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We consider the parametric estimation of the Ornstein-Uhlenbeck process driven by a non-Gaussian $\alpha$-stable L\'{e}vy process with the stable index $\alpha>1$ and possibly skewed jumps, based on a discrete-time sample over a fixed…

Statistics Theory · Mathematics 2026-01-28 Eitaro Kawamo , Hiroki Masuda

This paper builds a multivariate L\'evy-driven Ornstein-Uhlenbeck process for the management of non-maturing deposits, that are a major source of funding for banks. The contribution of the paper is both theoretical and operational. On the…

Risk Management · Quantitative Finance 2022-09-28 Marina Marena , Andrea Romeo , Patrizia Semeraro

We construct an estimator of the L\'evy density of a pure jump L\'evy process, possibly of infinite variation, from the discrete observation of one trajectory at high frequency. The novelty of our procedure is that we directly estimate the…

Probability · Mathematics 2020-04-06 Céline Duval , Ester Mariucci

We consider nonparametric statistical inference for L\'evy processes sampled irregularly, at low frequency. The estimation of the jump dynamics as well as the estimation of the distributional density are investigated. Non-asymptotic risk…

Statistics Theory · Mathematics 2015-11-23 Johanna Kappus

Ornstein-Uhlenbeck processes driven by general L\'{e}vy process are considered in this paper. We derive strongly consistent estimators for the moments of the underlying L\'{e}vy process and for the mean reverting parameter of the…

Probability · Mathematics 2010-11-30 Konstantinos Spiliopoulos

In this article, we study the problem of parameter estimation for a discrete Ornstein - Uhlenbeck model driven by Poisson fractional noise. Based on random walk approximation for the noise, we study least squares and maximum likelihood…

Statistics Theory · Mathematics 2017-12-15 Héctor Araya , Natalia Bahamonde , Tania Roa , Soledad Torres

The estimation of the L\'{e}vy density, the infinite-dimensional parameter controlling the jump dynamics of a L\'{e}vy process, is considered here under a discrete-sampling scheme. In this setting, the jumps are latent variables, the…

Statistics Theory · Mathematics 2011-04-25 José E. Figueroa-López

Given a sample from a discretely observed L\'evy process $X=(X_t)_{t\geq 0}$ of the finite jump activity, the problem of nonparametric estimation of the L\'evy density $\rho$ corresponding to the process $X$ is studied. An estimator of…

Statistics Theory · Mathematics 2018-04-17 Shota Gugushvili

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

The phenomenon of intermittency has been widely discussed in physics literature. This paper provides a model of intermittency based on L\'evy driven Ornstein-Uhlenbeck (OU) type processes. Discrete superpositions of these processes can be…

Probability · Mathematics 2016-10-12 Danijel Grahovac , Nikolai N. Leonenko , Alla Sikorskii , Irena Tešnjak

Existing results for the estimation of the L\'evy measure are mostly limited to the onedimensional setting. We apply the spectral method to multidimensional L\'evy processes in order to construct a nonparametric estimator for the…

Statistics Theory · Mathematics 2023-05-24 Maximilian F. Steffen

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

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

We suppose that a L\'evy process is observed at discrete time points. A rather general construction of minimum-distance estimators is shown to give consistent estimators of the L\'evy-Khinchine characteristics as the number of observations…

Statistics Theory · Mathematics 2008-05-29 Michael H. Neumann , Markus Reiss

We study nonparametric Bayesian statistical inference for the parameters governing a pure jump process of the form $$Y_t = \sum_{k=1}^{N(t)} Z_k,~~~ t \ge 0,$$ where $N(t)$ is a standard Poisson process of intensity $\lambda$, and $Z_k$ are…

Statistics Theory · Mathematics 2019-10-02 Richard Nickl , Jakob Söhl

We propose a non-Gaussian operator-valued extension of the Barndorff-Nielsen and Shephard stochastic volatility dynamics, defined as the square-root of an operator-valued Ornstein-Uhlenbeck process with Levy noise and bounded drift. We…

Probability · Mathematics 2015-06-25 Fred Espen Benth , Barbara Ruediger , Andre Suess

We investigate the problem of estimating the drift parameter of a high-dimensional L\'evy-driven Ornstein--Uhlenbeck process under sparsity constraints. It is shown that both Lasso and Slope estimators achieve the minimax optimal rate of…

Statistics Theory · Mathematics 2022-05-17 Niklas Dexheimer , Claudia Strauch

We examine the question of existence and uniqueness of evolution systems of measures for non-autonomous Ornstein-Uhlenbeck-type processes with jumps. In particular, we give examples where we explicitly compute the densities of such families…

Probability · Mathematics 2012-05-07 Robert Wooster

Assuming that a L\'evy-Driven Ornstein-Uhlenbeck (or CAR(1)) processes is observed at discrete times $0$, $h$, $2h$,$\cdots$ $[T/h]h$. We introduce a step-by-step methodological approach on how a person would verify the model assumptions.…

Applications · Statistics 2025-01-14 Ibrahim Abdelrazeq , Hardy Smith , Dinmukhammed Zhanbyrshy

Moving average processes driven by exponential-tailed L\'evy noise are important extensions of their Gaussian counterparts in order to capture deviations from Gaussianity, more flexible dependence structures, and sample paths with jumps.…

Statistics Theory · Mathematics 2023-08-01 Zhongwei Zhang , David Bolin , Sebastian Engelke , Raphaël Huser