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Related papers: Martingales et calcul stochastique

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It is shown that under a certain condition on a semimartingale and a time-change, any stochastic integral driven by the time-changed semimartingale is a time-changed stochastic integral driven by the original semimartingale. As a direct…

Probability · Mathematics 2010-10-26 Kei Kobayashi

Lecture notes for a master-level applied mathematics course on stochastic processes and applications, held at the University of Orl\'eans, France. Contents: Markov chains, Poisson point processes, Markovian jump processes, queueing theory.…

History and Overview · Mathematics 2013-12-31 Nils Berglund

We show that solutions of free stochastic differential equations with regular drifts and diffusion coefficients, when considered backwards in time, still satisfy free SDEs for an explicit free Brownian motion and drift. We also study the…

Probability · Mathematics 2014-02-20 Yoann Dabrowski

Clifford analysis has been the field of active research for several decades resulting in various methods to solve problems in pure and applied mathematics. However, the area of stochastic analysis has not been addressed in its full…

Probability · Mathematics 2022-01-19 Swanhild Bernstein , Dmitrii Legatiuk

We prove the Martingale Convergence Theorem by using the work of L. Dubins and I. Monroe about embedding a given discrete-time martingale in the sample paths of a Brownian motion.

Probability · Mathematics 2024-12-20 P. J. Fitzsimmons

In this paper we introduce the concept of conic martingales}. This class refers to stochastic processes having the martingale property, but that evolve within given (possibly time-dependent) boundaries. We first review some results about…

Probability · Mathematics 2016-03-25 Frédéric Vrins , Monique Jeanblanc

A peculiar feature of It\^o's calculus is that it is an integral calculus that gives no explicit derivative with a systematic differentiation theory counterpart, as in elementary calculus. So, can we define a pathwise stochastic derivative…

Probability · Mathematics 2010-05-25 Hassan Allouba

This work shows how exponential concentration inequalities for additive functionals of stochastic processes over a finite time interval can be derived from concentration inequalities for martingales. The approach is entirely probabilistic…

Probability · Mathematics 2020-07-14 Bob Pepin

Depuis le tout d\'ebut du XX${}^\text{e}$ si\`ecle, l'\'etude des processus stochastiques est un domaine tr\`es actif de la recherche en math\'ematiques. Parmi ces processus, le mouvement brownien --- dont l'\'etude math\'ematique a \'et\'e…

Probability · Mathematics 2016-06-24 Bastien Mallein , Marc Yor

We generalise the martingale-coboundary representation of discrete time stochastic processes to the non-stationary case and to random variables in Orlicz spaces. Related limit theorems (CLT, invariance principle, log log law, probabilities…

Probability · Mathematics 2023-11-07 Dalibor Volny

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

This paper begins by giving an historical context to fractional Brownian Motion and its development. Section 2 then introduces the fractional calculus, from the Riemann-Liouville perspective. In Section 3, we introduce Brownian motion and…

Probability · Mathematics 2014-01-14 Benjamin McGonegal

Stochastic integration \textit{wrt} Gaussian processes has raised strong interest in recent years, motivated in particular by its applications in Internet traffic modeling, biomedicine and finance. The aim of this work is to define and…

Probability · Mathematics 2018-02-15 Joachim Lebovits

We present a new approach to noncommutative stochastic calculus that is, like the classical theory, based primarily on the martingale property. Using this approach, we introduce a general theory of stochastic integration and quadratic…

Operator Algebras · Mathematics 2025-10-28 David A. Jekel , Todd A. Kemp , Evangelos A. Nikitopoulos

We review the theory of martingales as applied to stochastic thermodynamics and stochastic processes in physics more generally.

Statistical Mechanics · Physics 2024-08-20 Édgar Roldán , Izaak Neri , Raphael Chetrite , Shamik Gupta , Simone Pigolotti , Frank Jülicher , Ken Sekimoto

In these lecture notes, we explore the mathematical preliminaries and foundational concepts that connect stochastic processes with partial differential equations. We begin by investigating Brownian motion, which serves as a model for random…

Probability · Mathematics 2025-09-15 Helder Rojas

We present a construction of the basic operators of stochastic analysis (gradient and divergence) for a class of discrete-time normal martingales called obtuse random walks. The approach is based on the chaos representation property and…

Probability · Mathematics 2015-02-18 Uwe Franz , Tarek Hamdi

The stochastic trajectories of molecules in living cells, as well as the dynamics in many other complex systems, often exhibit memory in their path over long periods of time. In addition, these systems can show dynamic heterogeneities due…

Statistical Mechanics · Physics 2024-07-10 Michał Balcerek , Agnieszka Wyłomańska , Krzysztof Burnecki , Ralf Metzler , Diego Krapf

This is a guide to the mathematical theory of Brownian motion and related stochastic processes, with indications of how this theory is related to other branches of mathematics, most notably the classical theory of partial differential…

Probability · Mathematics 2018-02-28 Jim Pitman , Marc Yor

Given a random time, we characterize the set of martingales for which the stopping theorems still hold. We also investigate how the stopping theorems are modified when we consider arbitrary random times. To this end, we introduce some…

Probability · Mathematics 2007-08-03 Ashkan Nikeghbali
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