Parameter estimation for a discrete sampling of an intergrated Ornstein-Uhlenbeck process

DOI10.1080/02331880108802733zbMath0980.62072OpenAlexW2059908963WikidataQ126242882 ScholiaQ126242882MaRDI QIDQ2762606

Arnaud Gloter

Publication date: 19 February 2002

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331880108802733

zbMATH Keywords

diffusion processesdiscrete time observationsWhittle approximationminimum contrast

Mathematics Subject Classification ID

Related Items (18)

NONPARAMETRIC ESTIMATION OF SECOND-ORDER STOCHASTIC DIFFERENTIAL EQUATIONS ⋮ Unnamed Item ⋮ Characteristic function estimation of non-Gaussian Ornstein-Uhlenbeck processes ⋮ Change of spatiotemporal scale in dynamic models ⋮ Parameter estimation by contrast minimization for noisy observations of a diffusion process ⋮ Ergodicity and invariant measures for a diffusing passive scalar advected by a random channel shear flow and the connection between the Kraichnan-Majda model and Taylor-Aris dispersion ⋮ Parameter estimation for integrated Ornstein-Uhlenbeck processes with small Lévy noises ⋮ Variance reduction estimation for return models with jumps using gamma asymmetric kernels ⋮ Discrete sampling of an integrated diffusion process and parameter estimation of the diffusion coefficient ⋮ Estimation for a second-order jump diffusion model from discrete observations: application to stock market returns ⋮ Modeling financial time series through second-order stochastic differential equations ⋮ Asymptotics for theL^p-deviation of the variance estimator under diffusion ⋮ LAMN property for hidden processes: the case of integrated diffusions ⋮ Approximation of epidemic models by diffusion processes and their statistical inference ⋮ Convergence of integrated superpositions of Ornstein-Uhlenbeck processes to fractional Brownian motion ⋮ Adaptive estimation for degenerate diffusion processes ⋮ Bias Correction Estimation for a Continuous‐Time Asset Return Model with Jumps ⋮ Non Parametric Estimation of Second-Order Diffusion Equation by Using Asymmetric Kernels

Cites Work

• Time series: theory and methods.
• Consistent and asymptotically normal parameter estimates for hidden Markov models
• Martingale estimation functions for discretely observed diffusion processes
• Estimation of an Ergodic Diffusion from Discrete Observations
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Parameter estimation for a discrete sampling of an intergrated Ornstein-Uhlenbeck process