Câu hỏi: 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 1: 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 2: 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 3: If the number of non-zero eigenvalues of the pi matrix under a Johansen test is 2, this implies that

A. There are 2 linearly independent cointegrating vectors

B. There are at most 2 linearly independent cointegrating vectors

C. There are 3 variables in the system

D. There are at least 2 linearly independent cointegrating vectors

Câu 4: 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 5: If a series, yt, follows a random walk (with no drift), what is the optimal 1-step ahead forecast for y?

A. The current value of y

B. Zero

C. The historical unweighted average of y

D. An exponentially weighted average of previous values of y

Câu 6:  Which one of the following best describes most series of asset prices?

A. An independently and identically distributed (iid, i.e. “completely random”) process

B. A random walk with drift

C. An explosive process

D. A deterministic trend process