The loss distribution typically has fat tails, and you might get more than one break in a short period of time.
fat tails). A narrower peak around the mean also characterizes it. What this means in “real English' is that there are far more major winners and losers than you would experience if the real world distribution were exactly normal.
Fat tails means there is a higher than normal probability of big positive and negative returns realizations. When calculating kurtosis, a result of +3.00 indicates the absence of kurtosis (distribution is mesokurtic).
This is a phenomenon known as "fat tails". As a result, stock and share prices which are more than two multiples of the standard deviation away from the average may be slightly more common than the statistical 95.
It is sometimes described as the volatility of volatility. A high kurtosis portrays a chart with fat tails and a low, even distribution, whereas a low kurtosis portrays a chart with skinny tails and a distribution concentrated toward the mean.
Leptokurtosis describes a probability function which is similar to the bell curve, but not quite. The extreme cases, while still rare, are not as rare as expected. This is often called "fat tails" because of the way this looks when you graph the ...
Kurtosis measures the "fatness" of the tails of a distribution. Excess kurtosis means that distribution has fatter tails than a normal distribution. Fat tails means there is a higher than normal probability of big positive and negative returns ...
 See also: Distribution, Normal Distribution, Asset, Kurtosis, Around
  
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