Abstract
The occurrence‐50 of economic policies and other sudden and large shocks often bring out jumps in financial data, which can be characterized through continuous‐time jump‐diffusion model. In this article, we present the double smoothed non‐parametric approach for infinitesimal conditional volatility of jump‐diffusion model based on high frequency data. Under certain minimal conditions, we obtain the strong consistency and asymptotic normality for the estimator as the time span T → ∞ and the sample interval . The procedure and asymptotic behavior can be applied for both Harris recurrent and positive Harris recurrent processes. The finite sample properties of the underlying double smoothed volatility estimator are verified through Monte Carlo simulation and Shanghai Interbank Offered Rate in China for application.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
