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AIM 8: Explain how implied volatility can predict future volatility and discuss its advantages and disadvantages.

Approaches for estimating value-at-risk (VAR) can be based on the history of past returns or on current market data. The approach that focuses exclusively on current market data is:

A) the parametric approach.

B) the implied-volatility-based approach.

C) the hybrid approach.

D) the nonparametric approach. 

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The correct answer is B

The implied-volatility-based approach uses a derivatives pricing model such as the Black-Scholes option pricing model to estimate implied volatility based on current market data rather than historical data.


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AIM 9: Explain the implications of mean reversion in returns and return volatility, respectively have on VAR forecasts over long time horizons.

Which of the following statements regarding mean reversion is FALSE?

A) The single period conditional variance of the rate of change is 2.

B) The 2-period variance is calculated as (1+b2)2, where b is the rate of change in mean reversion. 

C) The long horizon risk is smaller than the square root volatility if mean reversion exists.

D) If the rate of change of mean reversion, b, is greater than one, the process is mean reverting.

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The correct answer is D

Under the context of mean reversion the single-period conditional variance of the rate of change is σ2. The 2-period variance is (1 + b2)σ2. If b = 1, the typical variance would occur as this represents a random walk. If b < 1, the process is mean reverting.


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AIM 10: Discuss the effects non-synchronous data has on estimating correlation and describe approaches that mitigate the impact of non-synchronous data on risk estimates.

1、Assume that the flow of information is constant and that returns are independent of one another. By what amount should the covariance term be inflated to adjust for nonsynchronous data between the New York Stock Exchange and the London Stock Exchange if there is a 6-hour lag between the market closing times?

A) 2.66.

B) 3.00.

C) 6.00.

D) 1.33.

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The correct answer is D

For a 24-hour period, there are 6 hours that overlap for the NYSE and London Stock Exchange. If we assume information is constant, we need to inflate the covariance by multiplying it by 1.33, calculated as follows:

 

 

 

[attach]13894[/attach]

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AIM 6: Compare and contrast the use of historic simulation, multivariate density estimation, and hybrid methods for volatility forecasting.

l =

0.96

 

 

K =

100

 

 

Rank

Ten Lowest Returns

Number of Past Periods

Hybrid Weight

1

-4.30%

7

0.0318

2

-3.90%

10

0.0282

3

-3.70%

15

0.0230

4

-3.50%

20

0.0187

5

-3.00%

17

0.0212

6

-2.90%

28

0.0135

7

-2.60%

32

0.0115

8

-2.50%

18

0.0203

9

-2.40%

55

0.0045

10

-2.30%

62

0.0034

The value at risk measure for the fifth percentile using the hybrid approach is closest to:

A)  –3.90%.

B)  –4.30%.

C)  –4.04%.

D)  –4.10%.

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The correct answer is C

The lowest and second lowest returns have cumulative weights of 3.18% and 6.00%, respectively. The point halfway between the two lowest returns is interpolated as –4.10% with a cumulative weight of 4.59% calculated as follows: –4.10% = (–4.30%+ –3.90%)/2; 4.59% = (3.18%+6.00%)/2. Further interpolation is required to find the fifth percentile VAR level with a return somewhere between –3.90% and –4.10%. The 5% VAR using the hybrid approach is calculated as: 4.10% – (4.10% – 3.90%)[(0.05 – 0.0459)/(0.06 – 0.0459)] = 4.10% – 0.20%[0.2908] = 4.04%.

l =

0.96

 

 

 

K =

100

 

 

 

Rank

Ten Lowest Returns

Number of Past Periods

Hybrid Weight

Hybrid Cumulative Weight

1

-4.30%

7

0.0318

0.0318

2

-3.90%

10

0.0282

0.0600

3

-3.70%

15

0.0230

0.0830

4

-3.50%

20

0.0187

0.1017

5

-3.00%

17

0.0212

0.1229

6

-2.90%

28

0.0135

0.1364

7

-2.60%

32

0.0115

0.1479

8

-2.50%

18

0.0203

0.1682

9

-2.40%

55

0.0045

0.1727

10

-2.30%

62

0.0034

0.1761

 

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