Câu hỏi: 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 1: What would be the consequences for the OLS estimator if autocorrelation is present in a regression model but ignored?

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

Câu 2: 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 3: 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 4:  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

Câu 5: 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 6: 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