Double Smoothed Volatility Estimation of Potentially Non‐stationary Jump‐diffusion Model of Shibor
Yuping Song,
Weijie Hou and
Zhengyan Lin
Journal of Time Series Analysis, 2022, vol. 43, issue 1, 53-82
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 Δn→0. 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.
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1111/jtsa.12592
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:43:y:2022:i:1:p:53-82
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0143-9782
Access Statistics for this article
Journal of Time Series Analysis is currently edited by M.B. Priestley
More articles in Journal of Time Series Analysis from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().