Which among the following is not a noncomparative scaling technique?

Which among the following is not comparative scaling technique?

The interval scale possesses all of the below properties, except:

Problem identification research is undertaken to:

The process of marketing involves all of the following EXCEPT:

Suppose that a researcher wanted to obtain an estimate of realised (“actual”) volatility. Which one of the following is likely to be the most accurate measure of volatility of stock returns for a particular day?

Which of the following would represent the most appropriate definition for implied volatility?

What would typically be the shape of the news impact curve for a series that exactly followed a GARCH (1,1) process?

Consider the testing of hypotheses concerning the cointegrating vector(s) under the Johansen approach. Which of the following statements is correct?

If a Johansen “max” test for a null hypothesis of 1 cointegrating vectors is applied to a system containing 4 variables is conducted, which eigenvalues would be used in the test?

If the number of non-zero eigenvalues of the pi matrix under a Johansen test is 2, this implies that

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?

Which one of the following best describes most series of asset prices?

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

What is the optimal three-step ahead forecast from the AR(2) model given in question 14?

Consider the following picture and suggest the model from the following list that best characterises the process:

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?

If a series, yt, follows a random walk (with no drift), what is the optimal 1-step ahead forecast for y?

If a series, yt, follows a random walk (with no drift), what is the optimal 1-step ahead forecast for y?

If a series, yt, follows a random walk (with no drift), what is the optimal 1-step ahead forecast for y?

Which of the following conditions must hold for the autoregressive part of an ARMA model to be stationary?

A process, xt, which has a constant mean and variance, and zero autocovariance for all non-zero lags is best described as:

Which of the following sets of characteristics would usually best describe an autoregressive process of order 3 (i.e. an AR(3))?

If a regression equation contains an irrelevant variable, the parameter estimates will be

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

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

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

Which of the following would probably NOT be a potential “cure” for non-normal residuals?

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

Which of the following would you expect to be a problem associated with adding lagged values of the dependent variable into a regression equation?

Which of the following is NOT a good reason for including lagged variables in a regression?

The value of the Durbin Watson test statistic in a regression with 4 regressors (including the constant term) estimated on 100 observations is 3.6. What might we suggest from this?

Which of the following would NOT be a potential remedy for the problem of multicollinearity between regressors?

What is the relationship, if any, between t-distributed and F-distributed random variables?

Which of the following is the correct value for?

Consider a standard normally distributed variable, a t-distributed variable with d degrees of freedom, and an F-distributed variable with (1, d) degrees of freedom. Which of the following statements is FALSE?

What is the relationship, if any, between the normal and t-distributions?

Consider an increase in the size of the test used to examine a hypothesis from 5% to 10%. Which one of the following would be an implication?

Two researchers have identical models, data, coefficients and standard error estimates. They test the same hypothesis using a two-sided alternative, but researcher 1 uses a 5% size of test while researcher 2 uses a 10% test. Which one of the following statements is correct?

Which of the following is the most accurate definition of the term “the OLS estimator”?

Which one of the following is NOT an assumption of the classical linear regression model?

Which of the following is NOT correct with regard to the p-value attached to a test statistic?

Which of the following is NOT a good reason for including a disturbance term in a regression equation?

Which of the following statements is correct concerning the conditions required for OLS to be a usable estimation technique?

Which of the following is a correct interpretation of a “95% confidence interval” for a regression parameter?

The type I error associated with testing a hypothesis is equal to:

What result is proved by the Gauss-Markov theorem?

Suppose that we wanted to sum the 2007 returns on ten shares to calculate the return on a portfolio over that year. What method of calculating the individual stock returns would enable us to do this?

The numerical score assigned to the credit rating of a bond is best described as what type of number?

Vì sao phải sử dụng ước lượng chính là phần dư?