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Explanation:
Non-parametric methods do not require assumptions regarding the entire distribution of returns to estimate VaR. The multivariate density estimation is very flexible in introducing dependence on economic state variables. Deviations from normality are not as big of a concern for non-parametric compared to parametric methods. Data is used more efficiently with parametric methods. Multivariate density estimation requires a large amount of data that is directly related to the number of conditioning variables used in the model.
(Book 4, Module 49.2, LO 49.d)
Question 14
A hedge fund is considering using one of the following non-parametric methods for estimating value at risk (VaR): traditional historical simulation or multivariate density estimation. Which of the following statements is an advantage of these methods compared to parametric methods for estimating VaR?
A
Deviations from normality may be a concern for non-parametric methods.
B
Data is used more efficiently with non-parametric methods than with parametric methods.
C
The multivariate density estimation is very flexible in introducing dependence on economic state variables.
D
Parametric methods require a large amount of data that is directly related to the number of conditioning variables used in the model.
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