For those who didn’t read my last week’s article, according to Nassim Taleb, a best-selling author, quant trader and New York Polytechnic University Professor, Black Swans are events which are rare, extremely significant and retrospectively (but not prospectively) predictable. Major events of our era, including practically all major inventions, fashion trends, epidemics, financial market collapses, events of 11 September 2001… really are Black Swans.
According to Taleb, we go about our lives pretending that Black Swans don’t exist. We spend our time reading various economic and financial forecasts which are based on the erroneous assumption that we live in some form of an ‘Averageville’. In Averageville, if you have a sufficiently large sample, one particular specimen could not affect the result of the whole. Examples include human height, caloric intake or intelligence. Most of the economic models used in economic forecasting and in financial risk management are based on statistical probability theory which counts on normal distribution, i.e. on the game of average numbers. That means, they are firmly set in Averageville. In Extremeville, just one recorded case can distort the average of not only the sample but often of the entire category. Take as an example personal wealth. If you add the personal wealth of Bill Gates to the fortunes of any random thousand people, it is quite likely that it will significantly change the results. The problem of course is, that we mostly live in Extremeville. Therefore, most of the economic forecasting models are fundamentally flawed and the resulting forecasts are not worth the paper they are printed on.
Is that a scary thought? Does it seem completely unbelievable? Jean-Philippe Bouchaud, a Paris-based quantum physicist, has published a study analyzing in detail ca. two thousand forecasts by various equity analysts. The study found that the equity analysts’ forecasts were less useful than if you just plugged the numbers from the previous year and copy-pasted them. What is worse, the study quite clearly showed very strong herd mentality in their forecasting.
Or consider this. We all know that the financial services sector has gone global and hugely concentrated. The banks are gigantic, and present themselves to us as far more sophisticated than the good old banks of yore. For one, they are all claiming that they have highly advanced risk controls. JPMorgan in 1990’s started all the rage by introducing RiskMetrics, a risk management method which, alongside its generally more known sibling, Value-at-Risk, use quantitative assessment of risks based on normal distribution, i.e. pure Averageville methodology. To translate into normal language, they all base their huge proprietary trading portfolios and products they develop for their institutional and retail clients on the assumption that a) they can foresee the probability of all the risks, and b) that the probability is perfectly symmetrical for positive and negative outcomes. Does that sound remotely like the world we live in?
That is coupled with the increasing complexity of the products which the wizards on the bank payroll are allowed to structure, and the growing gap between their individual focus and the ability of their management to capture and supervise it all. No surprise then, that the front pages of newspapers are periodically filled with headlines about yet another trading scandal at yet another sophisticated international bank, which has blown such a hole in its balance sheet that the consequences far exceed anything the bank’s Board would have imagined possible in their worst nightmares. Do you remember Nick Leeson, the English public school boy whose “speculative” trading in Singapore caused the collapse of Barings Bank, the UK's oldest investment bank, in 1997? It was a laughable US$1.4bn then. How about Jerome Kerviel, the dashing 29-year old Frenchman who caused French bank Societe Generale US$6.7bn in trading losses in 2006-07? Kerviel had told investigators that “his trading behavior was widespread at the bank and that getting a profit makes the hierarchy turn a blind eye”. The latest is Kweku Adoboli, another “rogue trader” who caused UBSUS$2.3bn in losses in 2011. The prosecutor in Adoboli's trial stated that Adoboli "was a gamble or two from destroying Switzerland's largest bank”, it certainly was enough for CEO Oswald Grubel and 2 of his lieutenants to resign. What did all of these have in common, apart from some very poor human resources function (the way media are picturing these, you would be forgiven to think that a rogue trader is akin to a wolf dressed in sheep’s clothing amongst the good white lambs)? Poor risk management, of course. So, wait for the next one, it is coming to a theater near you soon…
Merry Christmas!