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2、When using a Value-at-Risk (VaR) model in the loss distribution approach, a higher confidence level would:

A) increase the importance on modeling the tails and requires the use of both internal and external data.
 
B) decrease the importance on modeling the tails but requires the use of both internal and external data
 
C) decrease the importance on modeling the tails and only allow the use of only internal data.
 
D) increase the importance on modeling the tails and requires the use of only internal data.
 

nayizhenfeng

The correct answer is A

A high confidence level, i.e., 99.98%, places a great deal of importance on modeling the tails of the loss distributions correctly and requires the use of both internal and external data.

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3、A bank simulates the distribution of its operational losses. It finds that the loss that corresponds to the 99th percentile of potential losses is $250,000 and the mean of the distribution is $30,000. An estimate of operational risk economic capital is closest to:

A) $30,000.
 
B) $220,000.
 
C) $250,000.
 
D) $270,000.

nayizhenfeng

The correct answer is B

Operational risk economic capital is the difference between the loss at a given confidence level and the expected loss. In this case, $250,000 ? $30,000 = $220,000.

nayizhenfeng

AIM 13: Describe the analysis and validation of loss distribution approaches, including the loss distribution, sensitivity analysis, stress testing, back testing and benchmarking.

 

1、Which of the following best describes concerns with respect to data and risk-sensitive measures in the validation processes for estimates of regulatory and economic capital using the loss distribution approach?

A) Data problems and the lack of a risk-sensitive measure for operational risk modeling complicate the problem. Thus, there is inherent uncertainty in the validation process, and expert judgment should complement quantitative measures.
 
B) Data gathering techniques have improved, and there is now an established risk-sensitive measure for operational risk modeling. Therefore, validation processes should largely depend upon quantitative measures and not subjective expert judgment.
 
C) There are data problems, but there is an established risk-sensitive measure for operational risk modeling. Thus, there still is inherent uncertainty in the validation process, and expert judgment should complement quantitative measures.
 
D) Data problems and the lack of a risk-sensitive measure for operational risk modeling complicate the problem to such an extent that validation processes are useless.

nayizhenfeng

The correct answer is A

To show that the estimates for regulatory and economic capital are reasonable, there should be a validation process. Given that confidence levels are often high, this can be challenging. Data problems and the lack of a risk-sensitive measure for operational risk modeling complicate the problem. Thus, there is inherent uncertainty in the validation process, and expert judgment should complement quantitative measures.

nayizhenfeng

2、The validation of an operational risk model involves which of the following?

A review of data inputs, model methodology, and model outputs.
An examination of the assumed frequencies, severities, and dependence structure.
An examination of the role of insurance.
An examination of the assumptions in the model such as correlations.
A) II, III, and IV only.
 
B) I, II, and IV only.
 
C) II and IV only.
 
D) I, II, III, and IV.

nayizhenfeng

The correct answer is D

The validation of an operational risk model involves a review of data inputs, model methodology, and model outputs. The review of the model would include examining the assumed frequencies, severities, dependence structure and insurance as well as assumptions in the model such as correlations. The validation would include an assessment of the impact of different modeling assumptions and the sensitivity of capital requirements to parameter changes.

nayizhenfeng

3、In the loss distribution approach, backtesting a model:

A) is recommended; however, it cannot fully validate the model because the capital requirements represent extreme losses.
 
B) is not recommended because it is time consuming, and the models should be forward looking.
 
C) is not recommended because unrealized potential losses are not included in observed data.
 
D) is recommended, straightforward and valid given that it uses observed data.

nayizhenfeng

The correct answer is A

The researcher should backtest the model to see how well it represents what has occurred. Unfortunately, with respect to operational risk, data problems are an issue. In validating a loss distribution model, a good approach is to backtest the capital estimates against actual annual losses; however, this cannot fully validate the model because the capital requirements represent extreme losses.