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: 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 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

Câu 3: 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 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: A normal distribution has coefficients of skewness and excess kurtosis which are respectively:

A. 0 and 0

B. 0 and 3

C. 3 and 0

D. Will vary from one normal distribution to another

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