Month: January 2017

Why is Amazon so successful?

Amazon

At Movefresh we are obsessed by Amazon – they are a great role model for thinking long term (this isn’t that popular in the current economic environment)

I am still amazed that sophisticated investors can’t get their head around Amazon as a business and investment opportunity. Firstly, having been born around the dot com boom, it is certainly associated with the many businesses that failed within this cohort.

Secondly, investors really struggle to understand businesses that can continue to find ways to effectively invest their cashflow/profit. Many investors look at Amazon as a business that is “marginally” profitable, I see a business that can actively invest in the future and give bigger returns to shareholders who are willing be part of that.

I always recommend reading the Amazon letter to shareholders that have been published annually. The 2015 shareholder letter makes some interesting reading.

1. “The fastest company to reach $100 billion in annual sales”
2. AWS reached $10 billion pretty quickly too
3. “Customer obsession rather than Competitor obsession”
4. “Willingness to fail”
5. “Patience to think long term”

All of this is contained in the first paragraph – it is totally clear that that the business knows how to invest its cash flow.

They also included a copy of the letter from 1997 (reprinted from the 1997 Annual Report). They haven’t really changed their strategy since this original letter – something that I admire greatly.

Monty Python on Statistics

I was reminded today of my favourite Monty Python sketch on statistics. I had a look for it on YouTube but sadly couldn’t find it.

The sketch was set on election night with a reporter who did a vox pop and asked a lady in the street how she was going to vote. She said “Conservative”. They then went back to the studio and extrapolated this to their swing-o-meter which predicted a 100% swing to the Conservatives and all seats in the House of Commons switching to that party.

It was very funny. But like the best comedy it was also very true. We’ve all been in situations in business were very small datasets are extrapolated.

Interpolation is of course much more accurate. But to interpolate my experience of statistics in business I can say that interpolation is something that is much less common that extrapolation.

Michael Fish

Michael Fish announced on TV on 15 October 1987 that there was no hurricane on the way. That evening the worst storm to hit South East England caused record damage and killed 19 people.

Andy Haldane of the Bank of England recently said that the failure to predict the 2008-09 financial crash was a similar moment for economists and has resulted in economics forecasting being “in crisis”.

It is true that the record for prediction of economists, financial analysts and accountants is very poor. When we look back over the last half century it is indeed true that all three groups failed to predict the big crashes in US public companies.

But conversely they also failed to identify the ten days over the last fifty years which accounted for roughly half the return of the same US public companies.

In other words, out of 18,250 trading days just 10 days accounted for half of the return. So surely it was a failure of economists, financial analysts and accountants that they did not identify these days in advance? Or identify the days in 2008-09 that resulted in dramatic reductions in market value?

I would disagree with Andy Haldane on this. I don’t think it is reasonable to expect economists to identify in advance the 0.05% of days in which markets move dramatically.

My favourite book on this subject is A Treatise on Probability by John Maynard Keynes who wrote in Chapter 3:

Is our expectation of rain, when we start out for a walk, always more likely than not, or less likely than not, or as likely as not? I am prepared to argue that on some occasions none of these alternatives hold, and that it will be an arbitrary matter to decide for or against the umbrella. If the barometer is high, but the clouds are black, it is not always rational that one should prevail over the other in our minds, or even that we should balance them, though it will be rational to allow caprice to determine us and to waste no time on the debate.

Keynes understood that some probabilities are measurable. He gave an example in the book of pulling red and black balls out an urn of which half are red and half are black which is clearly a system that can be easily measured but many probabilities are inherently unmeasurable such as his example of the requirement for an umbrella or his discussion of an ern where the the proportions of red and black balls are unknown.

However although there are many probabilities that are not measurable but are comparable. The example Keynes gave was the possibility of surviving a walk home in a thunderstorm: this is not measurable but it is clearly less safe and therefore comparable to walking home during good weather.

So to get back to our trio of economists, financial analysts and accountants. It is unreasonable to expect any of them to predict a dramatic period of recession or growth however it is reasonable to expect them to suggest that a situation is more or less comparable i.e. more or less likely to result in a period of recession or growth.

I do not think that it is a failure of economics to predict the ten best trading days of the last half century. I do think that economics is useful in producing data that makes the best trading days comparable with poor trading days or the best investment opportunities comparable with the worst while accepting that neither are measurable.

So in my investments I accept that I cannot make predictions as to when it will rain. But I can see clouds in the sky as Micheal Fish did successfully over his career at the Met Office from 1962 to 2004.

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