Publication Type
Journal Article
Version
submittedVersion
Publication Date
9-2014
Abstract
We study two methods of adjusting for intraday periodicity of high-frequency financial data: the well-known Duration Adjustment (DA) method and the recently proposed Time Transformation (TT) method (Wu (2012)). We examine the effects of these adjustments on the estimation of intraday volatility using the Autoregressive Conditional Duration-Integrated Conditional Variance (ACD-ICV) method of Tse and Yang (2012). We find that daily volatility estimates are not sensitive to intraday periodicity adjustment. However, intraday volatility is found to have a weaker U-shaped volatility smile and a biased trough if intraday periodicity adjustment is not applied. In addition, adjustment taking account of trades with zero duration (multiple trades at the same time stamp) results in deeper intraday volatility smile.
Keywords
Autoregressive conditional duration model, Intraday volatility, Time transformation, Transaction data
Discipline
Econometrics | Economics | Finance
Research Areas
Econometrics
Publication
Journal of Empirical Finance
Volume
28
Issue
4
First Page
352
Last Page
361
ISSN
0927-5398
Identifier
10.1016/j.jempfin.2014.04.004
Publisher
Elsevier
Citation
TSE, Yiu Kuen and DONG, Yingjie.
Intraday periodicity adjustments of transaction duration and their effects on high-frequency volatility estimation. (2014). Journal of Empirical Finance. 28, (4), 352-361.
Available at: https://ink.library.smu.edu.sg/soe_research/1572
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.jempfin.2014.04.004