Most of us have some painful memories of the 2007-08 crunch. It is not surprising that most people in the business are keen to forget and to resume business as usual. This will not happen and if you believe it is happening now, you are heading for trouble.
One of the reasons we had the crunch was that the whole of economic and finance theory is wrong. By wrong, I mean it is based on assump-tions that are false, so the models it uses do not represent reality except in very limited ways.
Rational investors, maximising utility, symmetric risk preferences, normal distribution of returns…any so-called theory this full of holes would have been terminated long ago in any of the hard sciences. Only because of political factors has neoclassical economic and finance theory survived so long – in essence, it has served the interests of the rich and the bankers, who in the US have bought the regulators and politicians.
These may seem extreme assertions, but I refer you to Steve Keen’s Debunking Economics and Justin Fox’s The Myth of the Rational Market for the evidence.
There are lots of very big implications of the collapse of current theory, but for now I will stick to a few specific to the investment business.
Academics have known for years that investment returns are not “normally distributed”, so standard deviation is not a valid way of assessing them.
The reason they chose to stick with the bell curve or Gaussian distribution is that the maths is manageable, whereas the chaos maths pioneered by Benoit Mandelbrot now used in physics, weather forecasting and biology is very difficult.
The patches applied to normal distribution models to cope with “fat tails” are ugly ad hoc attempts to make the models look more like reality. But this does not work, as exemplified in the total failure of value at risk models (however adapted) to measure the real risk incurred by banks.
The conventional defence to the inaccuracy of standard distribution models is that they work most of the time or work except in exceptional circumstances.
But since there is no way of predicting when they will and will not work, using such models as a basis for decisions is simply unscientific. It can only rest on the belief that the user can judge whether the model will work at this time.
A user of modern portfolio theory methods would have to say to their clients: “Our model works most of the time but it will not cope with extreme events like crashes and panics and it has no means of predicting when such events will occur or how extreme they will be”.
If that is what they were told, how many clients would sign up to the use of such models?
The market is not efficient, probabilistic risk measures do not provide reliable grounds for decision-making and the coming revolution in economic and finance theory will, like those in meteorology and biology, emphasise “butterfly wing” effects that are simply not predictable.
As JM Keynes said, the real problem investors face is not risk, which is measurable, but uncertainty, which is not.
In the absence of genuine science, which Keynes was sceptical could ever happen with investment, it is entirely rational for practitioners to use judgement and heuristics – old fashioned rules of thumb – in making decisions.
Chris Gilchrist is the joint author of The Process of Financial Planning and editor of the IRS Report