A NEW METHOD FOR OBTAINING THE AUTOCOVARIANCE OF AN ARMA MODEL: AN EXACT FORM SOLUTION

1998 ◽  
Vol 14 (5) ◽  
pp. 622-640 ◽  
Author(s):  
M. Karanasos

In this article we present a new method for computing the theoretical autocovariance function of an autoregressive moving average model. The importance of our theorem is that it yields two interesting results: First, a closed-form solution is derived in terms of the roots of the autoregressive polynomial and the parameters of the moving average part. Second, a sufficient condition for the lack of model redundancy is obtained.

1998 ◽  
Vol 14 (3) ◽  
pp. 326-338 ◽  
Author(s):  
B.P.M. McCabe ◽  
S.J. Leybourne

This paper investigates the behavior of the maximum likelihood estimator of a Gaussian autoregressive moving average model with a unit root in the moving average polynomial. The results are primarily of interest in testing hypotheses that involve moving average unit roots as, for example, when testing for stationarity of a series.


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