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Arisk analyst is comparing the use of parametric and non-parametric approaches for calculating VaR and is concerned about some of the characteristics present in the loss data. Which of the following distribution characteristics would make parametric approaches the favored method to use?>>>点击领取2021年FRM备考资料大礼包（戳我免·费领取）

A) Skewness in the distribution

B) Fat tails in the distribution

C) Scarcity of high magnitude loss events.

D) Heteroskedasticity in the distribution

答案：C

解析：Non-parametric approaches can accommodate fat tails, skewness, and any other non-normal features that can cause problems for parametric approaches. However, if the data period that is used in estimation includes few losses or losses with low magnitude, non-parametric methods will often produce risk measures that are too low. Hence, parametric methods would be more appropriate in those situations.

All of the following items are generally considered advantages of non-parametric estimation methods except:

A) Ability to accommodate skewed data.

B) Availability of data.

C) Use of historical data.

D) Little or no reliance on covariance matrices.

答案：C 【资料下载】[融跃财经]FRM一级ya题-pdf版

解析：The use of historical data in non-parametric analysis is a disadvantage, not an advantage. If the estimation period was quiet (volatile) then the estimated risk measures may understate (overstate) the current risk level. Generally, the largest VaR cannot exceed the largest loss in the historical period.

On the other hand, the remaining choices are all considered advantages of non-parametric methods. For instance, the non-parametric nature of the analysis can accommodate skewed data, data points are readily available, and there is no requirement for estimates of covariance matrices.

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