In the recent bestselling book The Black Swan, Nassim Nicholas Taleb argues that traditional models focus on predicting events that stay within a “normal” range – that is, outliers and extremely rare events are excluded from the analysis and therefore are not predictable.ans, he argues, alter history with great frequency but we tend not to recognize their importance and rationalize them away post-facto. His hedge fund takes advantage of the rare event of a stock “exploding” – much the way a venture capital firm bets on many startups with the hope that one will become a Google.
The Economist reports on a study showing our inability to predict recidivism in criminals – even within a group of criminals who are very likely to become repeat offenders, there is wide variation in any individual criminal’s likelihood. What this means is that although we may be able to classify someone into a high-risk group, we still don’t know how likely he/she is to commit a Black Swan event .
In an article in Scientific American (“Shaping the Future,” April 2005), researchers at RAND Coporation and decision anlaysis firm Evolving Logic describe a second way of making predictions…
Rather than building a model based on one (or a few) scenarios and optimizing to find the result with the highest expected value, what if we optimize to choose the result that is most robust? I.e., when dealing with policy affecting global environment and international economics, the best policy will be one that can *never* result in widespread destruction. We can’t build a portfolio on worlds the way a venture capitalist can, so when we bet the farm on a single set of policies, we should prefer a policy that eliminates the possibility of World War III or widespread famine over a policy that offers the possibility of a utopia (but might end in World War III instead).
When we look at analysis – we must ask whether we want to predict the unusual event or the mundane event, and in the latter case what ramifications the Black Swan event can have on our business or our life.