The least squares estimation for the \(\alpha\)-stable Ornstein-Uhlenbeck process with constant drift
From MaRDI portal
Publication:2176362
DOI10.1007/S11009-018-9654-ZzbMath1447.60085OpenAlexW2889215085MaRDI QIDQ2176362
Publication date: 4 May 2020
Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11009-018-9654-z
asymptotic distributionconsistencyOrnstein-Uhlenbeck processleast squares estimation\(\alpha\)-stable motion
Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Strong limit theorems (60F15) Stable stochastic processes (60G52)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Least squares estimators for stochastic differential equations driven by small Lévy noises
- Parameter estimation for a class of stochastic differential equations driven by small stable noises from discrete observations
- On the singularity of least squares estimator for mean-reverting \(\alpha\)-stable motions
- On Itô stochastic integration with respect to p-stable motion: Inner clock, integrability of sample paths, double and multiple integrals
- Statistical inference for ergodic diffusion processes.
- The central limit theorem for stochastic integrals with respect to Levy processes
- A least squares estimator for discretely observed Ornstein-Uhlenbeck processes driven by symmetric \(\alpha \)-stable motions
- Least squares estimator for Ornstein-Uhlenbeck processes driven by \(\alpha \)-stable motions
- Asymptotic properties of estimators in a stable Cox-Ingersoll-Ross model
- Parameter estimation in stochastic differential equations.
- Simulation and inference for stochastic differential equations. With R examples.
This page was built for publication: The least squares estimation for the \(\alpha\)-stable Ornstein-Uhlenbeck process with constant drift