Which of the following conditions must hold for the autoregressive part of an ARMA model to be stationary?

A. Close to zero

B. Close to two

C. Close to four

D. Close to one

A. 0 and 0

B. 0 and 3

C. 3 and 0

D. Will vary from one normal distribution to another

A. It will be biased

B. It will be inconsistent

C. It will be inefficient

D. All of a, b and c will be true

A. A white noise process

B. A covariance stationary process

C. An autocorrelated process

D. A moving average process

A. 0.4

B. 0.34

C. 1

D. It is not possible to determine the value of the autocovariances without knowing the disturbance variance

A. Biased but consistent coefficient estimates

B. Biased and inconsistent coefficient estimates

C. Unbiased but inconsistent coefficient estimates

D. Unbiased and consistent but inefficient coefficient estimates

A. A slowly decaying acf, and a pacf with 3 significant spikes

B. A slowly decaying pacf and an acf with 3 significant spikes

C. A slowly decaying acf and pacf

D. An acf and a pacf with 3 significant spikes