Moving block bootstrapping for a CUSUM test for correlation change
Ji-Eun Choi and
Dong Wan Shin
Computational Statistics & Data Analysis, 2019, vol. 135, issue C, 95-106
Based on the test of Wied et al. (2012), we construct a bootstrapping CUSUM test for correlation change. The bootstrap test uses the bootstrap critical value obtained from the distribution of the moving block bootstrap samples. The asymptotic null distribution of the bootstrap test is shown to be the same as that of the original test. Consistency of the bootstrap test is proved under an alternative hypothesis of a correlation change. A Monte Carlo simulation shows that the proposed bootstrap test has a good size performance while the existing tests have serious size distortion for conditionally heteroscedastic samples and for serially correlated samples. The better size of the bootstrap test than the existing tests is achieved at the cost of some power loss in some cases.
Keywords: CUSUM test; Bootstrap test; Conditional heteroscedasticity; Serially correlation; Moving block bootstrapping (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:135:y:2019:i:c:p:95-106
Access Statistics for this article
Computational Statistics & Data Analysis is currently edited by S.P. Azen
More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().