Abstract
AbstractWe prove asymptotically efficient inference results concerning an Ornstein–Uhlenbeck regression model driven by a non-Gaussian stable Lévy process, where the output process is observed at high frequency over a fixed period. The local asymptotics of non-ergodic type for the likelihood function is presented, followed by a way to construct an asymptotically efficient estimator through a suboptimal, yet very simple preliminary estimator.
Publisher
Springer Science and Business Media LLC
Subject
Computational Theory and Mathematics,Statistics and Probability
Reference23 articles.
1. Borovkova, S., & Schmeck, M. D. (2017). Electricity price modeling with stochastic time change. Energy Economics, 63, 51–65.
2. Brouste, A., & Masuda, H. (2018). Efficient estimation of stable Lévy process with symmetric jumps. Statistical Inference for Stochastic Processes, 21(2), 289–307.
3. Challis, C. J., & Schmidler, S. C. (2012). A stochastic evolutionary model for protein structure alignment and phylogeny. Molecular Biology and Evolution, 29(11), 3575–3587.
4. Cheridito, P., Kawaguchi, H., & Maejima, M. (2003). Fractional Ornstein-Uhlenbeck processes. Electronic Journal of Probability, 8(3), 14. electronic.
5. Clément, E., & Gloter, A. (2020). Joint estimation for SDE driven by locally stable Lévy processes. Electronic Journal of Statistics, 14(2), 2922–2956.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Gaussian quasi-information criteria for ergodic Lévy driven SDE;Annals of the Institute of Statistical Mathematics;2023-08-11