Reading 7: Statistical Concepts and Market Returns-LOS k习题 following, statements, concerning, div, class

bmaggie

Session 2: Quantitative Methods: Basic Concepts
Reading 7: Statistical Concepts and Market Returns

LOS k: Define and interpret measures of sample skewness and kurtosis.

 

 

 

Which of the following statements concerning skewness is least accurate? A distribution with:

A) a distribution with skew equal to 1 is not symmetrical.

B) positive skewness has a long left tail.

C) negative skewness has a large number of outliers on its left side.

bmaggie

Which of the following statements concerning skewness is least accurate? A distribution with:

A) a distribution with skew equal to 1 is not symmetrical.

B) positive skewness has a long left tail.

C) negative skewness has a large number of outliers on its left side.

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A distribution with positive skewness has long right tails.

bmaggie

Which of the following statements concerning kurtosis is least accurate?

A) A distribution that is more peaked than a normal distribution is leptokurtic.

B) A leptokurtic distribution has fatter tails than a normal distribution.

C) A leptokurtic distribution has excess kurtosis less than zero.

bmaggie

Which of the following statements concerning kurtosis is least accurate?

A) A distribution that is more peaked than a normal distribution is leptokurtic.

B) A leptokurtic distribution has fatter tails than a normal distribution.

C) A leptokurtic distribution has excess kurtosis less than zero.

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A leptokurtic distribution is more peaked than normal and has fatter tails. However, the excess kurtosis is greater than zero.

bmaggie

Which of the following statements about kurtosis is least accurate? Kurtosis:

A) measures the peakedness of a distribution reflecting a greater or lesser concentration of returns around the mean.

B) describes the degree to which a distribution is not symmetric about its mean.

C) is used to reflect the probability of extreme outcomes for a return distribution.

bmaggie

Which of the following statements about kurtosis is least accurate? Kurtosis:

A) measures the peakedness of a distribution reflecting a greater or lesser concentration of returns around the mean.

B) describes the degree to which a distribution is not symmetric about its mean.

C) is used to reflect the probability of extreme outcomes for a return distribution.

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The degree to which a distribution is not symmetric about its mean is measured by skewness. Excess kurtosis which is measured relative to a normal distribution, indicates the peakedness of a distribution, and also reflects the probability of extreme outcomes.

bmaggie

Which of the following statements concerning a distribution with positive skewness and positive excess kurtosis is least accurate?

A) It has a lower percentage of small deviations from the mean than a normal distribution.

B) The mean will be greater than the mode.

C) It has fatter tails than a normal distribution.

bmaggie

Which of the following statements concerning a distribution with positive skewness and positive excess kurtosis is least accurate?

A) It has a lower percentage of small deviations from the mean than a normal distribution.

B) The mean will be greater than the mode.

C) It has fatter tails than a normal distribution.

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A distribution with positive excess kurtosis has a higher percentage of small deviations from the mean than normal. So it is more “peaked” than a normal distribution. A distribution with positive skew has a mean > mode.

bmaggie

A distribution of returns that has a greater percentage of small deviations from the mean and a greater percentage of large deviations from the mean compared to a normal distribution:

A) is positively skewed.

B) has positive excess kurtosis.

C) has negative excess kurtosis.

bmaggie

A distribution of returns that has a greater percentage of small deviations from the mean and a greater percentage of large deviations from the mean compared to a normal distribution:

A) is positively skewed.

B) has positive excess kurtosis.

C) has negative excess kurtosis.

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A distribution that has a greater percentage of small deviations from the mean and a greater percentage of large deviations from the mean will be leptokurtic and will exhibit positive excess kurtosis. The distribution will be taller (more peaked) with fatter tails than a normal distribution.