Small-sample autocorrelation structure for long-memory time series

Small-sample autocorrelation structure for long-memory time series

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Article ID: iaor1991761
Country: United Kingdom
Volume: 41
Issue: 8
Start Page Number: 735
End Page Number: 754
Publication Date: Aug 1990
Journal: Journal of the Operational Research Society
Authors:
Abstract:

This paper provides results on the behaviour of the sample autocorrelation function for an ARUMA model-that is, an ARIMA process in which the differencing operator (1-B)d is replaced by a more general real polynomial, Ud(B), having each of its zeros anywhere on the unit circle (subject to the restraint that complex zeros occur in conjugate pairs). Various simulated series are considered, and it is found empirically that the observed sample autocorrelations are in close agreement with appropriate ratios of limiting serial covariance expectations. This agreement is better than that with the theoretical autocorrelations, in the nearly non-stationary case, or the limits of the theoretical autocorrelations (as the homogeneous non-stationarity boundary is approached), in the non-stationary case. The paper also notes some striking features and distinctions in the serial correlation behaviour of processes, according to the position of the zero (or zeros) of Ud on the unit circle, and demonstrates the general considerable difference between the serial correlations of a non-stationary ARUMA model and a nearly non-stationary approximation to it, obtained by replacing the Ud(B) with Ud(αB), where α is a little (but appreciable bit) less than unity.

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