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Bootstrapping the Box–Pierce Q test: A robust test of uncorrelatedness

Journal of EconometricsPublished 23 August 2005
Joël L. Horowitz, Ignacio N. Lobato, John C. Nankervis, N. E. Savin
Citations88
SJR quartileQ1
SJR score12.17
SNIP4.85

Abstract

This paper describes a test of the null hypothesis that the first K autocorrelations of a covariance stationary time series are zero in the presence of statistical dependence. The test is based on the Box–Pierce Q statistic with bootstrap-based P-values. The bootstrap is implemented using a double blocks-of-blocks procedure with prewhitening. The finite sample performance of the bootstrap Q test is investigated by simulation. In our experiments, the performance is satisfactory for samples of n=500. At this sample size, the differences between the empirical and nominal rejection probabilities are essentially eliminated.

Keywords

Decision SciencesEconomics, Econometrics and Finance