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Efficient maximum likelihood estimation for Lévy-driven Ornstein-Uhlenbeck processes
| Content Provider | Semantic Scholar |
|---|---|
| Author | Mai, Hans Peter |
| Copyright Year | 2012 |
| Abstract | We consider the problem of efficient estimation of the drift parameter of an Ornstein-Uhlenbeck type process driven by a Lévy process when high-frequency observations are given. The estimator is constructed from the time-continuous likelihood function that leads to an explicit maximum likelihood estimator and requires knowledge of the continuous martingale part. We use a thresholding technique to approximate the continuous part of the process. Under suitable conditions we prove asymptotic normality and efficiency in the Hájek-Le Cam sense for the resulting drift estimator. To obtain these results we prove an estimate for the Markov generator of a pure jump Lévy process. Finally, we investigate the finite sample behavior of the method and compare our approach to least squares estimation. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://edok01.tib.uni-hannover.de/edoks/e01fn13/727023152.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Approximation algorithm Least squares Likelihood Functions Markov chain Normality Unit Phenylephrine Hydrochloride 10 MG Oral Tablet Population Parameter Severo Ornstein Thresholding (image processing) chorioallantoic membrane |
| Content Type | Text |
| Resource Type | Article |
