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

By Joel L. Horowitz, Ignacio N. Lobato, John C. Nankervis, Nathan Eugene Savin. 2006

95 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/167cfd73ee7362975db7328fa31feac21c018552

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Citations in the corpus

Multi-scale tests for serial correlation (2015, methodology): “Building on the block bootstrap inference for autocorrelations of Romano and Thombs (1996), Horowitz et al. (2006) develop a blocks-of-blocks bootstrap that reduces the error rejection probability to nearly zero for samples with at least 500 observations.”
Testing for high-dimensional white noise using maximum cross-correlations (2016, methodology): “Horowitz et al. (2006) proposed a double blockwise bootstrap method to test for white noise that is not independent and identically distributed.”
The Evolution of Stock Market Efficiency Over Time: A Survey of the Empirical Literature (2011, background): “In contrast, despite numerous methodological refinements to existing serial correlation tests (see, for example, Lobato et al., 2002; Horowitz et al., 2006) and spectral-based tests (see, for example, Durlauf, 1991; Deo, 2000), we do not find any applications of these improved statistical tools on…”
Testing for linear vector autoregressive dynamics under multivariate generalized autoregressive heteroskedasticity (2009, methodology): “Horowitz et al. (2006) use a double blocks-of-blocks bootstrap procedure to test for serial autocorrelation.”
An Automatic Portmanteau Test for Serial Correlation (2009, methodology): “These tests were initially proposed by Neyman (1937) in the context of goodness-of-t of distributions, and since then, a plethora of research has developed, see, for instance, Rayner and Best (1989), Eubank and Hart (1992), Ledwina (1994), Fan (1996), Inglot and Ledwina (1996), Kallenberg and Ledwi”
Are US stock index returns predictable? Evidence from automatic autocorrelation-based tests (2013, methodology): “Pierce test (recent studies include Horowitz et al., 2006; Kan and Wang, 2010). In spite of this, since the seminal work of Lo and MacKinlay (1988), the VR tests remain popular among investigators in empirical finance research.”
Bootstrap Methods in Econometrics (2006, unknown): “See Horowitz et al. (2006).”
White Noise Testing and Model Diagnostic Checking for Functional Time Series (2016, methodology): “…some commonly used test statistics, such as Box and Pierce’s portmanteau test, are obtained under the i.i.d assumption, and they are no longer valid under the assumption of dependent white noise (Romano and Thombs, 1996; Lobato et al., 2002; Francq et al., 2005; Horowitz et al., 2006; Shao, 2011b).”
A bootstrap-assisted spectral test of white noise under unknown dependence (2011, background): “Testing for white noise, or lack of serial correlation, is a classical problem in time series analysis and it is an integral part of the Box–Jenkins linear modeling framework.”