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Related papers: Coupling for Ornstein--Uhlenbeck processes with ju…

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In this paper we study the pricing of exchange options under a dynamic described by stochastic correlation with random jumps. In particular, we consider a Ornstein-Uhlenbeck covariance model with Levy Background Noise Process driven by…

Computational Finance · Quantitative Finance 2017-11-29 Olivares Pablo , Villamor Enrique

It is shown that large deviation statistical quantities of the discrete time, finite state Markov process $P_{n+1}^{(j)}=\sum_{k=1}^NH_{jk}P_n^{(k)}$, where P_n^{(j)} is the probability for the j-state at the time step n and H_{jk} is the…

Chaotic Dynamics · Physics 2009-11-13 Miki U. Kobayashi , Hirokazu Fujisaka , Syuji Miyazaki

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

We study a Markov process with two components: the first component evolves according to one of finitely many underlying Markovian dynamics, with a choice of dynamics that changes at the jump times of the second component. The second…

Probability · Mathematics 2015-04-14 Bertrand Cloez , Martin Hairer

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

We consider the extreme value statistics of correlated random variables that arise from a Langevin equation. Recently, it was shown that the extreme values of the Ornstein-Uhlenbeck process follow a different distribution than those…

Statistical Mechanics · Physics 2021-08-17 Lior Zarfaty , Eli Barkai , David A. Kessler

In this article we consider parametric Bayesian inference for stochastic differential equations (SDE) driven by a pure-jump stable Levy process, which is observed at high frequency. In most cases of practical interest, the likelihood…

Statistics Theory · Mathematics 2017-07-28 Ajay Jasra , Kengo Kamatani , Hiroki Masuda

Two-level system strongly coupled to a single resonator mode (harmonic oscillator) is a paradigmatic model in many subfields of physics. We study theoretically the Landau-Zener transition in this model. Analytical solution for the…

Mesoscale and Nanoscale Physics · Physics 2018-01-31 Rajesh K. Malla , M. E. Raikh

We study a general non-homogeneous Skellam-type process with jumps of arbitrary fixed size. We express this process in terms of a linear combination of Poisson processes and study several properties, including the summation of independent…

Probability · Mathematics 2025-04-11 Fabrizio Cinque , Enzo Orsingher

General stochastic equations with jumps are studied. We provide criteria for the uniqueness and existence of strong solutions under non-Lipschitz conditions of Yamada-Watanabe type. The results are applied to stochastic equations driven by…

Probability · Mathematics 2010-08-04 Zenghu Li , Leonid Mytnik

We consider non-local Ornstein-Uhlenbeck (OU) operators that correspond to Ornstein-Uhlenbeck processes driven by L\'evy processes. These are ergodic Markov processes and the OU operator is in general non-normal in the $L^2$ space weighted…

Probability · Mathematics 2026-04-14 Rohan Sarkar

Consider $n$ independent Goldstein-Kac telegraph processes $X_1(t), \dots ,X_n(t), \; n\ge 2, \; t\ge 0,$ on the real line $\Bbb R$. Each the process $X_k(t), \; k=1,\dots,n,$ describes a stochastic motion at constant finite speed $c_k>0$…

Probability · Mathematics 2018-08-14 Alexander D. Kolesnik

While short-range dependence is widely assumed in the literature for its simplicity, long-range dependence is a feature that has been observed in data from finance, hydrology, geophysics and economics. In this paper, we extend a…

Methodology · Statistics 2019-05-20 Michele Nguyen , Almut E. D. Veraart

Let $X:=(X_t)_{t\geq 0}$ be an ergodic Markov process on $\real^d$, and $p>0$. We derive upper bounds of the $p$-Wasserstein distance between the invariant measure and the empirical measures of the Markov process $X$. For this we assume,…

Probability · Mathematics 2025-12-30 René L. Schilling , Jian Wang , Bingyao Wu , Jie-Xiang Zhu

We consider the problem of parameter estimation for the partially observed linear stochastic differential equation. We assume that the unobserved Ornstein-Uhlenbeck process depends on some unknown parameter and estimate the unobserved…

Statistics Theory · Mathematics 2019-02-25 Yury A. Kutoyants

Based on a version of Dudley's Wiener process on the mass shell in the momentum Minkowski space of a massive point particle, a model of a relativistic Ornstein--Uhlenbeck process is constructed by addition of a specific drift term. The…

Mathematical Physics · Physics 2017-03-22 Jürgen Potthoff , Robert Schrader

This paper establishes a Transition Path Theory (TPT) for L\'{e}vy-type processes, addressing a critical gap in the study of the transition mechanism between meta-stabile states in non-Gaussian stochastic systems. A key contribution is the…

Probability · Mathematics 2026-05-04 Yuanfei Huang , Xiang Zhou

Statistical testing is classically used as an exploratory tool to search for association between a phenotype and many possible explanatory variables. This approach often leads to multiple testing under dependence. We assume a hierarchical…

Applications · Statistics 2021-09-28 Antoine Bichat , Christophe Ambroise , Mahendra Mariadassou

This paper considers multidimensional jump type stochastic differential equations with super linear growth and non-Lipschitz coefficients. After establishing a sufficient condition for nonexplosion, this paper presents sufficient…

Probability · Mathematics 2018-10-05 Fubao Xi , Chao Zhu

This work focuses on a class of regime-switching jump diffusion processes, which is a two component Markov processes $(X(t),\Lambda(t))$, where $\Lambda(t)$ is a component representing discrete events taking values in a countably infinite…

Probability · Mathematics 2018-10-22 Fubao Xi , George Yin , Chao Zhu