Volatility Analysis
When analyzing statistical data, we study the dispersion and geometry of the
distribution. Geometry has two basic components:
- Skewness: the bias in the data set where the tail of the distribution is pointing
to either left or right side of the mean. If the tail in the data set is shifted to
the left, we say that the distribution is skewed to the left, that is, negatively
skewed. In such a case, the mode is usually greater than the median, which in
turn is greater than the mean. If the tail in the data set is shifted to the right,
we say that the distribution is skewed to the right, that is, positively skewed,
where the mode is usually less than the median, which in turn is less than the
mean. See Figure 21.16. - Kurtosis: is a measure of the distribution’s peakedness. Distributions that are
flatter and more spread out than the normal distributions are called platykurtic
distributions, whereas distributions that are taller and more concentrated around
the mean are called leptokurtic distributions. See Figures 21.16 and 21.17.
figure 21.16 Left and Right Skewed Distributions.
figure 21.17 Distributions with Differing Kurtosis.