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Estimating autocorrelations in the presence of deterministic trends

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  • Hafner, Christian
  • Wang, Shin-Huei

Abstract

This 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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Suggested Citation

  • Hafner, Christian & Wang, Shin-Huei, 2011. "Estimating autocorrelations in the presence of deterministic trends," LIDAM Reprints ISBA 2011051, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2011051
    Note: In : Journal of Time Series Econometrics, vol. 3, no.2, p. 1-25 (2011)
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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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