Wavelet variance ratio cointegration test and wavestrapping

Burak Alparslan Eroğlu

Journal of Multivariate Analysis, 2019, vol. 171, issue C, 298-319

Abstract: In this paper, we propose a wavelet-based cointegration test for fractionally integrated time series. The proposed test is nonparametric and asymptotically invariant to different forms of short-run dynamics. The use of wavelets allows us to take advantage of the wavelet-based bootstrapping method mainly known as wavestrapping. In this regard, we introduce to the literature a new wavestrapping algorithm for multivariate time series processes specifically for cointegration tests. The Monte Carlo simulations indicate that this new wavestrapping procedure can alleviate the severe size distortions which we generally observe in cointegration tests with time series containing innovations that possess highly negative moving average roots.

Keywords: Cointegration; Fractional integration; Wavelet; Wavestrapping (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047259X18300988
Full text for ScienceDirect subscribers only

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:eee:jmvana:v:171:y:2019:i:c:p:298-319

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.jmva.2018.12.011

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().