Could perhaps be created using genetic engineering in the future 🙂 I’ve been reading Nassim Taleb’s The Black Swan. It’s an engaging book once you get beyond the pages and pages of insults directed against professional statisticians.
They key point could be summarised as follows. Professional statisticians have become obsessed with applying gaussian distribution models to real world phenomenon which don’t match the model for a range of reasons. Primarily the gaussian model attaches a lower probability to rarer events than is actually the case in many real world phenomenon such as degrees of wealth. When these models are used for prediction and risk management the results may be acceptable when making predictions about data close to the median but are hugely error prone about rarer conditions. The seeming success of the model in limited predictions promotes over-confidence and encourages further bad predictions.
Mr. Taleb goes on to point out that Mandelbrotian randomness more accurately depicts many phenomenon as it allows for greater deviations within a sample and more probable outliers. The point is made enthusiastically and in an idiosyncratic style. It’s accessible in a way that encourages most people to understand the contents and query current models for market analysis. It’s not an in-depth mathematical treatise and this is ultimately a weakness given some of the grand claims. However, Taleb’s rage at the amount of bullshit spouted by should-know-better financial and quantitative engineers is understandable. You only have to watch market analysts in programmes on CNN, MSNBC to figure out that, with a lot of jargon, there’s often not a lot of actual knowledge or understanding. Differences of opinion and rude/crude arguments abound but few of the experts called the current crisis. What’s the point of accepted financial models if they’re not just unsuccessful at predicting (a very hard task) but cause risk to be discounted (a very bad thing)? The Black Swan is essential reading for anyone who’s blithely applying statistical models to whatever economic, marketing or social science application they’re working on. It should give them pause for thought.
So, back to my headline. Mankind are great at producing huge inequalities and surprising outliers. History is littered with them! The more power we achieve over our environment and, indeed, our genetics the more probable the improbable becomes. I’d content that the number of potential black swans increasing (if that isn’t too wild any idea). Not in a linear way of course. More of a giant leap, black swan, kind of increments 🙂 We’ve found black swans on the moon, black swans in space, black swans in the earth, on the earth and with genetic engineering we can create human black swans. Scary.
So the current market models are deeply flawed. Indeed they don’t seem so much models as talking points for TV debates. Who predicted the crisis? Currently in the “Deep Financial Shit is Nigh” hall of fame are international players like Peter Schiff, Nassim Taleb and local players like David McWilliams, Alan Ahearne and Morgan Kelly. Very few economists correctly predicted the current crisis nationally or internationally.
I believe one reason for this is that it became fashionable for these most miserable of analysts to predict boom followed by a soft landing. Economists by their nature are supposed to be pessimistic and risk aware. They should be over-predicting recessions, which is the butt of the famous economist joke.
“An economist is a person who predicts 10 of the last 3 economic recessions”
In this case, there seems to have been an international fear of being caught out in predicting an end to this boom, fueled by financial innovations in the bond market. Many economists simply suspended disbelief even when scandals like Enron encouraged skepticism. Conversely this old joke gives the lie to the belief that economists create recessions. They make predictions and pass comments. Some may add to recessions and further despair but if they could really create economic turmoil then their predictions would never be wrong!