Author:
Lobato I.N.,Nankervis John C.,Savin N.E.
Abstract
The problem addressed in this paper is to test the null hypothesis
that a time series process is uncorrelated up to lag K
in the presence of statistical dependence. We propose an extension
of the Box–Pierce Q-test that is asymptotically
distributed as chi-square when the null is true for a very general
class of dependent processes that includes non-martingale
difference sequences. The test is based on a consistent estimator
of the asymptotic covariance matrix of the sample autocorrelations
under the null. The finite sample performance of this extension
is investigated in a Monte Carlo study.
Publisher
Cambridge University Press (CUP)
Subject
Economics and Econometrics,Social Sciences (miscellaneous)
Cited by
71 articles.
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