Which of the following is (are) an advantage(s) of nonparametric methods compared to parametric methods for quantifying volatility?
　　I.Nonparametric models require assumptions regarding the entire distribution of returns.
　　II.Data is used more efficiently with nonparametric methods than parametric methods.
　　III.Fat tails, skewness and other deviations from some assumed distribution are no longer a concern in the estimation process for nonparametric methods.
　　IV.Multivariate density estimation (MDE) allows for weights to vary based on how relevant the data is to the current market environment by weighting the most recent data more heavily.
　　A. I and II.
　　B. III only.
　　C. I and III.
　　D. III and IV.
　　Answer:B
　　Fat tails, skewness, and other deviations from some assumed distribution are no longer a concern in the estimation process for nonparametric methods. The other statements are false for the following reasons. Nonparametric models do not require assumptions regarding the entire distribution of returns. Data is used more efficiently with parametric methods than nonparametric methods. Multivariate density estimation (MDE) allows for weights to vary based on how relevant the data is to the current market environment, regardless of the timing of the most relevant data. MDE is also very flexible in introducing dependence on state variables.