Estimating Autocorrelations in the Presence of Deterministic Trends
AbstractThis paper considers the impact of ordinary least squares (OLS) detrending and the first difference (FD) detrending on autocorrelation estimation in the presence of long memory and deterministic trends. We show that the FD detrending results in inconsistent autocorrelation estimates when the error term is stationary. Thus, the FD detrending should not be employed for autocorrelation estimation of the detrended series when constructing e.g. portmanteau-type tests. In an empirical application of volume in Dow Jones stocks, we show that for some stocks, OLS and FD detrending result in substantial differences in ACF estimates.
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Bibliographic InfoArticle provided by De Gruyter in its journal Journal of Time Series Econometrics.
Volume (Year): 3 (2011)
Issue (Month): 2 (April)
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Web page: http://www.degruyter.com
Other versions of this item:
- Wang, Shin-Huei & Hafner, Christian, 2008. "Estimating autocorrelations in the presence of deterministic trends," CORE Discussion Papers 2008073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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