Fat tails

I’ve often read that over the long term the most important factor driving equity returns is valuation. While share prices experience momentum over the short to medium term, eventually investors become more conscious that valuations are becoming ‘detached from reality’ and prices revert to mean.  Along this line of reasoning, momentum following is a dangerous game that can lead to bubbles and then crashes, such as the infamous ‘Dot-com’ crash in 2002-3. While there is truth to this analysis for the stock market as a whole, it misses a key nuance when you look at what is going on underneath.

Fat tails

This nuance is how the overall returns are distributed across the individual stocks that make up the stock market over the long term. If you take a very long term perspective, i.e. more than 20 years, the distribution of returns to individual stocks doesn’t follow the typical normal distribution you might expect if these returns were randomly distributed. In fact it is very far from this – the distribution has so-called ‘fat tails’. In other words, over the long term a much larger proportion of stocks than you might expect will either make very little (or negative) returns or very large returns. Relatively fewer than you might expect will make around the market average.

This is demonstrated in this article, which describes a study looking at the performance of the largest US stocks listed at any point between 1983 and 2006. It shows that:

  • About 40% of stocks made negative returns over the period
  • Almost two thirds of stocks underperformed the index
  • A minority of stocks dramatically outperformed the index (20% by more than 300% and 6.1% by more than 500%)
  • All of the net gains can be attributed to only 25% of stocks

Basically this shows that in the long term stock market returns are very far from evenly distributed across stocks, but rather can be attributed to a minority of big winners.  At a fundamental level this illustrates that the businesses that make up the stock market are far from equal. A minority of high quality businesses consistently generate strong returns for long periods of time and a majority of lower quality businesses consistently make more limited returns or lose money. Or more bluntly, in the long run there is a fairly stark distinction between ‘good’ businesses, which will make money if you buy and hold, and ‘bad’ businesses, which won’t. That’s not to say you can’t make money if you invest in ‘bad’ businesses, but to do this you have to be better at market timing than other market participants.

OK but how is this useful?

Given this distribution of returns across stocks in the long term, clearly a market beating strategy is to have an overweight exposure to the long term outperformers. But this is easy to say with the benefit of hindsight – how can you identify them in advance?

One approach is to look at the fundamentals of the businesses. Identifying these long term outperformers is broadly the strategy of investors like Warren Buffett and Terry Smith.  This closely relates to the concept of quality as a factor – for my approach I define quality specifically in a way that relates directly to whether the business is likely to be a long term outperformer: ‘does it have the ability to make market beating returns consistently in the long term?’

I’ve written previously about how I identify quality. Broadly my approach consists of assessing factors relating to how profitable the business is (both in terms of margin and in terms of how much investment is required to generate profit), how much of a competitive advantage it has, its prospects for continued growth and its track record.

However, my main point here is not how to identify quality using fundamental analysis. My main point is that the fat tails (in the distribution of returns across shares in the long run) must arise because over time there is a tendency of outperforming stocks to continue to outperform and vice versa. If this wasn’t the case the distribution would have a considerably greater proportion of shares nearer the average market return than at the extremes. This suggests that shares that have had higher long term returns in the past are more likely to have higher returns in the future. 

The authors of the research I referred to above make this point through the observation that the biggest winners in their research spent a disproportionate amount of time making new multi-year highs. Their conclusion, like mine, is that long term trend following makes sense as a strategy. I incorporate this by looking at the long term share price performance as part of my assessment of quality. Pretty much all of the shares in my portfolio or watchlist have share prices that have fairly consistently increased at a much greater rate than the index for the past 10 years.

 

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