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We derive an explicit representation for the transition law of a $p$-tempered $\alpha$-stable process of Ornstein-Uhlenbeck-type and use it to develop a methodology for simulation. Our results apply in both the univariate and multivariate…

Probability · Mathematics 2020-05-20 Michael Grabchak

We give an explicit representation for the transition law of a tempered stable Ornstein-Uhlenbeck process and use it to develop a rejection sampling algorithm for exact simulation of increments from this process. Our results apply to…

Probability · Mathematics 2020-05-19 Michael Grabchak

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

The paper describes the self-decomposable distribution and the background driving L\'evy process (BDLP) associated with the Generalized Tempered Stable (GTS) distribution. Two distributions are provided: the background driving L\'evy…

Probability · Mathematics 2024-05-28 A. H. Nzokem

Stable distributions are a celebrated class of probability laws used in various fields. The $\alpha$-stable process, and its exponentially tempered counterpart, the Classical Tempered Stable (CTS) process, are also prominent examples of…

Probability · Mathematics 2024-12-10 Taher Jalal

We investigate the distributional properties of two generalized Ornstein-Uhlenbeck (OU) processes whose stationary distributions are the gamma law and the bilateral gamma law, respectively. The said distributions turn out to be related to…

Probability · Mathematics 2021-03-25 Nicola Cufaro Petroni , Piergiacomo Sabino

An Ornstein-Uhlenbeck (OU) process can be considered as a continuous time interpolation of the discrete time AR$(1)$ process. Departing from this fact, we analyse in this work the effect of iterating OU treated as a linear operator that…

Statistics Theory · Mathematics 2012-10-02 Argimiro Arratia , Alejandra Cabaña , Enrique M. Cabaña

L\'evy-driven Ornstein-Uhlenbeck (OU) processes represent an intriguing class of stochastic processes that have garnered interest in the energy sector for their ability to capture typical features of market dynamics. However, in the current…

Computational Finance · Quantitative Finance 2026-05-07 Roberto Baviera , Pietro Manzoni

This paper analyzes various classes of processes associated with the tempered positive Linnik (TPL) distribution. We provide several subordinated representations of TPL L\'evy processes and in particular establish a stochastic…

Probability · Mathematics 2022-06-07 Lorenzo Torricelli , Lucio Barabesi , Andrea Cerioli

We prove some efficient inference results concerning estimation of a Ornstein-Uhlenbeck regression model, which is driven by a non-Gaussian stable Levy process and where the output process is observed at high-frequency over a fixed time…

Statistics Theory · Mathematics 2023-01-18 Hiroki Masuda

The steady state of the Fokker-Planck equation corresponding to a density dependent one-step process is approximated by a suitable normal distribution. Starting from the master equations of the process, written in terms of the time…

Dynamical Systems · Mathematics 2016-09-16 Peter L. Simon , Eszter Sikolya

In this paper we introduce the well-balanced L\'{e}vy driven Ornstein-Uhlenbeck process as a moving average process of the form $X_t=\int \exp(-\lambda |t-u|)dL_u$. In contrast to L\'{e}vy driven Ornstein-Uhlenbeck processes the…

Probability · Mathematics 2013-01-08 Alexander Schnurr , Jeannette H. C. Woerner

Consider a multivariate L\'evy-driven Ornstein-Uhlenbeck process where the stationary distribution or background driving L\'evy process is from a parametric family. We derive the likelihood function assuming that the innovation term is…

Statistics Theory · Mathematics 2021-09-01 Kevin W. Lu

We consider an Ornstein-Uhleneck (OU) process associated to self-normalised sums in i.i.d. symmetric random variables from the domain of attraction of $N(0, 1)$ distribution. We proved the self-normalised sums converge to the OU process (in…

Probability · Mathematics 2013-02-04 Gopal K. Basak , Amites Dasgupta

The study of non-stationary processes whose local form has controlled properties is a fruitful and important area of research, both in theory and applications. We present here a construction of multifractional multistable processes, based…

Probability · Mathematics 2009-11-03 Ronan Le Guével , Jacques Lévy-Véhel

We consider a transformed Ornstein-Uhlenbeck process model that can be a good candidate for modelling real-life processes characterized by a combination of time-reverting behaviour with heavy distribution tails. We begin with presenting the…

Probability · Mathematics 2011-03-01 K. Borovkov , G. Decrouez

In this study we define a three-step procedure to relate the self-decomposability of the stationary law of a generalized Ornstein-Uhlenbeck process to the law of the increments of such processes. Based on this procedure and the results of…

Computational Finance · Quantitative Finance 2021-03-25 Piergiacomo Sabino

In recent years there have been many proposals as flexible alternatives to Gaussian based continuous time stochastic volatility models. A great deal of these models employ positive L\'evy processes. Among these are the attractive…

Statistics Theory · Mathematics 2007-06-13 Lancelot F. James

We introduce the elliptical Ornstein-Uhlenbeck (OU) process, which is a generalisation of the well-known univariate OU process to bivariate time series. This process maps out elliptical stochastic oscillations over time in the complex…

Methodology · Statistics 2021-12-08 Adam M. Sykulski , Sofia C. Olhede , Hanna M. Sykulska-Lawrence

Rapidly decreasing tempered stable distributions are useful models for financial applications. However, there has been no exact method for simulation available in the literature. We remedy this by introducing an exact simulation method in…

Probability · Mathematics 2021-02-09 Michael Grabchak
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