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In the present work, we establish the approximation of nonlinear stochastic partial differential equation (SPDE) driven by cylindrical {\alpha}-stable L\'evy processes via modulation or amplitude equations. We study SPDEs with a cubic…

Dynamical Systems · Mathematics 2021-06-30 Shenglan Yuan , Dirk Blömker

This paper advocates proximal Markov Chain Monte Carlo (ProxMCMC) as a flexible and general Bayesian inference framework for constrained or regularized estimation. Originally introduced in the Bayesian imaging literature, ProxMCMC employs…

Methodology · Statistics 2023-11-27 Xinkai Zhou , Qiang Heng , Eric C. Chi , Hua Zhou

We give new proofs of certain equivalent conditions for the existence of generalized moments of a L\'evy process $(X_t)_{t\geq 0}$; in particular, the existence of a generalized $g$-moment is equivalent to the uniform integrability of…

Probability · Mathematics 2022-02-21 David Berger , Franziska Kühn , René L. Schilling

In this work, we quantify the irregularity of a given cylindrical L\'evy process $L$ in $L^2({\mathbb R}^d)$ by determining the range of weighted Besov spaces $B$ in which $L$ has a regularised version $Y$, that is a stochastic process $Y$…

Probability · Mathematics 2024-09-24 Matthew Griffiths , Markus Riedle

In this paper, we establish a probabilistic representation as well as some integration by parts formulae for the marginal law at a given time maturity of some stochastic volatility model with unbounded drift. Relying on a perturbation…

Probability · Mathematics 2020-11-23 Junchao Chen , Noufel Frikha , Houzhi Li

In this paper asymptotic formulas are given for the Lebesgue constants generated by three special approximation processes related to the $\ell_1$-partial sums of Fourier series. In particular, we consider the Lagrange interpolation…

Classical Analysis and ODEs · Mathematics 2020-09-16 Yurii Kolomoitsev , Tetiana Lomako

A strong quasi-invariance principle and a finite-dimensional integration by parts formula as in the Bismut approach to Malliavin calculus are obtained through a suitable application of Lie's symmetry theory to autonomous stochastic…

Probability · Mathematics 2023-07-12 Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

Stochastic convergence of discrete time Markov processes has been analysed based on a dual Lyapunov approach. Using some existing results on ergodic theory of Markov processes, it has been shown that existence of a properly subinvariant…

Dynamical Systems · Mathematics 2024-02-20 Özkan Karabacak , Horia Cornean , Rafael Wisniewski

A general method is proposed which allows one to estimate drift and diffusion coefficients of a stochastic process governed by a Langevin equation. It extends a previously devised approach [R. Friedrich et al., Physics Letters A 271, 217…

Data Analysis, Statistics and Probability · Physics 2009-11-11 D. Kleinhans , R. Friedrich , A. Nawroth , J. Peinke

Continuous-time autoregressive moving average (CARMA) process driven by simple semi-L\'evy process has periodically correlated property with many potential application in finance. In this paper, we study on the estimation of the parameters…

Probability · Mathematics 2019-12-24 N. Modarresi , S. Rezakhah , M. Mohammadi

In order to solve tasks like uncertainty quantification or hypothesis tests in Bayesian imaging inverse problems, we often have to draw samples from the arising posterior distribution. For the usually log-concave but high-dimensional…

Computation · Statistics 2025-01-23 Matthias J. Ehrhardt , Lorenz Kuger , Carola-Bibiane Schönlieb

We show that for $\gamma<\sqrt{4/3}$, it is possible to define the Levy area of a planar Brownian motion with the Liouville measure of intermittency parameter $\gamma$ as the underlying area measure. We also consider the case of smoother…

Probability · Mathematics 2021-05-05 Isao Sauzedde

L\'{e}vy processes with completely monotone jumps appear frequently in various applications of probability. For example, all popular stock price models based on L\'{e}vy processes (such as the Variance Gamma, CGMY/KoBoL and Normal Inverse…

Probability · Mathematics 2016-01-08 Daniel Hackmann , Alexey Kuznetsov

In this paper we study rough differential equations driven by Gaussian rough paths from the viewpoint of Malliavin calculus. Under mild assumptions on coefficient vector fields and underlying Gaussian processes, we prove that solutions at a…

Probability · Mathematics 2014-06-09 Yuzuru Inahama

We study the weak approximation of the second-order backward SDEs (2BSDEs), when the continuous driving martingales are approximated by discrete time martingales. We establish a convergence result for a class of 2BSDEs, using both…

Probability · Mathematics 2015-09-10 Dylan Possamaï , Xiaolu Tan

The purpose of the present work is twofold. First, we develop the theory of general self-similar growth-fragmentation processes by focusing on martingales which appear naturally in this setting and by recasting classical results for…

Probability · Mathematics 2017-12-13 Jean Bertoin , Timothy Budd , Nicolas Curien , Igor Kortchemski

Through a regularization procedure, few approximation schemes of the local time of a large class of one dimensional processes are given. We mainly consider the local time of continuous semimartingales and reversible diffusions, and the…

Probability · Mathematics 2007-09-05 Blandine Berard Bergery , Pierre Vallois

The paper develops multiplicative compensation for complex-valued semimartingales and studies some of its consequences. It is shown that the stochastic exponential of any complex-valued semimartingale with independent increments becomes a…

Probability · Mathematics 2023-05-10 Aleš Černý , Johannes Ruf

Rough volatility models have recently been empirically shown to provide a good fit to historical volatility time series and implied volatility smiles of SPX options. They are continuous-time stochastic volatility models, whose volatility…

Mathematical Finance · Quantitative Finance 2021-11-01 Jingtang Ma , Wensheng Yang , Zhenyu Cui

In this paper we introduce a simple space-filtration discretization scheme on Wiener space which allows us to study weak decompositions and smooth explicit approximations for a large class of Wiener functionals. We show that any Wiener…

Probability · Mathematics 2013-07-23 Dorival Leão , Alberto Ohashi
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