What does a high positive kurtosis mean?
For investors, high kurtosis of the return distribution implies the investor will experience occasional extreme returns (either positive or negative), more extreme than the usual + or – three standard deviations from the mean that is predicted by the normal distribution of returns.
Is a positive kurtosis a bad thing?
If a distribution has positive kurtosis, it is said to be leptokurtic, which means that it has a sharper peak and heavier tails compared to a normal distribution. This simply means that fewer data values are located near the mean and more data values are located on the tails.
What does it mean when a distribution has a high kurtosis?
A distribution, or data set, is symmetric if it looks the same to the left and right of the center point. Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution. That is, data sets with high kurtosis tend to have heavy tails, or outliers.
Which is an example of a positive kurtosis?
A distribution with a positive kurtosis value indicates that the distribution has heavier tails and a sharper peak than the normal distribution. For example, data that follow a t distribution have a positive kurtosis value. The solid line shows the normal distribution and the dotted line shows a distribution with a positive kurtosis value.
What does a kurtosis value of 0 mean?
Normally distributed data establishes the baseline for kurtosis. Sample kurtosis that significantly deviates from 0 may indicate that the data are not normally distributed. A distribution with a positive kurtosis value indicates that the distribution has heavier tails and a sharper peak than the normal distribution.
Which is the best test for kurtosis and skewness?
However, size distortions render testing for kurtosis almost meaningless except for distri- butions with thin tails, such as the normal distribution. Combining skewness and kurtosis is still a useful test of normality provided that the limiting variance accounts for the serial correlation in the data.