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.
Beijing Normal UniversitySchool of economics and business administration
Citations
APA
Chicago
FWB
Hafner, C., & Wang, S.-H. (2011). Estimating Autocorrelations in the Presence of Deterministic Trends. Journal of Time Series Econometrics, 3(2), 1-23. https://doi.org/10.2202/1941-1928.1022 (Original work published 2011)