Much of economic theory is built on the assumption that financial returns follow the well-known Bell curve. However, there is much evidence to support the idea that the Bell curve understates the likelihood of extreme events.
Some theorists believe that financial returns follow a Cauchy distribution, which is superficially similar to the Bell curve:
However, the Cauchy distribution is narrower in the middle and higher at the sides. This means that mild events are a little less likely and extreme events are more likely.
To see just how different these curves are for extreme events we need to look at the same curves on a log plot where each horizontal gridline represents a factor of 10:
A 5-standard deviation event on the Bell curve is very unlikely, but the same event on this Cauchy distribution is about 6000 times more likely.
So, if a financial institution was selling insurance against unlikely events based on the Bell curve, it might charge a million dollars, but really have a 6-billion dollar exposure if the events actually follow a Cauchy distribution.
It’s not hard to see the potential danger of using the wrong math to value extreme events. Of course, this danger is mostly a problem for taxpayers who bail out financial institutions.