Limit Theorems for Power Variations of Pure-Jump Processes with Application to Activity Estimation
This paper derives the asymptotic behavior of realized power variation of pure-jump It^o semimartingales as the sampling frequency within a fixed interval increases to infinity. We prove convergence in probability and an associated central limit theorem for the realized power variation as a function of its power. We apply the limit theorems to propose an e±cient adaptive estimator for the activity of discretely-sampled It^o semimartingale over a fixed interval.
|Date of creation:||2010|
|Contact details of provider:|| Postal: Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097|
Phone: (919) 660-1800
Fax: (919) 684-8974
Web page: http://econ.duke.edu/
When requesting a correction, please mention this item's handle: RePEc:duk:dukeec:10-74. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Department of Economics Webmaster)
If references are entirely missing, you can add them using this form.