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Dzhaparidze and Spreij [5] showed that the quadratic variation of a semimartingale can be approximated using a randomized periodogram. We show that the same approximation is valid for a special class of continuous stochastic processes. This…

Probability · Mathematics 2012-03-07 Ehsan Azmoodeh , Esko Valkeila

This article gives an account on various aspects of stochastic calculus in the plane. Specifically, our aim is 3-fold: (i) Derive a pathwise change of variable formula for a path indexed by a square, satisfying some H\"older regularity…

Probability · Mathematics 2013-09-26 Khalil Chouk , Samy Tindel

We introduce a stochastic partial differential equation (SPDE) with elliptic operator in divergence form, with measurable and bounded coefficients and driven by space-time white noise. Such SPDEs could be used in mathematical modelling of…

Probability · Mathematics 2020-01-09 Mounir Zili , Eya Zougar

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…

Probability · Mathematics 2007-05-23 Peter Friz , Nicolas Victoir

In this paper we present a variant of the well known Skorokhod Representation Theorem. In our main result, given $S$ a Polish space, to a given continous path $\alpha$ in the space of probability measures on $S$, we associate a continuous…

Probability · Mathematics 2007-05-23 Jean Cortissoz

We derive a functional change of variable formula for {\it non-anticipative} functionals defined on the space of right continuous paths with left limits. The functional is only required to possess certain directional derivatives, which may…

Probability · Mathematics 2010-04-09 Rama Cont , David-Antoine Fournie

Various functional limit theorems for partial sum processes of strictly stationary sequences of regularly varying random variables in the space of cadlag functions $D[0,1]$ with one of the Skorohod topologies have already been obtained. The…

Probability · Mathematics 2014-07-23 Danijel Krizmanic

We derive functional convergence of the partial maxima stochastic processes of multivariate linear processes with weakly dependent heavy-tailed innovations and random coefficients. The convergence takes place in the space of…

Probability · Mathematics 2024-07-23 Danijel Krizmanic

To a coarse structure we associate a Grothendieck topology which is determined by coarse covers. A coarse map between coarse spaces gives rise to a morphism of Grothendieck topologies. This way we define sheaves and sheaf cohomology on…

Algebraic Geometry · Mathematics 2022-03-24 Elisa Hartmann

We consider a stochastic partial differential equation with piecewise constant coefficients driven by a multiplicative space-time white noise. The existence and uniqueness of the mild solution in Walsh sense is established. We mainly study…

Probability · Mathematics 2025-11-18 Yongkang Li , Huisheng Shu , Litan Yan

A geometric setup for constrained variational calculus is presented. The analysis deals with the study of the extremals of an action functional defined on piecewise differentiable curves, subject to differentiable, non-holonomic…

Mathematical Physics · Physics 2015-05-08 Enrico Massa , Danilo Bruno , Gianvittorio Luria , Enrico Pagani

We construct a pathwise integration theory, associated with a change of variable formula, for smooth functionals of continuous paths with arbitrary regularity defined in terms of the notion of $p$-th variation along a sequence of time…

Probability · Mathematics 2019-05-07 Rama Cont , Nicolas Perkowski

The study of stochastic variational principles involves the problem of constructing fixed-endpoint and adapted variations of semimartingales. We provide a detailed construction of variations of semimartingales that are not only fixed at…

Mathematical Physics · Physics 2025-09-11 Archishman Saha

We study the variational structure of the discrete Kadomtsev-Petviashvili (dKP) equation by means of its pluri-Lagrangian formulation. We consider the dKP equation and its variational formulation on the cubic lattice ${\mathbb Z}^{N}$ as…

Mathematical Physics · Physics 2019-11-11 Raphael Boll , Matteo Petrera , Yuri B. Suris

We study homological invariants of smooth families of real quadratic forms as a step towards a "Lagrange multipliers rule in the large" that intends to describe topology of smooth maps in terms of scalar Lagrange functions.

Algebraic Topology · Mathematics 2014-12-16 Andrei Agrachev

This paper extends the results of Ma, Wu, Zhang, Zhang [11] to the context of path-dependent multidimensional forward-backward stochastic differential equations (FBSDE). By path-dependent we mean that the coefficients of the…

Probability · Mathematics 2022-01-14 Kaitong Hu , Zhenjie Ren , Nizar Touzi

The normalised partial sums of values of a nonnegative multiplicative function over divisors with appropriately restricted sizes of a random permutation from the symmetric group define trajectories of a stochastic process. We prove a…

Probability · Mathematics 2026-01-14 Eugenijus Manstavičius

This article characterizes conjugates and subdifferentials of convex integral functionals over linear spaces of cadlag stochastic processes. The approach is based on new measurability results on the Skorokhod space and new interchange rules…

Optimization and Control · Mathematics 2018-12-12 Ari-Pekka Perkkiö , Erick Treviño-Aguilar

We give tightness criteria for random variables taking values in the space of all compact sets of cadlag real-valued paths, in terms of both the Skorohod J1 and M1 topologies. This extends earlier work motivated by the study of the Brownian…

Probability · Mathematics 2026-05-01 Nic Freeman , Jan M. Swart

We use the abstract method of (local) martingale problems in order to give criteria for convergence of stochastic processes. Extending previous notions, the formulation we use is neither restricted to Markov processes (or semimartingales),…

Probability · Mathematics 2021-08-27 David Criens , Peter Pfaffelhuber , Thorsten Schmidt