An automatic Portmanteau test for serial correlation

Juan Carlos Escanciano and Ignacio Lobato

Journal of Econometrics, 2009, vol. 151, issue 2, 140-149

Abstract: This article introduces a data-driven Box-Pierce test for serial correlation. The proposed test is very attractive compared to the existing ones. In particular, implementation of this test is extremely simple for two reasons: first, the researcher does not need to specify the order of the autocorrelation tested, since the test automatically chooses this number; second, its asymptotic null distribution is chi-square with one degree of freedom, so there is no need of using a bootstrap procedure to estimate the critical values. In addition, the test is robust to the presence of conditional heteroskedasticity of unknown form. Finally, the proposed test presents higher power in simulations than the existing ones for models commonly employed in empirical finance.

Keywords: Autocorrelation; Consistency; Power; Akaike's; AIC; Schwarz's; BIC (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (137)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:151:y:2009:i:2:p:140-149

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