Where the puck? How the big picture can help direct our play
History is one of investors’ greatest teachers, offering rich lessons and valuable guiding principles. But this aspect of investing is a level playing field — the past is “open access”. The distinction of the skilled investor lies in the discipline of applying the lessons and principles from history to the future. As Wayne Gretzky, widely regarded as the greatest ice-hockey player yet, eloquently puts it: “I skate to where the puck is going to be, not where it has been.”
However, in applying Gretzky’s principle of figuring out the future, a material danger immediately presents itself in the form of forecasting. The seduction of forecasting is the precision with which it parades, and the confidence that forecasts instil in decision makers. Yet the risk — indeed, the tragedy — is that people are overwhelmingly weak in this “exact science”. As David Epstein noted in a recent article in The Atlantic: “The track record of expert forecasters … is dismal. In business, esteemed (and lavishly compensated) forecasters routinely are wildly wrong in their predictions of everything from the next stock market correction to the next housing boom.”
In one study of annual exchange rate predictions made by 22 international banks, the banks missed every change of direction in the exchange rate over a decade. In six of the 10 years, the true exchange rate fell outside the entire range of all 22 bank forecasts. Such results led former US treasury secretary Donald Regan to quip: “If you believe [in forecasts], then you also believe in the tooth fairy.”
However, as much as hanging onto point forecasts can feed poor investment decisions, a variation on Gretzky’s point is that if we can’t figure out the exact future location of the puck, perhaps working out its general travel direction could give us a powerful information advantage. As John Maynard Keynes put it: “It is better to be roughly right than precisely wrong.” This is the subtle but critical shift that sees “decimal-place-point forecasting” replaced by “big-picture thinking”, giving weight to the structural drivers that will shape tomorrow’s investment landscape rather than next quarter’s company earnings.
Three such “big-picture” drivers that will shape markets over the next five years include fewer babies, older people, and smarter machines:
- Fewer babies: In 1950, women had an average of 4.7 children, leading to global fears about a “population explosion”. Since then, higher incomes and gains in education (especially among women) have translated into the global fertility rate steadily falling to 2.4 children per woman in 2018. When the rate drops below 2.1, populations start to shrink — what demographers refer to as a “baby bust”. In 2018 it was reported that half of all countries now face a “baby bust”, including India, Japan, China, the US, France, Russia, Bangladesh and finally Taiwan — which has just 1.2 babies per woman. Experts suggest that the global rate could fall below the replacement ratio of 2.1 as soon as 2030.
- More people: While fewer babies are being born, people are also living longer, helped by advances in medicine and science. Estimates suggest that in the premodern, poor world, life expectancy was about 30 years in all regions. At the beginning of the 19th century, no country in the world had a life expectancy over 40 years. As recently as 1960 the average life expectancy for all countries was 51. Yet the country with the lowest life expectancy now is the Central African Republic at 53 years, and the world average stands at 72 years. Japan leads the world in life expectancy, having lifted from 68 in 1960 to 84 today. Thus, despite falling fertility rates, the world population continues to grow — and to grey.
- Smarter machines: Since 1960 computing power has, on average, doubled every 18 months. More pictures are now taken every two minutes than were taken in the entire 19th century. In terms of raw computing power, computers now rival the abilities of mouse brains. And it is highly likely that within the next 15 years computers will have outpaced the processing capacity of any single human being. Many fear such a future because machines will change the world in disruptive ways. But the net effect will be a better world in which robots will apply their problem-solving capabilities to cure diseases, mine data, drive cars, reduce poverty and help reverse the damage of climate change.
How, then, do you invest for this world where the puck could leap to a completely different plane? You could buy the iShares Global Tech ETF, which is invested in more than 100 world-leading technology firms, including Intel, Samsung and CISCO. You could invest in Omega Healthcare Investors, which owns 900 skilled-nursing and assisted-living facilities in 42 states in the US and UK. Ageing populations in these two large economies will cause an increasing demand for health care. Or, through investing in Japanese multinational Softbank, you could own Boston Dynamics, a world leader in mobile robots, whose products include the agile anthropomorphic robot Atlas, a 1.8m bipedal humanoid robot designed for a variety of search-and-rescue tasks.
Knowing when, how, or even if Britain will Brexit is the stuff of forecasting. Most predictions are likely to be exactly wrong. By contrast, we can suggest with confidence that the world in five or 10 years will have relatively more adults than children, who on average will be a little older than now, and will be working with smarter machines that are increasingly humanoid in their behaviour and thinking.
Investing based on forecasts might feel exact but is more likely to be folly. Investing on the back of structural drivers will feel inexact, and sometimes fuzzy. But being approximately right is a far more powerful force in driving successful investment decisions than being exactly wrong.
• Dr Saville is CEO of Cannon Asset Managers.
Would you like to comment on this article or view other readers' comments?
Register (it’s quick and free) or sign in now.
Please read our Comment Policy before commenting.