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We show that, under certain smoothness conditions, a Brownian martingale at a fixed time can be represented as an exponential of its value at a later time. The time-dependent generator of this exponential operator is equal to one half times…

Probability · Mathematics 2015-11-06 Henry Schellhorn

We introduce a transform on the class of stochastic exponentials for d-dimensional Brownian motions. Each stochastic exponential generates another stochastic exponential under the transform. The new exponential process is often merely a…

Probability · Mathematics 2007-05-23 Victor Goodman

In this paper we give necessary and sufficient conditions for a cylindrical continuous local martingale to be the stochastic integral with respect to a cylindrical Brownian motion. In particular we consider the class of cylindrical…

Probability · Mathematics 2018-11-07 Ivan S. Yaroslavtsev

Taylor's formula holds significant importance in function representation, such as solving differential difference equations, ordinary differential equations, partial differential equations, and further promotes applications in visual…

Machine Learning · Computer Science 2025-07-15 Guoyou Wang , Yihua Tan , Shiqi Liu

In this paper we explore the fundamentals of the Martingale Representation Theorem (MRT) and a closely related result, the Clark-Ocone formula. We also investigate how far these theorems can be taken, notably beyond the regular Sobolev…

Probability · Mathematics 2013-06-25 Deborah Schneider-Luftman

We represent fractional conditional expectations of a functional of fractional Brownian motion as a convergent series in L^2 space. When the target random variable is some function of a discrete trajectory of fractional Brownian motion, we…

Probability · Mathematics 2015-08-17 Sixian Jin , Qidi Peng , Henry Schellhorn

In this report the emphasis is on an alternative representation of the Magnus series by proper operator (matrix) exponential solutions to differential equations (systems), both linear and nonlinear ODEs and PDEs. The main idea here is in…

Mathematical Physics · Physics 2026-01-06 Yu. N. Kosovtsov

Consider $\mathbb{G}$ the progressive enlargement of a filtration $\mathbb{F}$ with a random time $\tau$. Assuming that, in $\mathbb{F}$, the martingale representation property holds, we examine conditions under which the martingale…

Probability · Mathematics 2015-05-18 M. Jeanblanc , S. Song

Let $(W,H,\mu)$ be the classical Wiener space on $\R^d$. Assume that $X=(X_t)$ is a diffusion process satisfying the stochastic differential equation $dX_t=\sigma(t,X)dB_t+b(t,X)dt$, where $\sigma:[0,1]\times C([0,1],\R^n)\to \R^n\otimes…

Probability · Mathematics 2019-01-09 Ali Süleyman Üstünel

In this paper we obtain a martingale representation theorem in the progressive enlargement $\mathbb{G}$ by a random time $\tau$ of the filtration $\mathbb{F}^L$ generated by a L\'evy process $L$. The assumptions on the random time are that…

Probability · Mathematics 2020-07-29 Paolo Di Tella , Hans-Jürgen Engelbert

We show that all local martingales with respect to the initially enlarged natural filtration of a vector of multivariate point processes can be weakly represented up to the minimum among the explosion times of the components. We also prove…

Probability · Mathematics 2021-07-12 Antonella Calzolari , Barbara Torti

In this paper we explain that the natural filtration of a continuous Hunt process is continuous, and show that martingales over such a filtration are continuous. We further establish a martingale representation theorem for a class of…

Probability · Mathematics 2009-10-27 Zhongmin Qian , ; Jiangang Ying

We study the predictable representation property in the progressive enlargement F^\tau of a reference filtration F by a random time \tau. Our approach is based on the decomposition of any random time into two parts, one overlapping…

Probability · Mathematics 2024-06-21 Antonella Calzolari , Barbara Torti

Let $X$ be a point process and let $\mathbb{X}$ denote the filtration generated by $X$. In this paper we study martingale representation theorems in the filtration $\mathbb{G}$ obtained as an initial and progressive enlargement of the…

Probability · Mathematics 2020-09-09 Paolo Di Tella , Monique Jeanblanc

We develop a numerical method for the martingale analogue of the Benamou--Brenier optimal transport problem, which seeks a martingale interpolating two prescribed marginals which is closest to the Brownian motion. Recent contributions have…

Computational Finance · Quantitative Finance 2026-03-10 Manuel Hasenbichler , Benjamin Joseph , Gregoire Loeper , Jan Obloj , Gudmund Pammer

We work in the setting of the progressive enlargement $\mathbb G$ of a reference filtration $\mathbb F$ through the observation of a random time $\tau$. We study an integral representation property for some classes of $\mathbb…

Probability · Mathematics 2018-08-14 Anna Aksamit , Monique Jeanblanc , Marek Rutkowski

We devise a numerical scheme for the time evolution of matrix product operators by adapting the time-dependent variational principle for matrix product states [J. Haegeman et al, Phys. Rev. B 94, 165116 (2016)]. A simple augmentation of the…

Quantum Physics · Physics 2019-01-01 Christian B. Mendl

It is well known that Brownian motion enjoys several distributional invariances such as the scaling property and the time reversal. In this paper, we prove another invariance of Brownian motion that is compatible with the time reversal. The…

Probability · Mathematics 2023-10-20 Yuu Hariya

We outline a method based on successive canonical transformations which yields a product expansion for the evolution operator of a general (possibly non-Hermitian) Hamiltonian. For a class of such Hamiltonians this expansion involves a…

Quantum Physics · Physics 2009-10-31 Ali Mostafazadeh

Let ${\psi}:\mathbb{R}^{+}\rightarrow\mathbb{R}^{+}$ be a smooth and continuous real function and $\psi\in\mathrm{L}^{2}(\mathbb{R}^{+})$. Let ${B}(t)$ be a standard Brownian motion defined with respect to a probability space…

Probability · Mathematics 2023-02-08 Steven D Miller
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