Why some advisers ignore big market risks
And why you need to learn the basics
Here’s one reason why there’s so much bad investment advice around – even from professionals.
The professionals have been taught the wrong model!
Yes, seriously – and it’s all to do with the Gaussian formula
What on earth is the Gaussian formula, and should you care?
Well, yes I think you should.
The Gaussian (aka Normal) distribution is that bell-shaped curve “thingamajig” which is used, for example, by statisticians to predict likely outcomes from a limited amount of data.
If you’re not familiar with it – it looks like this:
Now, if your data set fits this model then you can predict that there’s only a tiny chance of getting an outcome that’s very different to the average one.
And the average one normally sits somewhere around the middle of your data set.
Okay, sorry, if that’s got a bit technical, let’s try an example.
Imagine, that you were measuring the height of people in a particular area of the world.
You’d soon discover that people’s heights follow this sort of model. The height of most people sits around an average, and there are fewer and fewer people of extremely short or tall heights.
You would not expect to find any 12 foot high giants or 1-foot tall people, right?
So, this ‘Gaussian’ (normal) distribution model is very useful in all sorts of industries…
For example, if you were planning a production run of shoes – it would help you to know how many shoes of each size to make.
Similarly, if you were designing a car seat, this ‘normal’ model could help you design the range of movement necessary to allow most people to get comfortable whilst driving their car.
The problem is, this Guassian model is NO USE for predicting the likelihood of big crashes in stock markets.
Learn more – in this wonderful FT interview with Benoit MandelBrot
Or read Nassim Taleb’s books
Nassim Taleb, in one of his early books ‘Fooled by Randomness’ (Penguin 2004) tells a wonderful story about the Gaussian as follows
I was transiting through Frankfurt airport in December 2001, on my way between Olso and Zurich.
I had time to kill at the airport and it was a great occasion for me to buy dark European chocolate, especially as I have managed to successfully convince myself that airport calories don’t count.
The cashier handed me, among other things, a ten Deutschemark bill. The Deutschmark banknotes were going to be put out of circulation in a matter of days, as Europe was switching to the Euro. I kept it as a valedictory.
Before the coming of the Euro, Europe had plenty of national currencies, which was good for printers, money changers, and, of course, currency traders like this (more or less) humble author.
As I was eating my dark European chocolate and wistfully looking at the bill, I almost choked.
I suddenly noticed, for the first time, that there was something curious.
The bill bore the portrait of Karl Friedrich Gauss and the Gaussian “bell curve” smack on it.
The striking irony is that the last possible object that can be linked to the German currency is precisely such a curve.
The Reichsmark (as the currency was then called) went from four per dollar to four trillion per dollar in the space of a few years during the 1920s.
And that’s an outcome that tells you that the bell curve is meaningless as a description of the randomness in currency fluctuations.
All you need to reject the bell curve is for such a movement to occur once and only once–just consider the consequences.
Yet there was the bell curve and to its right Herr Professor Doktor Gauss, unprepossessing, a little stern, certainly not someone I’d like want to spend time with lounging on a terrace drinking pastis and holding a conversation without a subject.
Taleb has made an excellent contribution to the debunking of traditional risk modelling theories and his books ‘Black Swan’ and ‘Antifragile’ are ‘must-reads’ for anyone wishing to delve deeper into questions of investment risk.
Now it’s true to say that maths is a pure and perfect subject. It’s simple logic, so it cannot be wrong.
However, people are wrong – big time – if they use a maths model to describe the wrong system in the real world. And this is precisely the issue we have with the way in which investment risk has been measured by the Investment banks (and a few advisers) for a very long time.
This is an extraordinarily dangerous mistake to make and is (according to most well-informed opinion) a big factor behind the blow-up of the whole financial system in 2008-9.
So, there are some seriously flawed economic models out there – and they support a belief system about ‘perfect markets’ which says (broadly speaking) that whilst market prices will wobble a bit from time to time – they generally just bounce around their long term trend in a nice neat fashion according to that bell curve shape above.
Or to put that into even simpler terms, the theory suggests (my words) that:
very big events
massive crashes in short time-scales
are impossibly unlikely to happen.
Look at what has happened at least twice in the last 20 years on stock-markets around the world – and you’ll know that this isn’t right.
Unfortunately, the world’s investment bankers (and quite a few financial advisers) are trained to believe these models.
Of course, the brighter advisers and investment bankers realise very well that these models don’t work – but sadly, there are enough who believe in them for this to be a big worry.
So, if your adviser starts telling you there’s little or no risk to investing – and that they have a clever tool called a “stochastic model” to prove it, you might like to pose your adviser this test.
Just remember this,
Stockmarkets tend to produce
low (or negative) returns
from high valuation points
and higher return from low ones.
Where are we now?
Well as of today, we’re at a high valuation point at least on US stock as we can see here
So, be careful who you listen to about investing.
Thanks for dropping in
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