Distributions aren’t cast in concrete, and many Monte Carlo software packages allow you to fit the distribution to the demands of the questions you’re addressing with your risk analysis model. If you find yourself in agreement with the New Normal, it shouldn’t be that hard to get the tails right.
The so-called Great Moderation, the economic period that began in the late 1980s and ended with the financial crisis of 2007, was characterized by less volatility and more stability and predictability in the financial markets. I recently saw commentary that identified one of the causes of the economy’s’ plunge from moderation to recession as "Monte Carlo simulation" and the projections it produced.
Over time and a few blog entries it became apparent that what should have come under fire was not Monte Carlo as a statistical technique but the probability distributions on which the financial risk analysis models were based. During the Great Moderation, apparently, many financial analysts involved in portfolio risk management relied on "normal" probability distributions and continued to rely on them even after tail risk events–events in which risk exceeded 3 standard deviations away from an asset’s current price–began to occur much more frequently than "normal" accounted for. This, of course, meant that actual investment returns were far from those predicted by the models.
Commenting on recession-proofing and tail risk, PIMCO’s Richard H. Clarida observes that as we begin to leave the recession behind we are entering a period in which the New Normal is the paradigm distribution function for asset management. The New Normal "is flatter and the tails are fatter." As he sees it the long reach of risk has just gotten longer. I recommend his essay, which stresses how important it is to "get the tails right."