Reference no: EM132798237

Investment Management (Risk Measurement and Analysis)

[Hull]: John Hull, Risk Management and Financial Institutions, 4th Edition (John Wiley & Sons, 2015).

1. [Lecture 5] Johanna Roberto has collected a data set of 1,000 daily observations on equity returns. She is concerned about the appropriateness of using parametric techniques as the data appears skewed. Ultimately, she decides to use historical simulation and bootstrapping to estimate the 5% VaR. Which of the following steps is most likely to be part of the estimation procedure?

a. Filter the data to remove the obvious outliers.

b. Repeated sampling with replacement.

c. Identify the tail region from reordering the original data.

d. Apply a weighting procedure to reduce the impact of older data.

2. [Lecture 5] All of the following approaches improve the traditional historical simulation approach for estimating VaR except the:

a. Volatility-weighted historical simulation.

b. Age-weighted historical simulation.

c. Value-weighted historical simulation.

d. Correlation- weighted historical simulation.

3. [Lecture 5] Which of the following statements is FALSE?

a. Age-weighted historical simulation deals with the issue that all historical observations are given equal weights regardless their age.

b. Volatility-weighted historical simulation deals with the issue that historical observations with various levels of volatility are given equal weights regardless the current volatility level.

c. The filtered HS method uses bootstrapping and incorporates rich volatility modeling (e.g. GARCH).

d. Empirical evidence suggests that age-weighted historical simulation produces superior VaR estimates to the volatility-weighted one.

4. [Lecture 5] Which of the following statements about volatility-weighting is true?

a. Historic returns are adjusted, and the VaR calculation is more complicated.

b. Historic returns are adjusted, and the VaR calculation procedure is the same.

c. Current period returns are adjusted, and VaR calculation is more complicated.

d. Current period returns are adjusted, and VaR calculation is the same.

5. [Lecture 5] Which of the following statements is true?

a. The non-parametric approach makes specific assumption about the distribution of asset returns.

b. The parametric approach makes no specific assumption about the distribution of asset returns.

c. Bootstrapping improves the precision of the sample estimates.

d. Monte Carlo simulation is not as powerful as parametric or non-parametric approaches.

6. [Lecture 5] Assuming normal distribution, which of the following statement regarding confidence interval of VaR estimators is FALSE?

a. Wider confidence interval indicates lower precision of the VaR estimator.

b. Confidence interval of VaR estimator narrows when sample size increases.

c. Higher confidence level of VaR leads to wider confidence interval of the VaR estimator.

d. When using the quantile-standard-error approach to estimate the confidence interval of VaR estimators, small sample size generally leads to more reliable results.