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The paper gives a new representation for the fractional Brownian motion that can be applied to simulate this self-similar random process in continuous time. Such a representation is based on the spectral form of mathematical description and…

Probability · Mathematics 2025-01-28 Konstantin A. Rybakov

In this paper, we introduce a new method to study the doubly reflected backward stochastic differential equation driven by G-Brownian motion (G-BSDE). Our approach involves approximating the solution through a family of penalized reflected…

Probability · Mathematics 2024-03-28 Hanwu Li , Ning Ning

Starting with conformally covariant correlation functions, a sequence of functional representations of the conformal algebra is constructed. A key step is the introduction of representations which involve an auxiliary functional. It is…

High Energy Physics - Theory · Physics 2018-04-24 Oliver J. Rosten

In this paper, we show an approximation in law of the complex Brownian motion by processes constructed from a stochastic process with independent increments. We give sufficient conditions for the characteristic function of the process with…

Probability · Mathematics 2013-08-28 Xavier Bardina , Carles Rovira

We show that if a random variable is the final value of an adapted log-H\"{o}lder continuous process, then it can be represented as a stochastic integral with respect to a fractional Brownian motion with adapted integrand. In order to…

Probability · Mathematics 2015-10-08 Taras Shalaiko , Georgiy Shevchenko

We review some recent results on connections between Brownian motion, Whittaker functions, random matrices and representation theory.

Probability · Mathematics 2012-10-26 Neil O'Connell

By using the Picard iteration scheme, this article establishes the existence and uniqueness theory for solutions to stochastic functional differential equations driven by G-Browniain motion. Assuming the monotonicity conditions, the…

Probability · Mathematics 2018-06-21 Faiz Faizullah

Sufficient and necessary conditions are presented for the comparison theorem of path dependent $G$-SDEs. Different from the corresponding study in path independent $G$-SDEs, a probability method is applied to prove these results. Moreover,…

Probability · Mathematics 2020-04-28 Xing Huang , Fen-Fen Yang

We consider a modification of the covariance function in Gaussian processes to correctly account for known linear constraints. By modelling the target function as a transformation of an underlying function, the constraints are explicitly…

Machine Learning · Statistics 2017-09-20 Carl Jidling , Niklas Wahlström , Adrian Wills , Thomas B. Schön

We study integral representations of random variables with respect to general H\"older continuous processes and with respect to two particular cases; fractional Brownian motion and mixed fractional Brownian motion. We prove that arbitrary…

Probability · Mathematics 2014-05-01 Georgiy Shevchenko , Lauri Viitasaari

We establish Harnack inequality and shift Harnack inequality for stochastic differential equation driven by $G$-Brownian motion. As applications, the uniqueness of invariant linear expectations and estimates on the $\sup$-kernel are…

Probability · Mathematics 2018-08-28 Fenfen Yang

We derive sufficient conditions for the convex and monotonic g-stochastic ordering of diffusion processes under nonlinear g-expectations and g-evaluations. Our approach relies on comparison results for forward-backward stochastic…

Probability · Mathematics 2022-04-13 Sel Ly , Nicolas Privault

This paper presents a new approach to the analysis of mixed processes \[X_t=B_t+G_t,\qquad t\in[0,T],\] where $B_t$ is a Brownian motion and $G_t$ is an independent centered Gaussian process. We obtain a new canonical innovation…

Probability · Mathematics 2016-09-05 Chunhao Cai , Pavel Chigansky , Marina Kleptsyna

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 book, we introduce a new approach of sublinear expectation to deal with the problem of probability and distribution model uncertainty. We a new type of (robust) normal distributions and the related central limit theorem under…

Probability · Mathematics 2010-02-25 Shige Peng

Majorana's arbitrary spin theory is considered in a hyperbolic complex representation. The underlying differential equation is embedded into the gauge field theories of Sachs and Carmeli. In particular, the approach of Sachs can serve as a…

General Physics · Physics 2014-09-16 S. Ulrych

The objective of this paper is to establish the decomposition theorem for supermartingales under the $G$-framework. We first introduce a $g$-nonlinear expectation via a kind of $G$-BSDE and the associated supermartingales. We have shown…

Probability · Mathematics 2020-11-10 Hanwu Li , Shige Peng , Yongsheng Song

This paper reviews and extends some recent results on the multivariate fractional Brownian motion (mfBm) and its increment process. A characterization of the mfBm through its covariance function is obtained. Similarly, the correlation and…

In this paper, we study the reflected backward stochastic differential equation driven by G-Brownian motion (reflected G-BSDE for short) with an upper obstacle. The existence is proved by approximation via penalization. By using a variant…

Probability · Mathematics 2017-09-29 Hanwu Li , Shige Peng

This paper develops a new technique for the path approximation of one-dimensional stochastic processes, more precisely the Brownian motion and families of stochastic differential equations sharply linked to the Brownian motion (usually…

Probability · Mathematics 2020-12-16 Madalina Deaconu , Samuel Herrmann