John Kay, one of my favorite columnists for the Financial Times, has again denounced pratices in the City. Diffusing UNCOMFORTABLE KNOWLEDGE in times of pending catastrophe is not easy. Many probably know, and do not speak. It is a duty though, and the fact that people do not dare to speak, is the surest sign of a “closed hegemony” impairing any democratic process. See http://ow.ly/46h4p
John’s article though leads me to put the finger on another phenomenon which prevents change: Mindsets.
Read the comment I made in the Financial Times pursuant to John’s article:
“This is again a great article, John.
It explains that our world does not change, because people do not learn from their mistakes. Why is that so?
Two possible explanations:
Either people are totally bad-faithed and cynic and follow the path “après moi le déluge”, trying everything to make sure that indeed this “déluge” appears only when they are on safe ground. (I leave open here whether that safe ground is an illusion or not).
Or they are totally blinded by what Carol Dweck, well-renowned Stanford University psychologist calls a “fixed mindset”. Such a mindset blinds people to reality. It prevents them to accept failures, or worse, cause them to attribute failure to others (or to circumstances), or worse, it leads them to cheat (or worse!)… Such deviations might explain the cynic’s reactions explained as first possibility.
It goes beyond the intention here to explain further the why, what, how of mindsets, but just a hint: fixed mindsets very often appear to be characteristic of the best and the brightest, those successful professionals that have made it to the city. And it is well known that the city recruits them “en masse” so they are over-represented there.
I highly recommend Carol Dweck’s book, Mindset: an easy read. It might not be a comfortable read though, for many who have been educated towards a fixed mindset. But here’s the consolation: whilst it might explain quite convincingly how fixed mindsets are infused in people, and why this makes it so difficult to resolve the intractable problems of our time, it also contains precious indications on how a fixed mindset can be changed into a learning one, and how to educate our newborn baby’s towards a learning mindsets from early age on.
Carol Dweck, Mindsets, follow http://mindsetonline.com ”
Let’s again refer the cynic, but wise Machiavelli, advising his Prince:
“It ought to be remembered that there is nothing more difficult to take in hand, more perilous to conduct, or more uncertain in its success, than to take the lead in the introduction of a new order of things. Because the innovator has for enemies all those who have done well under the old conditions, and lukewarm defenders in those who may do well under the new. This coolness arises partly from fear of the opponents, who have the laws on their side, and partly from the incredulity of men, who do not readily believe in new things until they have had a long experience of them.”
Don’t blame luck when your models misfire
By John Kay
When the financial crisis broke in August 2007, David Viniar, chief financial officer of Goldman Sachs, famously commented that 25-standard deviation events had occurred on several successive days. If you marked your position to market every day for a million years, there would still be a less than one in a million chance of experiencing a 25-standard deviation event. None had occurred. What had happened was that the models Goldman used to manage risk failed to describe the world in which it operated.
If the water in your glass turns to wine, you should consider more prosaic explanations before announcing a miracle. If your coin comes up heads 10 times in a row – a one in a thousand probability – it may be your lucky day. But the more likely reason is that the coin is biased, or the person who flips the penny or reports the result is cheating. The source of most extreme outcomes is not the fulfilment of possible but improbable predictions within models, but events that are outside the scope of these models.
Techniques such as value at risk modelling – the principal methodology used by banks and pressed on them by their regulators – may be of help in monitoring the day-to-day volatility of returns. But they are useless for understanding extreme events, which is, unfortunately, the main purpose for which they are employed. This is what Mr Viniar and others learnt, or should have learnt, in 2007.