A unified approach to standardized-residuals-based correlation tests for GARCH-type models
Yi-Ting Chen
Additional contact information
Yi-Ting Chen: Institute of Economics, Academia Sinica, Taipei, Taiwan, Postal: Institute of Economics, Academia Sinica, Taipei, Taiwan
Journal of Applied Econometrics, 2008, vol. 23, issue 1, 111-133
Abstract:
In this paper, we propose a unified approach to generating standardized-residuals-based correlation tests for checking GARCH-type models. This approach is valid in the presence of estimation uncertainty, is robust to various standardized error distributions, and is applicable to testing various types of misspecifications. By using this approach, we also propose a class of power-transformed-series (PTS) correlation tests that provides certain robustifications and power extensions to the Box-Pierce, McLeod-Li, Li-Mak, and Berkes-Horváth-Kokoszka tests in diagnosing GARCH-type models. Our simulation and empirical example show that the PTS correlation tests outperform these existing autocorrelation tests in financial time series analysis. Copyright © 2008 John Wiley & Sons, Ltd.
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://hdl.handle.net/10.1002/jae.985 Link to full text; subscription required (text/html)
http://qed.econ.queensu.ca:80/jae/2008-v23.1/ Supporting data files and programs (text/html)
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:jae:japmet:v:23:y:2008:i:1:p:111-133
Ordering information: This journal article can be ordered from
http://www3.intersci ... e.jsp?issn=0883-7252
DOI: 10.1002/jae.985
Access Statistics for this article
Journal of Applied Econometrics is currently edited by M. Hashem Pesaran
More articles in Journal of Applied Econometrics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().