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We develop a novel stochastic derivative estimation framework for sample performance functions that are discontinuous in the parameter of interest, based on the multidimensional Leibniz integral rule. When discontinuities arise from…

Methodology · Statistics 2025-11-04 Xingyu Ren , Michael C. Fu , Pierre L'Ecuyer

In this paper we study the path-regularity and martingale properties of the set-valued stochastic integrals defined in our previous work Ararat et al. (2023). Such integrals have some fundamental differences from the well-known…

Probability · Mathematics 2023-08-28 Çağın Ararat , Jin Ma

In this note we prove an existence and uniqueness result for the solution of multidimensional stochastic delay differential equations with normal reflection. The equations are driven by a fractional Brownian motion with Hurst parameter…

Probability · Mathematics 2012-03-05 Mireia Besalú , Carles Rovira

This papers develops a stochastic integration theory with respect to volatility modulated L\'{e}vy-driven Volterra (VMLV) processes. It extends recent results in the literature to allow for stochastic volatility and pure jump processes in…

Probability · Mathematics 2012-05-16 Ole E. Barndorff-Nielsen , Fred Espen Benth , Jan Pedersen , Almut E. D. Veraart

In this work we develop and apply a path integral formulation for the microscopic degrees of freedom obeying stochastic differential equations to an active Brownian particle (ABP) trapped in a harmonic potential. The formalism allows to…

Soft Condensed Matter · Physics 2025-10-01 Carsten Littek , Mike Brandt , Falko Ziebert

In this paper we study the forward integral of operator-valued processes with respect to a cylindrical Brownian motion. In particular, we provide conditions under which the approximating sequence of processes of the forward integral,…

Probability · Mathematics 2014-08-29 Matthijs Pronk , Mark Veraar

In many applications that involve the inference of an unknown smooth function, the inference of its derivatives will often be just as important as that of the function itself. To make joint inferences of the function and its derivatives, a…

Methodology · Statistics 2023-02-07 Ziang Zhang , Alex Stringer , Patrick Brown , Jamie Stafford

This paper compares the results of applying a recently developed method of stochastic uncertainty quantification designed for fluid dynamics to the Born-Infeld model of nonlinear electromagnetism. The similarities in the results are…

Mathematical Physics · Physics 2019-01-15 Darryl D. Holm

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

Probability · Mathematics 2016-01-11 Feng-Yu Wang

In this work we show that it is possible to calculate the fractional integrals and derivatives of order $\alpha$ (using the Riemann-Liouville formulation) of power functions $\left( t-\ast\right) ^{\beta}$ with $\beta$ being any real value,…

Classical Analysis and ODEs · Mathematics 2018-11-30 Fabio Grangeiro Rodrigues , Edmundo Capelas de Oliveira

Motivated by fractional derivative models in viscoelasticity, a class of semilinear stochastic Volterra integro-differential equations, and their deterministic counterparts, are considered. A generalized exponential Euler method, named here…

Numerical Analysis · Mathematics 2020-01-17 Mihály Kovács , Stig Larsson , Fardin Saedpanah

In this paper we study set-valued Volterra-type stochastic integrals driven by L\'{e}vy processes. Upon extending the classical definitions of set-valued stochastic integral functionals to convoluted integrals with square-integrable…

Probability · Mathematics 2024-12-04 Weixuan Xia

In this paper, we study two variations of the time discrete Taylor schemes for rough differential equations and for stochastic differential equations driven by fractional Brownian motions. One is the incomplete Taylor scheme which excludes…

Probability · Mathematics 2015-10-30 Yaozhong Hu , Yanghui Liu , David Nualart

For backward stochastic Volterra integral equations (BSVIEs, for short), under some mild conditions, the so-called adapted solutions or adapted M-solutions uniquely exist. However, satisfactory regularity of the solutions is difficult to…

Probability · Mathematics 2018-02-13 Tianxiao Wang , Jiongmin Yong

Space-time regularity of linear stochastic partial differential equations is studied. The solution is defined in the mild sense in the state space $L^p$. The corresponding regularity is obtained by showing that the stochastic convolution…

Probability · Mathematics 2021-04-08 Petr Čoupek , Bohdan Maslowski , Martin Ondreját

We consider the oscillatory integrals with parameter-dependent phases. We decompose the integrals into a leading term and a remainder term. Instead of the pointwise estimate, we use some $L^p$-estimate for the remainder term and get various…

Classical Analysis and ODEs · Mathematics 2024-02-14 Zihua Guo

We consider the problem of estimating the roughness of the volatility process in a stochastic volatility model that arises as a nonlinear function of fractional Brownian motion with drift. To this end, we introduce a new estimator that…

Statistical Finance · Quantitative Finance 2026-04-17 Xiyue Han , Alexander Schied

We establish the higher differentiability of solutions to a class of obstacle problems for integral functionals where the convex integrand f satisfies p-growth conditions with respect to the gradient variable. We derive that the higher…

Analysis of PDEs · Mathematics 2023-05-25 Michele Caselli , Andrea Gentile , Raffaella Giova

Since integration by parts is an important tool when deriving energy or entropy estimates for differential equations, one may conjecture that some form of summation by parts (SBP) property is involved in provably stable numerical methods.…

Numerical Analysis · Mathematics 2021-03-12 Hendrik Ranocha , Jan Nordström

We survey recent developments in the field of complexity of pathwise approximation in $p$-th mean of the solution of a stochastic differential equation at the final time based on finitely many evaluations of the driving Brownian motion.…

Probability · Mathematics 2024-03-04 T. Müller-Gronbach , L. Yaroslavtseva
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