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We consider additive functionals of stationary Markov processes and show that under Kipnis-Varadhan type conditions they converge in rough path topology to a Stratonovich Brownian motion, with a correction to the Levy area that can be…

Probability · Mathematics 2019-12-23 Jean-Dominique Deuschel , Tal Orenshtein , Nicolas Perkowski

We provide an overview on how to use the measurable selection techniques to derive the dynamic programming principle for a general stochastic optimal control/stopping problem. By considering its martingale problem formulation on the…

Optimization and Control · Mathematics 2024-10-03 Nicole El Karoui , Xiaolu Tan

We propose a novel framework for analyzing convergence rates of stochastic optimization algorithms with adaptive step sizes. This framework is based on analyzing properties of an underlying generic stochastic process, in particular by…

Optimization and Control · Mathematics 2018-10-23 Jose Blanchet , Coralia Cartis , Matt Menickelly , Katya Scheinberg

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 strict local martingale is a local martingale which is not a martingale. There are few explicit examples of "naturally occurring" strict local martingales with jumps available in the literature. The purpose of this paper is to provide…

Probability · Mathematics 2014-03-26 Philip Protter

Stochastic variational inference makes it possible to approximate posterior distributions induced by large datasets quickly using stochastic optimization. The algorithm relies on the use of fully factorized variational distributions.…

Machine Learning · Computer Science 2014-11-27 Matthew D. Hoffman , David M. Blei

For a real Borel measurable function b, which satisfies certain integrability conditions, it is possible to define a stochastic integral of the process b(Y) with respect to a Brownian motion W, where Y is a diffusion driven by W. It is well…

Probability · Mathematics 2010-10-06 Aleksandar Mijatović , Nika Novak , Mikhail Urusov

This paper studies large deviations of a ``fully coupled" finite state mean-field interacting particle system in a fast varying environment. The empirical measure of the particles evolves in the slow time scale and the random environment…

Probability · Mathematics 2021-06-24 Sarath Yasodharan , Rajesh Sundaresan

We study Bessel processes on Weyl chambers of types A and B on $\mathbb R^N$. Using elementary symmetric functions, we present several space-time-harmonic functions and thus martingales for these processes $(X_t)_{t\ge0}$ which are…

Probability · Mathematics 2019-08-30 Miklos Kornyik , Michael Voit , Jeannette H. C. Woerner

In variational phase-field modeling of brittle fracture, the functional to be minimized is not convex, so that the necessary stationarity conditions of the functional may admit multiple solutions. The solution obtained in an actual…

Computational Engineering, Finance, and Science · Computer Science 2023-07-19 Tymofiy Gerasimov , Ulrich Römer , Jaroslav Vondřejc , Hermann G. Matthies , Laura De Lorenzis

We analyze the effect of additive fractional noise with Hurst parameter $H > \frac{1}{2}$ on fast-slow systems. Our strategy is based on sample paths estimates, similar to the approach by Berglund and Gentz in the Brownian motion case. Yet,…

Probability · Mathematics 2020-02-19 Katharina Eichinger , Christian Kuehn , Alexandra Neamtu

We use the martingale-theoretic approach of game-theoretic probability to incorporate imprecision into the study of randomness. In particular, we define a notion of computable randomness associated with interval, rather than precise,…

Probability · Mathematics 2017-05-05 Gert de Cooman , Jasper De Bock

The comparison of local characteristics of two random processes can shed light on periods of time or space at which the processes differ the most. This paper proposes a method that learns about regions with a certain volume, where the…

Methodology · Statistics 2022-09-14 Miguel de Carvalho , Gabriel Martos Venturini

The aim of this paper is to represent any continuous local martingale as an almost sure limit of a nested sequence of simple, symmetric random walks, time changed by a discrete quadratic variation process. One basis of this is a similar…

Probability · Mathematics 2010-08-10 Balazs Szekely , Tamas Szabados

We consider local martingales which are standard or stochastic exponentials M of one component X of a multivariate affine process in the sense of Duffie, Filipovic and Schachermayer (2003). By completing their characterization of…

Probability · Mathematics 2011-05-06 Eberhard Mayerhofer , Johannes Muhle-Karbe , Alexander G. Smirnov

This work develops change-point methods for statistics of high-frequency data. The main interest is in the volatility of an It\^{o} semi-martingale, the latter being discretely observed over a fixed time horizon. We construct a…

Statistics Theory · Mathematics 2016-01-13 Markus Bibinger , Moritz Jirak , Mathias Vetter

Estimation and prediction in high dimensional multivariate factor stochastic volatility models is an important and active research area because such models allow a parsimonious representation of multivariate stochastic volatility. Bayesian…

Computation · Statistics 2021-04-27 David Gunawan , Robert Kohn , David Nott

Multi-dimensional continuous local martingales, enhanced with their stochastic area process, give rise to geometric rough paths with a.s. finite homogenous p-variation, p>2. Here we go one step further and establish quantitative bounds of…

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

The aim of this paper is to develop tractable large deviation approximations for the empirical measure of a small noise diffusion. The starting point is the Freidlin-Wentzell theory, which shows how to approximate via a large deviation…

Probability · Mathematics 2021-01-11 Paul Dupuis , Guo-Jhen Wu

We consider some versions and generalizations of an approach to the expansion of iterated Ito stochastic integrals of arbitrary multiplicity $k$ $(k\in\mathbb{N})$ based on generalized multiple Fourier series. Expansions of iterated…

Probability · Mathematics 2023-08-01 Dmitriy F. Kuznetsov