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The multivariate Ornstein-Uhlenbeck process is used in many branches of science and engineering to describe the regression of a system to its stationary mean. Here we present an $O(N)$ Bayesian method to estimate the drift and diffusion…

Statistical Mechanics · Physics 2018-08-01 Rajesh Singh , Dipanjan Ghosh , R. Adhikari

We introduce a flexible and tractable infinite-dimensional stochastic volatility model. More specifically, we consider a Hilbert space valued Ornstein-Uhlenbeck-type process, whose instantaneous covariance is given by a pure-jump stochastic…

Probability · Mathematics 2021-08-06 Sonja Cox , Sven Karbach , Asma Khedher

In this paper, we analyze the use of the Ornstein-Uhlenbeck process to model dynamical systems subjected to bounded noisy perturbations. In order to discuss the main characteristics of this new approach we consider some basic models in…

Dynamical Systems · Mathematics 2024-01-17 Tomás Caraballo , Renato Colucci , Javier López-de-la-Cruz , Alain Rapaport

We investigate the Local Asymptotic Property for fractional Brownian models based on discrete observations contaminated by a Gaussian moving average process. We consider both situations of low and high-frequency observations in a unified…

Statistics Theory · Mathematics 2023-12-01 Grégoire Szymanski , Tetsuya Takabatake

The use of an Ornstein-Uhlenbeck (OU) process is ubiquitous in business, economics and finance to capture various price processes and evolution of economic indicators exhibiting mean-reverting properties. When structural changes happen,…

Methodology · Statistics 2017-05-30 Fuqi Chen , Rogemar Mamon , Matt Davison

We establish an important connection between coherent quantum feedback and the Ornstein-Uhlenbeck process in quantum optics. We show that an emitter with fluctuating energy levels in front of a mirror results in an Ornstein-Uhlenbeck…

Quantum Physics · Physics 2020-09-16 Alexander Carmele , Scott Parkins , Andreas Knorr

Using the large deviation principle (LDP) for a re-scaled fractional Brownian motion $B^H_t$ where the rate function is defined via the reproducing kernel Hilbert space, we compute small-time asymptotics for a correlated fractional…

Pricing of Securities · Quantitative Finance 2021-03-17 Martin Forde , Hongzhong Zhang

In this paper we investigate a class of nonautonomous linear parabolic problems with time depending Ornstein-Uhlenbeck operators. We study the asymptotic behavior of the associated evolution operator and evolution semigroup in the periodic…

Analysis of PDEs · Mathematics 2014-02-26 Matthias Geissert , Alessandra Lunardi

We propose a two stage procedure for the estimation of the parameters of a fairly general, continuous-time stochastic volatility. An important ingredient of the proposed method is the Cuchiero-Teichmann volatility estimator, which is based…

Statistics Theory · Mathematics 2018-12-31 Milan Merkle , Yuri F. Saporito , Rodrigo S. Targino

We study the asymptotic behavior of distribution densities arising in stock price models with stochastic volatility. The main objects of our interest in the present paper are the density of time averages of the squared volatility process…

Pricing of Securities · Quantitative Finance 2009-06-03 A. Gulisashvili , E. M. Stein

We introduce the two-factor Quintic Ornstein-Uhlenbeck (OU) model, where volatility is modelled as a degree-five polynomial of the sum of two Ornstein-Uhlenbeck processes driven by the same Brownian motion, each mean-reverting at a…

Mathematical Finance · Quantitative Finance 2026-04-23 Eduardo Abi Jaber , Shaun , Li

We study the asymptotic behavior of weighted power variations of fractional Brownian motion in Brownian time Z_t:= X_{Y_t}, t >= 0, where X is a fractional Brownian motion and Y is an independent Brownian motion.

Probability · Mathematics 2017-02-28 Raghid Zeineddine

We consider the motion of an active Brownian particle with speed fluctuations in d-dimensions in the presence of both translational and orientational diffusion. We use an Ornstein-Uhlenbeck process for active speed generation. Using a…

Statistical Mechanics · Physics 2022-05-02 Amir Shee , Debasish Chaudhuri

Many fractional processes can be represented as an integral over a family of Ornstein-Uhlenbeck processes. This representation naturally lends itself to numerical discretizations, which are shown in this paper to have strong convergence…

Mathematical Finance · Quantitative Finance 2020-08-06 Philipp Harms

By working in the small persistence time limit, we determine the steady-state distribution of an Active Ornstein Uhlenbeck Particle (AOUP) experiencing, in addition to self-propulsion, a Gaussian white noise modelling a bath at temperature…

Statistical Mechanics · Physics 2021-05-26 David Martin , Thibaut Arnoulx de Pirey

In this paper, we study the asymptotic behaviour of one-dimensional integrated Ornstein-Uhlenbeck processes driven by $\alpha$-stable L\'{e}vy processes of small amplitude. We prove that the integrated Ornstein-Uhlenbeck process converges…

Probability · Mathematics 2014-02-06 Robert Hintze , Ilya Pavlyukevich

We consider a positive stationary generalized Ornstein--Uhlenbeck process \[V_t=\mathrm{e}^{-\xi_t}\biggl(\int_0^t\mathrm{e}^{\xi_{s-}}\ ,\mathrm{d}\eta_s+V_0\biggr)\qquadfor t\geq0,\] and the increments of the integrated generalized…

Statistics Theory · Mathematics 2010-02-24 Vicky Fasen

The volatility characterizes the amplitude of price return fluctuations. It is a central magnitude in finance closely related to the risk of holding a certain asset. Despite its popularity on trading floors, the volatility is unobservable…

Physics and Society · Physics 2008-12-02 Zoltan Eisler , Josep Perello , Jaume Masoliver

The paper considers the problem of robust estimating a periodic function in a continuous time regression model with dependent disturbances given by a general square integrable semimartingale with unknown distribution. An example of such a…

Statistics Theory · Mathematics 2010-10-20 Victor Konev , Serguei Pergamenchtchikov

Assuming that a threshold Ornstein-Uhlenbeck process is observed at discrete time instants, we propose generalized moment estimators to estimate the parameters. Our theoretical basis is the celebrated ergodic theorem. To use this theorem we…

Statistics Theory · Mathematics 2020-11-24 Yaozhong Hu , Yuejuan Xi