The early 21st century saw a few significant stresses on
the stock market. The markets dipped deeper and more quickly than many were
expecting might happen.
Which of the following statistical metrics most accurately
describes this event?
Low mean. Could the average stock
return be overstated? Absolutely. But understating the mean affects all
returns, not just the outliers.
High standard deviation. Again,
the standard deviation may play a role. These factors are all related to each
other. But the standard deviation applies to all dispersion, not just the tail.
Positive skewness. Skewness very
well could be playing a part here. The problem with this choice is that an
event like a large loss would be indicative of negative skewness.
High
kurtosis. Kurtosis is the metric used to capture tail risk. If
the extreme events are more likely than expected, that means that the kurtosis
is higher than expected.