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We establish central limit theorems for the Sample Average Approximation (SAA) method in discrete-time, finite-horizon stochastic optimal control. Our analysis is based on an abstract limit theorem for stochastic backward recursions, which…

Optimization and Control · Mathematics 2026-04-21 Johannes Milz , Alexander Shapiro

We establish the global asymptotic equivalence between a pure jumps L\'evy process $\{X_t\}$ on the time interval $[0,T]$ with unknown L\'evy measure $\nu$ belonging to a non-parametric class and the observation of $2m^2$ Poisson…

Probability · Mathematics 2013-09-20 Pierre Étoré , Sana Louhichi , Ester Mariucci

We study the small-time asymptotics of sample paths of L\'evy processes and L\'evy-type processes. Namely, we investigate under which conditions the limit $$\limsup_{t \to 0} \frac{1}{f(t)} |X_t-X_0|$$ is finite resp.\ infinite with…

Probability · Mathematics 2021-10-11 Franziska Kühn

Approximations to sums of stationary and ergodic sequences by martingales are investigated. Necessary and sufficient conditions for such sums to be asymptotically normal conditionally given the past up to time 0 are obtained. It is first…

Probability · Mathematics 2007-05-23 Wei Biao Wu , Michael Woodroofe

We consider a generalization of a one-dimensional stochastic process known in the physical literature as L\'evy-Lorentz gas. The process describes the motion of a particle on the real line in the presence of a random array of marked points,…

Probability · Mathematics 2016-04-12 Alessandra Bianchi , Giampaolo Cristadoro , Marco Lenci , Marilena Ligabò

Regularly varying stochastic processes are able to model extremal dependence between process values at locations in random fields. We investigate the empirical extremogram as an estimator of dependence in the extremes. We provide conditions…

Statistics Theory · Mathematics 2017-04-11 Sven Buhl , Claudia Klüppelberg

In this article we focus on estimating the quadratic covariation of continuous semimartingales from discrete observations that take place at asynchronous observation times. The Hayashi-Yoshida estimator serves as synchronized realized…

Statistics Theory · Mathematics 2011-06-22 Markus Bibinger

We consider the problem of estimation of the drift parameter of an ergodic Ornstein--Uhlenbeck type process driven by a L\'evy process with heavy tails. The process is observed continuously on a long time interval $[0,T]$, $T\to\infty$. We…

Statistics Theory · Mathematics 2019-11-27 Alexander Gushchin , Ilya Pavlyukevich , Marian Ritsch

In this paper we consider convergence of moments in the small-time limit theorems for L\'evy processes. We provide precise asymptotics for all the absolute moments of positive order. The convergence of moments in limit theorems holds…

Probability · Mathematics 2022-04-26 Danijel Grahovac

The term noncentral moderate deviations is used in the literature to mean a class of large deviation principles that, in some sense, fills the gap between the convergence in probability to a constant (governed by a reference large deviation…

Probability · Mathematics 2025-04-29 Neha Gupta , Claudio Macci

This article presents a new continuous-time modelling framework for multivariate time series of counts which have an infinitely divisible marginal distribution. The model is based on a mixed moving average process driven by L\'{e}vy noise -…

Methodology · Statistics 2016-08-11 Almut E. D. Veraart

The determination of the time averages of continuous functions, or discrete time sequences is important for various problems in physics and engineering, and the generalized final-value theorems of the Laplace and z-transforms, relevant to…

Mathematical Physics · Physics 2012-07-25 Emanuel Gluskin , Shmuel Miller

We study dynamical systems arising as time-dependent compositions of Pomeau-Manneville-type intermittent maps. We establish central limit theorems for appropriately scaled and centered Birkhoff-like partial sums, with estimates on the rate…

Dynamical Systems · Mathematics 2020-01-14 Olli Hella , Juho Leppänen

In this paper we study the problem of constructing bootstrap confidence intervals for the L\'evy density of the driving L\'evy process based on high-frequency observations of a L\'evy-driven moving average processes. Using a spectral…

Statistics Theory · Mathematics 2022-11-15 D. Belomestny , E. Ivanova , T. Orlova

This paper considers a semiparametric approach within the general Bayesian linear model where the innovations consist of a stationary, mean zero Gaussian time series. While a parametric prior is specified for the linear model coefficients,…

Statistics Theory · Mathematics 2024-09-25 Claudia Kirch , Alexander Meier , Renate Meyer , Yifu Tang

The hierarchical Dirichlet process is a discrete random measure used as a prior in Bayesian nonparametrics and motivated by the study of groups of clustered data. We study the asymptotic behavior of the power sum symmetric polynomials for…

Probability · Mathematics 2025-08-29 Shui Feng , J. E. Paguyo

We study sums of independent and identically distributed random velocities in special relativity. We show that the resulting one-dimensional velocity distributions are not only stable under relativistic velocity addition but define a…

Statistical Mechanics · Physics 2025-12-03 Lucas G. B. de Souza , M. G. E. da Luz , E. P. Raposo , Evaldo M. F. Curado , G. M. Viswanathan

We establish a dichotomy in the small-time asymptotic behavior of the spectral heat content (SHC) for symmetric, but not necessarily isotropic, L\'evy processes whose L\'evy density satisfies a weak lower scaling condition near zero. This…

Probability · Mathematics 2025-08-13 Jaehun Lee , Hyunchul Park

We study whether a multivariate L\'evy-driven moving average process can shadow arbitrarily closely any continuous path, starting from the present value of the process, with positive conditional probability, which we call the conditional…

Probability · Mathematics 2017-05-16 Mikko S. Pakkanen , Tommi Sottinen , Adil Yazigi

We prove that a suitably de-biased version of Chatterjee's rank correlation based on i.i.d. copies of a random vector $(X,Y)$ is asymptotically normal whenever $Y$ is not almost surely constant. No further conditions on the joint…

Probability · Mathematics 2025-05-19 Marius Kroll
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