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: Which criticism of Dickey-Fuller (DF) -type tests is addressed by stationarity tests, such as the KPSS test?

A. DF tests have low power to reject the null hypothesis of a unit root, particularly in small samples

B.  DF tests are always over-sized

C. DF tests do not allow the researcher to test hypotheses about the cointegrating vector

D. DF tests can only find at most one cointegrating relationship

Câu 2:  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 3: If the residuals of a model containing lags of the dependent variable are autocorrelated, which one of the following could this lead to?

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

Câu 4: If a residual series is negatively autocorrelated, which one of the following is the most likely value of the Durbin Watson statistic?

A. Close to zero

B. Close to two

C. Close to four

D. Close to one

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