Câu hỏi: Consider the following picture and suggest the model from the following list that best characterises the process:

A. An AR(1)

B. An AR(2)

C. An ARMA(1,1)

D. An MA(3)

Câu 1: Which of the following sets of characteristics would usually best describe an autoregressive process of order 3 (i.e. an AR(3))?

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

Câu 2: What is the optimal three-step ahead forecast from the AR(2) model given in question 14?

A. -0.1

B. 0.27

C. -0.34

D. -0.31

Câu 3: A normal distribution has coefficients of skewness and excess kurtosis which are respectively:

A. 0 and 0

B. 0 and 3

C. 3 and 0

D. Will vary from one normal distribution to another

Câu 4: A process, xt, which has a constant mean and variance, and zero autocovariance for all non-zero lags is best described as:

A. A white noise process

B. A covariance stationary process

C. An autocorrelated process

D. A moving average process

Câu 5: If there are three variables that are being tested for cointegration, what is the maximum number of linearly independent cointegrating relationships that there could be?

A. 0

B. 1

C. 2

D. 3

Câu 6: Which of the following conditions must hold for the autoregressive part of an ARMA model to be stationary?

A. All roots of the characteristic equation must lie outside the unit circle

B. All roots of the characteristic equation must lie inside the unit circle

C. All roots must be smaller than unity

D. At least one of the roots must be bigger than one in absolute value