Câu hỏi: Which of the following would probably NOT be a potential “cure” for non-normal residuals?

A. Transforming two explanatory variables into a ratio

B. Removing large positive residuals

C. Using a procedure for estimation and inference which did not assume normality

D. Removing large negative residuals

Câu 1: 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 2: 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 3: 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 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: Consider a series that follows an MA(1) with zero mean and a moving average coefficient of 0.4. What is the value of the autocorrelation function at lag 1?

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

Câu 6: 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