Câu hỏi: 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

Câu 1:  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 2: 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 3: 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 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 a regression equation contains an irrelevant variable, the parameter estimates will be

A. Consistent and unbiased but inefficient

B. Consistent and asymptotically efficient but biased

C. Inconsistent

D. Consistent, unbiased and efficient

Câu 6: 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