“It's tough to make predictions, especially about the future.” ― Yogi Berra
The Wall Street Journal recently ran a story describing the treasury bond rally that few saw coming. The most striking thing to us about the article were not the bond managers who bought the long-term treasury (check back for more on long treasuries in a later blog post) but the practice of forecasting and the dismal predictions from practitioners of the dismal science.
“We have two classes of forecasters: Those who don’t know — and those who don’t know they don’t know.” — economist John Kenneth Galbraith
Going into 2019 the average forecast from economists surveyed by the Wall Street Journal was for the 10-year treasury to end the year yielding more than 3.35%, and one can see from the chart above that most of them expected it to rise.
These forecasters were presumably armed with all kinds of economic data as well as lengthy resumes that detail their post-graduate schooling at very expensive, distinguished universities and their lengthy, on the job experience. So how did so many experienced, smart, well informed, and well-educated forecasters get it so wrong?
We think there are two main reasons: they didn’t know and there is comfort in the consensus. Humans are herd like creatures and in public prediction games there is career risk in being out of consensus and wrong. If you are going to fail, fail conventionally. It is also possible that the forecaster’s background and experience worked against them. When making predictions about uncertain events, research shows that more data and education only serve to increase confidence but not accuracy. These dismal scientists the Wall Street Journal surveyed were wrong, but at least they were confidently wrong together.
“Forecasts usually tell us more of the forecaster than of the future.” — Warren Buffett
Mr. Buffett is the great teacher in investing and his quote here is quite instructive. Often when one is forecasting, the forecaster projects their desires or worldview onto the forecast. As an example, a forecaster might think to themselves (subconsciously) “I think interest rates are too low and they should be higher because they have been higher in the past.” Indeed, this was the consensus forecast in late 2018.
The goal should be to make a prediction that reflects the way things are, not how we hope or wish for them to be. Many economists, including those at the Fed, hope and wish for rates to be higher but that may not reflect the state of the world as it is today.
On being “wrong” and how this influences our thinking
This is all well and good, but we are picking on (perhaps unfairly) some poor economists who collectively made a bad call. What does it mean for what we do in portfolios? It’s simple; at Accretive we try not to make too many forecasts. Instead, we seek to build a solid framework for making investment decisions on how we allocate capital. We then seek to continually improve the framework. In part, we seek to see and understand the investing world for how things are and to build portfolios that contemplate various good and bad scenarios. We much prefer forecasts with a range of outcomes rather than those centered around one number. When we do make some kind of prediction, we recognize that we may be wrong and try to be cognizant of the risks that could make something play out differently than we initially thought. We also try to hedge our ignorance by avoiding all or nothing bets.
Investing has a high error rate and mistakes will be made, perfection is unattainable. Humility is important, and if we are wrong about something, we try to admit it quickly and not prolong the problem by remaining wrong. We do so by being open to changing our mind. We do pre-mortems to memorialize our thinking in the moment, which limits our ability to change a narrative to fit the facts. We then conduct post-mortems which allow us to see where our thinking could be improved. In our view, everything creates an opportunity to learn and improve our process, and that is especially true when we are wrong about something.
