qingshu

 

The correct answer is B

GARCH(1,1) models have been shown to be useful in forecasting future volatility, which may indicate to an option trader the relative value of an option price.

qingshu

 

10、You estimate the following GARCH model:

σ2n = 0.04 + 0.30μ2t-1 + 0.50σ2n-1

If the most recent volatility estimate and error term are 0.15 and 0.02, respectively, the long-run average volatility is closest to:

A) 0.16.

B) 0.23.

C) 0.20.

D) 0.04.

qingshu

 

6、Which of the following statements regarding volatility in VAR models are TRUE? I. The RiskMetricsTM approach is very similar to the GARCH model. II. The historical standard deviation approach creates a variance-covariance matrix that is estimated under the assumption that all asset returns are normally distributed. III. The parametric approach typically assumes asset returns are normally or lognormally distributed with constant volatility. IV. Exponential smoothing methods and the historical standard deviation methods both apply a set of weights to recent past squared returns.

A) I, III, and IV.

B) I, II, and III.

C) I, II, and IV. 

D) II, III, and IV.

qingshu

 

The correct answer is C

The third statement is false. The parametric approach typically assumes asset returns are normally or lognormally distributed with time-varying volatility. The RiskMetricsTM approach is actually a special case of the GARCH model. Both the exponential and historical standard deviation approaches create a variance-covariance matrix that is estimated under the assumption that all asset returns are normally distributed. Exponential smoothing methods and the historical standard deviation methods both apply a set of weights to recent past squared returns. The difference is that in the historical standard deviation method all weights are equal whereas more recent returns are weighted more heavily in exponential methods.

qingshu

 

7、Which of the following is/are (an) advantage(s) of nonparametric methods compared to parametric methods for quantifying volatility? I. Nonparametric models require assumptions regarding the entire distribution of returns. II. Data is used more efficiently with nonparametric methods than parametric methods. III. Fat tails, skewness and other deviations from some assumed distribution are no longer a concern in the estimation process for nonparametric methods. IV. Multivariate density estimation (MDE) allows for weights to vary based on how relevant the data is to the current market environment by weighting the most recent data more heavily.

A) I and II.

B) I and III.

C) III only.

D) III and IV.

qingshu

 

The correct answer is C

Fat tails, skewness, and other deviations from some assumed distribution are no longer a concern in the estimation process for nonparametric methods. The other statements are false for the following reasons. Nonparametric models do not require assumptions regarding the entire distribution of returns. Data is used more efficiently with parametric methods than nonparametric methods. Multivariate density estimation (MDE) allows for weights to vary based on how relevant the data is to the current market environment, regardless of the timing of the most relevant data. MDE is also very flexible in introducing dependence on state variables.

qingshu

 

The correct answer is B

A parametric model typically assumes asset returns are normally or lognormally distributed with time-varying volatility. The other approaches do not require assumptions regarding the underlying asset return distribution.

qingshu

 

4、Which of the following derivative instruments could be classified as linear or approximately linear?

I.           Swaption

II.         Forward on commodity

III.        Interest rate cap

IV.      Futures on equity index

V.        Currency swap

A) II and IV.

B) I and III.

C) II, IV, and V.

D) II, III, and IV.

qingshu

 

The correct answer is C

The value of a linear derivative has a constant linear relationship with the underlying asset.  The relationship does not need to be one-to-one but it must be constant (or approximately constant) and linear.  Forwards, futures, and swaps are generally linear.  The value of a nonlinear derivative is a function of the change in the underlying asset and depends on the state of the underlying asset.  Options generally are nonlinear.

qingshu

 

5、The historical standard deviation approach differs from the RiskMetricsTM and GARCH approaches for estimating conditional volatility, because it:

A) is a parametric method.

B) places a lower weight on more recent data.

C) uses recent historical data.

D) applies a set of weights to past squared returns.