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The martingale expansion provides a refined approximation to the marginal distributions of martingales beyond the normal approximation implied by the martingale central limit theorem. We develop a martingale expansion framework specifically…

Probability · Mathematics 2026-02-06 Masaaki Fukasawa

For one-dimensional diffusions on the half-line, we study a specific type of conditioning to avoid zero. We introduce supermartingales defined via concave functions with respect to the scale function. A conditioning is formulated through…

Probability · Mathematics 2025-09-30 Kosuke Yamato

This overview article concerns the notion of fractional smoothness of random variables of the form $g(X_T)$, where $X=(X_t)_{t\in [0,T]}$ is a certain diffusion process. We review the connection to the real interpolation theory, give…

Probability · Mathematics 2010-04-22 Stefan Geiss , Emmanuel Gobet

A multiplicative cascade can be thought of as a randomization of a measure on the boundary of a tree, constructed from an iid collection of random variables attached to the tree vertices. Given an initial measure with certain regularity…

Probability · Mathematics 2013-05-28 Tom Alberts , Ben Rifkind

We show that the existence of a martingale approximation of a stationary process depends on the choice of the filtration. There exists a stationary linear process which has a martingale approximation with respect to the natural filtration,…

Probability · Mathematics 2011-09-13 Hervé Queffélec , Dalibor Volný

Is this paper we study penalisations of diffusions satisfying some technical conditions, generalizing a result obtained by Najnudel, Roynette and Yor. If one of these diffusions has probability distribution $\mathbb{P}$, then our result can…

Probability · Mathematics 2009-11-24 Joseph Najnudel , Ashkan Nikeghbali

For a diffusion X_t in a one-dimensional Wiener medium W, it is known that there is a certain process b_x(W) that depends only on the environment W, so that X_t-b_{logt}(W) converges in distribution as t goes to infinity. We prove that,…

Probability · Mathematics 2007-05-23 Dimitrios Cheliotis

We provide verification theorems (at different levels of generality) for infinite horizon stochastic control problems in continuous time for semimartingales. The control framework is given as an abstract "martingale formulation", which…

Probability · Mathematics 2020-01-01 Ma. Elena Hernández-Hernández , Saul Jacka , Aleksandar Mijatović

In this paper we consider parameter estimation for discretely observed diffusion processes. In particular, we focus on data that are observed at low frequency and methodology that can estimate parameters with uncertainty quantification.…

Computation · Statistics 2026-05-01 Jingning Yao , Ajay Jasra , Sheng Jiang

Suppose that $(X,Y,Z)$ is a random walk in $\mathbb{Z}^3$ that moves in the following way: on the first visit to a vertex only $Z$ changes by $\pm 1$ equally likely, while on later visits to the same vertex $(X,Y)$ performs a…

Probability · Mathematics 2014-03-07 Yuval Peres , Bruno Schapira , Perla Sousi

We give a necessary and sufficient condition on a sequence of functions on a set $\Omega$ under which there is a measure on $\Omega$ which renders the given sequence of functions a martingale. Further such a measure is unique if we impose a…

Probability · Mathematics 2007-05-23 Rajeeva L Karandikar , M G Nadkarni

According to a theorem of S. Schumacher and T. Brox, for a diffusion $X$ in a Brownian environment it holds that $(X_t-b_{\log t})/\log^2t\to 0 $ in probability, as $t\to\infty$, where $b_{\cdot}$ is a stochastic process having an explicit…

Probability · Mathematics 2007-05-23 Dimitrios Cheliotis

We derive diffusion constants and martingales for senile random walks with the help of a time-change. We provide direct computations of the diffusion constants for the time-changed walks. Alternatively, the values of these constants can be…

Probability · Mathematics 2007-11-19 Wouter Kager

We analyze circumstances under which the microscopic dynamics of particles which are driven by a forced, gradient-type flow can be consistently interpreted as a Markovian diffusion process. Special attention is paid to discriminating…

Condensed Matter · Physics 2007-05-23 P. Garbaczewski

Through the analysis of unbiased random walks on fractal trees and continuous time random walks, we show that even if a process is characterized by a mean square displacement (MSD) growing linearly with time (standard behaviour) its…

Statistical Mechanics · Physics 2014-06-16 Giuseppe Forte , Fabio Cecconi , Angelo Vulpiani

Point processes often have a natural interpretation with respect to a continuous process. We propose a point process construction that describes arrival time observations in terms of the state of a latent diffusion process. In this…

Computation · Statistics 2023-06-02 Ali Hasan , Yu Chen , Yuting Ng , Mohamed Abdelghani , Anderson Schneider , Vahid Tarokh

We study representations of a random variable $\xi$ as an integral of an adapted process with respect to the Lebesgue measure. The existence of such representations in two different regularity classes is characterized in terms of the…

Probability · Mathematics 2023-08-08 Sara Biagini , Gordan Zitkovic

We present analytical results for the biased diffusion of particles moving under a constant force in a randomly layered medium. The influence of this medium on the particle dynamics is modeled by a piecewise constant random force. The…

Statistical Mechanics · Physics 2010-02-10 S. I. Denisov , H. Kantz

Two aspects of noncolliding diffusion processes have been extensively studied. One of them is the fact that they are realized as harmonic Doob transforms of absorbing particle systems in the Weyl chambers. Another aspect is integrability in…

Probability · Mathematics 2014-07-18 Makoto Katori

This paper introduces a martingale that characterizes two properties of evolving forecast distributions. Ideal forecasts of a future event behave as martingales, sequen- tially updating the forecast to leverage the available information as…

Machine Learning · Computer Science 2021-05-17 Dean P. Foster , Robert A. Stine