Why most things we know about investing are wrong
The following is an abridged version of an article written by Lawrence Burns, a Partner with Baillie Gifford whose firm run the Scottish Mortgage and Monks Investment trusts.
As the old saying goes ‘it’s never wrong to take a profit’. There is some validity in this approach, hence why it pervades and endures. A client is unlikely to be unhappy or indeed notice if you sell a stock that subsequently goes up significantly. That loss – of foregone upside – is not captured in performance data, but perhaps it should be. On the other hand, if the stock in question continues to be held and goes in the other direction it will become a clear detractor in performance data and you should expect to be asked, if not chastised, about it. And so, from the investment manager’s point of view, perhaps it can be said that it is never wrong to take a profit.
But what about the client? For the client, equity investing is asymmetric, the upside of not selling is near unlimited, while the downside is naturally capped. Surely, for the client it can be very wrong to take a profit? This goes to the heart of why so much of investing is wrong.
A study by Hendrik Bessembinder of Arizona State University in 2017 identified that a mere one per cent of companies accounted for all of the global net wealth creation. The other 99 per cent of companies were, it turns out, a distraction to the task of making money for clients. The entire active management industry should therefore be trying to identify these superstar companies since nothing else really matters. Investing is a game of extremes. It requires focus on the possibility of extreme upside, not the crippling fear of capped downside. This requires genuine imagination should there be any hope to grasp the potential of superstar companies.
In addition to imagination, Bessembinder makes it clear that it is the long-term compounding of superstar companies’ share prices that matters. Investing thus requires patience to deal with the inevitable ups and downs such companies experience as well as the ability to delay significant gratification. After all, the point of superstar companies is that they can go up five-fold and then go up five-fold again. If you sell after the share price merely doubles, crow and take your profits, you undermine the whole point of identifying companies with extreme return potential in the first place.
In early 2000, the founder of SoftBank, Masayoshi Son, made what may have been the greatest investment in history. He invested $20m in a Chinese ecommerce company. Two decades later his remaining investment is worth in excess of $180bn. A wonderful example of an extreme return.
This is a well-known story. However, less well-known is the story of Goldman Sachs. Goldman invested in the same company a year before Son on far better terms. Shirley Lin, who worked for its private equity fund, had an agreement to invest $5m for a 50 per cent stake. Unfortunately, her colleagues deemed $5m too risky and so they opted for investing a ‘safer’ $3m. Five years later their stake was worth $22m, a seven-fold return. At this point, the decision was taken to sell under the guise it’s never wrong to take a profit. In many ways, this was a remarkably successful investment, until that is you realise that today those shares would be worth over $200bn. That investment alone, if held, would have been worth more than double the value of the whole of Goldman Sachs today.
It would seem Goldman Sachs got the identification, and perhaps even the imagination part, right. They spotted one of the greatest superstar companies of our era early on. Yet, when asked why Goldman Sachs sold, Shirley gives a depressing but predictable answer: “they wanted quicker results”. Though this example is extreme and straddles public and private ownership, the point is clear: in investing, it is often not only wrong to bank profits, it can be the worst mistake you make. Despite this, in almost every client meeting I am asked about our sell-discipline. No one has ever asked me about our hold-discipline, which is a shame, as the greater cost to clients’ returns comes from the inability to hold onto superstar companies when their returns are ticking upwards. Investment managers are usually very good at selling.
For Ming Zeng, Alibaba’s Chief Strategy Officer, the greatest superstar companies of the future will be what he calls “smart businesses” harnessing network coordination and data intelligence. These organisations will look less like a company and more like a network. He notes:
The old, diversified conglomerate was like a complex machine of the old industrial age. It collapsed when it reached a certain complexity. But the future of business is more biological rather than mechanical… an ecological system grows and becomes more and more sophisticated, even more robust when it becomes richer and more diverse.
Network companies, such as Amazon, Uber or MercadoLibre, coordinate millions of entrepreneurs, guiding them with data intelligence in real-time so both the network companies and entrepreneurs can adapt to conditions instantly in ways traditional companies could never have dreamt. This marries the benefits of enormous scale with rapid adaptability. Moreover, the larger these network companies become, the more data they have and thus the more intelligent and effective the network can become. If Ming is right, then it is logical to assume the importance of superstar companies will grow even further with the application of machine learning.
The notion that companies can even produce such extreme returns goes against much of economic theory which holds that returns will revert to the mean in time. Yet Bessembinder’s data shows when looking at nearly a century of US stock market returns the concentration of wealth creation is becoming yet more skewed towards a small number of companies and these returns are becoming extreme. The superstar companies are becoming more super.
This is particularly odd given that economics focuses on diminishing returns to scale. It takes the work of Professor Brian Arthur of the Santa Fe Institute, to understand that this concept is rooted in observing the returns to scale of the “bulk-processing, smokestack” industrial companies of the 19th century. He notes that western economies have shifted “from processing of resources to processing of information, from application of raw energy to application of ideas”. Far from diminishing returns, today’s knowledge-based companies tend to exhibit increasing returns to scale and so, in the digital era, reversion to the mean is even less common. Returns are yet more extreme.
Despite the above, we must not forget that the prevalence of new superstar companies will be determined by the amount of economic and social change that takes place from here. Indeed, I would go further still and posit that the single greatest determinant of whether returns will swing from growth to value is whether the pace of change in the world increases or decreases. For it is change which creates new markets and disrupts old ones. It is change that fuels the rise of superstar companies.
We therefore need to believe the conditions for change will persist. To give us that conviction we have Moore’s law. The observation and projection made by Gordon Moore, the co-founder of Intel, that, for the same price computing power would double every 24 months. This projection has now become seen as a law, given its predictive power over the last 50 years. In doing so it has set the pace for the semi-conductor industry and thus for human progress.
It therefore perplexes me why with the power and predictability of Moore’s law, our industry decides instead to focus far more on what interest rates or GDP growth rates mean for investing. Frankly, I think we would all be much better investors if we concentrated on the future implications of Moore’s law. A 60x increase in computing power will profoundly shape our world. The question we must grapple with is what this new world will look like.
Lawrence Burns, Baillie Gifford
The opinions expressed are those of the fund managers above using their independent research and are subject to market or economic changes. This material is not a recommendation, or intended to be relied upon as a forecast. You may get back less than the amount invested.
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