Publication Type
Journal Article
Version
acceptedVersion
Publication Date
1-2024
Abstract
We present a general framework for optimal nonparametric spot volatility estimation based on intraday range data, comprised of the first, highest, lowest, and last price over a given time-interval. We rely on a decision-theoretic approach together with a coupling-type argument to directly tailor the form of the nonparametric estimator to the specific volatility measure of interest and relevant loss function. The resulting new optimal estimators offer substantial efficiency gains compared to existing commonly used range-based procedures.
Keywords
spot volatility, nonparametric estimation, range-based estimation, high-frequency data, decision theory
Discipline
Econometrics | Finance
Research Areas
Econometrics
Publication
Journal of Econometrics
Volume
238
Issue
1
First Page
1
Last Page
18
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2023.105548
Publisher
Elsevier
Citation
BOLLERSLEV, Tim; LI, Jia; and LI, Qiyuan.
Optimal nonparametric range-based volatility estimation. (2024). Journal of Econometrics. 238, (1), 1-18.
Available at: https://ink.library.smu.edu.sg/soe_research/2646
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.jeconom.2023.105548