Câu hỏi: 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 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
30/08/2021 8 Lượt xem
Câu 2: 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
30/08/2021 9 Lượt xem
Câu 3: 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
30/08/2021 9 Lượt xem
Câu 4: 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
30/08/2021 7 Lượt xem
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
30/08/2021 7 Lượt xem
Câu 6: 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
30/08/2021 8 Lượt xem

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