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Stochastic differential equations such as the Ornstein-Uhlenbeck process have long been used to model realworld probablistic events such as stock prices and temperature fluctuations. While statistical methods such as Maximum Likelihood…

Machine Learning · Computer Science 2026-02-05 Aroon Sankoh , Victor Wickerhauser

The LIBOR market model is very popular for pricing interest rate derivatives, but is known to have several pitfalls. In addition, if the model is driven by a jump process, then the complexity of the drift term is growing exponentially fast…

Computational Finance · Quantitative Finance 2015-03-19 Antonis Papapantoleon , John Schoenmakers , David Skovmand

Constructing \Levy-driven Ornstein-Uhlenbeck processes is a task closely related to the notion of self-decomposability. In particular, their transition laws are linked to the properties of what will be hereafter called the \emph{a-reminder}…

Probability · Mathematics 2020-11-19 Nicola Cufaro Petroni , Piergiacomo Sabino

We review the probabilistic properties of Ornstein-Uhlenbeck processes in Hilbert spaces driven by L\'{e}vy processes. The emphasis is on the different contexts in which these processes arise, such as stochastic partial differential…

Probability · Mathematics 2014-11-12 David Applebaum

The purpose of this article is to introduce a new L\'evy process, termed Variance Gamma++ process, to model the dynamic of assets in illiquid markets. Such a process has the mathematical tractability of the Variance Gamma process and is…

Mathematical Finance · Quantitative Finance 2022-07-03 M. Gardini , P. Sabino , E. Sasso

We study the least squares estimator for the drift parameter of the Langevin stochastic equation driven by the Rosenblatt process. Using the techniques of the Malliavin calculus and the stochastic integration with respect to the Rosenblatt…

Probability · Mathematics 2019-03-07 Radomyra Shevchenko , Ciprian A. Tudor

Motivated by empirical evidence from the joint behavior of realized volatility time series, we propose to model the joint dynamics of log-volatilities using a multivariate fractional Ornstein-Uhlenbeck process. This model is a multivariate…

Statistical Finance · Quantitative Finance 2026-05-19 Ranieri Dugo , Giacomo Giorgio , Paolo Pigato

We present a stochastic volatility market model where volatility is correlated with return and is represented by an Ornstein-Uhlenbeck process. With this model we exactly measure the leverage effect and other stylized facts, such as mean…

Condensed Matter · Physics 2007-05-23 Josep Perello , Jaume Masoliver

This work extends the variance reduction method for the pricing of possibly path-dependent derivatives, which was developed in (Genin and Tankov, 2016) for exponential L\'evy models, to affine stochastic volatility models (Keller-Ressel,…

Probability · Mathematics 2018-09-18 Zorana Grbac , David Krief , Peter Tankov

We propose a general framework of European power option pricing under two different market assumptions about extended Vasic\v{e}k interest rate process and exponential Ornstein-Uhlenbeck asset process with continuous dividend as underlying,…

Pricing of Securities · Quantitative Finance 2022-05-24 Jingwei Liu

We present a new model for the electricity spot price dynamics, which is able to capture seasonality, low-frequency dynamics and the extreme spikes in the market. Instead of the usual purely deterministic trend we introduce a non-stationary…

Applications · Statistics 2012-01-06 Fred Espen Benth , Claudia Klüppelberg , Gernot Müller , Linda Vos

In this paper, we study the Ornstein-Uhlenbeck bridge process (i.e. the Ornstein-Uhlenbeck process conditioned to start and end at fixed points) constraints to have a fixed area under its path. We present both anticipative (in this case, we…

Statistical Mechanics · Physics 2017-10-11 Alain Mazzolo

In this paper, we study the cut-off phenomenon under the total variation distance of $d$-dimensional Ornstein-Uhlenbeck processes which are driven by L\'evy processes. That is to say, under the total variation distance, there is an abrupt…

Probability · Mathematics 2023-05-05 Gerardo Barrera , Juan Carlos Pardo

Weather is a key production factor in agricultural crop production and at the same time the most significant and least controllable source of peril in agriculture. These effects of weather on agricultural crop production have triggered a…

Mathematical Finance · Quantitative Finance 2018-08-15 Samuel Asante Gyamerah , Philip Ngare , Dennis Ikpe

We consider the Graph Ornstein-Uhlenbeck (GrOU) process observed on a non-uniform discrete time grid and introduce discretised maximum likelihood estimators with parameters specific to the whole graph or specific to each component, or node.…

Methodology · Statistics 2022-07-12 Valentin Courgeau , Almut E. D. Veraart

The small noise cut-off phenomenon in continuous time and space has been studied in the recent literature for the linear and non-linear stable Langevin dynamics with additive L\'evy drivers - understood as abrupt thermalization of the…

Probability · Mathematics 2025-02-13 Gerardo Barrera , Michael A. Högele , Pauliina Ilmonen , Lauri Viitasaari

We study high-dimensional Ornstein--Uhlenbeck processes driven by L\'evy noise and consider drift matrices that decompose into a low-rank plus sparse component, capturing a few latent factors together with a sparse network of direct…

Probability · Mathematics 2026-03-25 Marina Palaisti

We study the ergodic properties of a class of multidimensional piecewise Ornstein-Uhlenbeck processes with jumps, which contains the limit of the queueing processes arising in multiclass many-server queues with heavy-tailed arrivals and/or…

Probability · Mathematics 2019-03-20 Ari Arapostathis , Guodong Pang , Nikola Sandrić

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

Due to complex physical phenomena, the distribution of heavy rainfall events is difficult to model spatially. Physically based numerical models can often provide physically coherent spatial patterns, but may miss some important…

Applications · Statistics 2020-03-13 Marco Oesting , Philippe Naveau
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