Publication Type

Journal Article

Version

Preprint

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

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1016/j.jempfin.2014.04.004

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