The former is…

Probability · Mathematics 2021-10-05 Peter Imkeller , Gonçalo dos Reis , William Salkeld

We consider a one-dimensional Stochastic Differential Equation with reflection where we allow the drift to be merely bounded and measurable. It is already known that such equations have a unique strong solution. Recently, it has been shown…

Probability · Mathematics 2014-10-03 Torstein Nilssen , Tusheng Zhang

We study Malliavin differentiability for the solutions of a stochastic differential equation with drift of super-linear growth. Assuming we have a monotone drift with polynomial growth, we prove Malliavin differentiability of any order. As…

Probability · Mathematics 2024-05-31 Cristina Anton

The aim of this paper is to develop estimation and inference methods for the drift parameters of multivariate L\'evy-driven continuous-time autoregressive processes of order $p\in\mathbb{N}$. Starting from a continuous-time observation of…

Methodology · Statistics 2023-07-26 Lorenzo Lucchese , Mikko S. Pakkanen , Almut E. D. Veraart

This paper deals with the problems of consistence and strong consistence of the maximum likelihood estimators of the mean and variance of the drift fractional Brownian motions observed at discrete time instants. A central limit theorem for…

Statistics Theory · Mathematics 2009-04-28 Hu Yaozhong , Xiao Weilin , Zhang Weiguo

In this work we present a condition for the regularity, in both space and Malliavin sense, of strong solutions to SDEs driven by Brownian motion. We conjecture that this condition is optimal. As a consequence, we are able to improve the…

Probability · Mathematics 2015-09-11 David Banos , Torstein Nilssen

By using Malliavin calculus, explicit derivative formulae are established for a class of semi-linear functional stochastic partial differential equations with additive or multiplicative noise. As applications, gradient estimates and Harnack…

Probability · Mathematics 2011-10-25 Jianhai Bao , Feng-Yu Wang , Chenggui Yuan

For a class of piecewise deterministic Markov processes we introduce a stochastic calculus which is a certain non-Gaussian counterpart to the classical Malliavin calculus. As an application we investigate the regularity of densities of…

Probability · Mathematics 2023-06-21 Jörg-Uwe Löbus

This paper presents a novel generic asymptotic expansion formula of expectations of multidimensional Wiener functionals through a Malliavin calculus technique. The uniform estimate of the asymptotic expansion is shown under a weaker…

Probability · Mathematics 2024-12-24 Akihiko Takahashi , Toshihiro Yamada

On any denumerable product of probability spaces, we extend the discrete Malliavin structure for conditionally independent random variables. As a consequence, we obtain the chaos decomposition for functionals of conditionally independent…

Probability · Mathematics 2024-04-08 Laurent Decreusefond , Christophe Vuong

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

For a difference approximations of multidimensional diffusion, the truncated local limit theorem is proved. Under very mild conditions on the distribution of the difference terms, this theorem provides that the transition probabilities of…

Probability · Mathematics 2008-01-16 Alexey M. Kulik

The complex Langevin method (CLM) provides a promising way to perform the path integral with a complex action using a stochastic equation for complexified dynamical variables. It is known, however, that the method gives wrong results in…

High Energy Physics - Lattice · Physics 2016-12-01 Shinji Shimasaki , Keitaro Nagata , Jun Nishimura

A novel discretization is presented for forward-backward stochastic differential equations (FBSDE) with differentiable coefficients, simultaneously solving the BSDE and its Malliavin sensitivity problem. The control process is estimated by…

Numerical Analysis · Mathematics 2021-10-12 Balint Negyesi , Kristoffer Andersson , Cornelis W. Oosterlee

Suppose $B$ is a Brownian motion and $B^n$ is an approximating sequence of rescaled random walks on the same probability space converging to $B$ pointwise in probability. We provide necessary and sufficient conditions for weak and strong…

Probability · Mathematics 2016-03-01 Christian Bender , Peter Parczewski

We develop a technique based on Malliavin-Bismut calculus ideas, for asymptotic expansion of dual control problems arising in connection with exponential indifference valuation of claims, and with minimisation of relative entropy, in…

Pricing of Securities · Quantitative Finance 2013-10-15 Michael Monoyios

We consider versions of Malliavin calculus on path spaces of compact manifolds with diffusion measures, defining Gross-Sobolev spaces of differentiable functions and proving their intertwining with solution maps, I, of certain stochastic…

Probability · Mathematics 2016-11-14 K. D. Elworthy , Xue-Mei Li

Based on Malliavin calculus tools and approximation results, we show how to compute a maximum likelihood type estimator for a rather general differential equation driven by a fractional Brownian motion with Hurst parameter H>1/2. Rates of…

Probability · Mathematics 2013-08-05 Alexandra Chronopoulou , Samy Tindel

By using the Malliavin calculus, the Driver-type integration by parts formula is established for the semigroup associated to to SPDEs with Multiplicative Noise. Moreover, estimates on the density of heat kernel w.r.t. Lebesgue measure are…

Probability · Mathematics 2016-10-11 Xing Huang , Shao-Qin Zhang , Li-Xia Liu
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