93 câu trắc nghiệm Kinh tế lượng – Phần 2

KTL_002_C8_1: What would typically be the shape of the news impact curve for a series that exactly followed a GARCH (1,1) process?

○ It would be asymmetric, with a steeper curve on the left than the right
○ It would be asymmetric, with a steeper curve on the right than the left
● It would be symmetric about zero
○ It would be discontinuous about zero

KTL_002_C8_2: Which of the following are NOT features of an IGARCH(1,1) model?
(i) Forecasts of the conditional variance will converge upon the unconditional variance as the horizon tends to infinity
(ii) The sum of the coefficients on the lagged squared error and the lagged conditional variance will be unity
(iii) Forecasts of the conditional variance will decline gradually towards zero as the horizon tends to infinity
(iv) Such models are never observed in reality

● (ii) only
○ (ii) and (iv) only
○ (ii), (iii) and (iv) only
○ (i), (ii), (iii) and (iv)

KTL_002_C8_3: Which of the following would represent the most appropriate definition for implied volatility?
● It is the volatility of the underlying asset’s returns implied from the price of a traded option and an option pricing model
○ It is the volatility of the underlying asset’s returns implied from a statistical model such as GARCH
○ It is the volatility of an option price implied from a statistical model such as GARCH
○ It is the volatility of an option price implied from the underlying asset volatility

KTL_002_C8_41: 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?
○ The price range (high minus low) on that day
○ The squared return on that day
● The sum of the squares of hourly returns on that day
○ The squared return on the previous day

KTL_002_C8_5: Suppose that a researcher wishes to test for calendar (seasonal) effects using a dummy variables approach. Which of the following regressions could be used to examine this?
(i) A regression containing intercept dummies
(ii) A regression containing slope dummies
(iii) A regression containing intercept and slope dummies
(iv) A regression containing a dummy variable taking the value 1 for one observation and zero for all others

○ (ii) and (iv) only
○ (i) and (iii) only
● (i), (ii), and (iii) only
○ (i), (ii), (iii), and (iv).

KTL_002_C8_6: Which of the following is the most plausible test regression for determining whether a series y contains “ARCH effects”?
○ \(y_t^2 = {\alpha _0} + {\alpha _1}y{}_{t – 1} + {\alpha _2}y{}_{t – 2} + {\alpha _3}y{}_{t – 3} + {\alpha _4}y{}_{t – 4} + {\alpha _5}y{}_{t – 5} + {u_t}\)
● \(y_t^2 = {\alpha _0} + {\alpha _1}y{{}_{t – 1}^2} + {\alpha _2}y{{}_{t – 2}^2} + {\alpha _3}y{{}_{t – 3}^2} + {\alpha _4}y{{}_{t – 4}^2} + {\alpha _5}y{{}_{t – 5}^2} + {u_t}\)
○ \(y_t^{} = {\alpha _0} + {\alpha _1}y{{}_{t – 1}^2} + {\alpha _2}y{{}_{t – 2}^2} + {\alpha _3}y{{}_{t – 3}^2} + {\alpha _4}y{{}_{t – 4}^2} + {\alpha _5}y{{}_{t – 5}^2} + {u_t}\)
○ \(y_t^{} = {\alpha _0} + {\alpha _1}y{{}_{t – 1}^2} + {\alpha _2}y{{}_{t – 2}^3} + {\alpha _3}y{{}_{t – 3}^4} + {\alpha _4}y{{}_{t – 4}^5} + {\alpha _5}y{{}_{t – 5}^6} + {u_t}\)

KTL_002_C8_7: Consider the following conditional variance equation for a GJR model.
\({h_t} = {\alpha _0} + {\alpha _1}u_{t – 1}^2 + \beta {h_{t – 1}} + \gamma u_{t – 1}^2{I_{t – 1}}\)
where \({I_{t – 1}}\) = 1 if \({u_{t – 1}}\) < 0
= 0 otherwise
For there to be evidence of a leverage effect, which one of the following conditions must hold?
○ \({\alpha _0}\) positive and statistically significant
● \(\gamma \) positive and statistically significant
○ \(\gamma \) statistically significantly greater than \({\alpha _0}\)
○ \({\alpha _1} + \beta $$ statistically significantly less than \(\gamma \)

KTL_002_C8_8: Consider the three approaches to conducting hypothesis tests under the maximum likelihood framework. Which of the following statements are true?
(i) The Wald test is based on estimation only under the null hypothesis
(ii) The likelihood ratio test is based on estimation under both the null and the alternative hypotheses
(iii) The lagrange multiplier test is based on estimation under the alternative hypothesis only
(iv) The usual t and F-tests are examples of Wald tests

● (ii) and (iv) only
○ (i) and (iii) only
○ (i), (ii), and (iv) only
○ (i), (ii), (iii), and (iv)

KTL_002_C8_9: If a series possesses the “Markov property”, what would this imply?
(i) The series is path-dependent
(ii) All that is required to produce forecasts for the series is the current value of the series plus a transition probability matrix
(iii) The state-determining variable must be observable
(iv) The series can be classified as to whether it is in one regime or another regime, but it can only be in one regime at any one time

● (ii) only
○ (i) and (ii) only
○ (i), (ii), and (iii) only
○ (i), (ii), (iii), and (iv)

KTL_002_C8_10: Which one of the following problems in finance could not be usefully addressed by either a univariate or a multivariate GARCH model?
○ Producing option prices
○ Producing dynamic hedge ratios
○ Producing time-varying beta estimates for a stock
● Producing forecasts of returns for use in trading models
○ Producing correlation forecasts for value at risk models