The hard part about predictions
Tren Griffin recently published an article about forecasting
Why is it so Hard to Forecast the Future?
For most of human history the life experiences of people have been overwhelmingly linear. Human are accustomed to…
which is interesting in and of itself but also closes with a quote from Tetlock & Mauboussin:
The predictions of the average expert were ‘little better than guessing,’ which is a polite way to say that ‘they were roughly as accurate as a dart-throwing chimpanzee.’ When confronted with the evidence of their futility, the experts did what the rest of us do: they put up their psychological defense shields. They noted that they almost called it right, or that their prediction carried so much weight that it affected the outcome, or that they were correct about the prediction but simply off on timing.
In the Fall of 2015, John Bogle and Michael Nolan published “Occam’s Razor Redux: Establishing Reasonable Expectations for Financial Market Returns” in the Journal of Portfolio Management. Like many other forecasters, they saw relatively muted returns in the future.
Thus, the prospective nominal investment return on stocks seems likely to run in the range of 7%, well below the long-term rate of about 9%. […] A reversion to that mean would entail an 11% decline in the P/E, equivalent to about one per- centage point per year, reducing stocks’ annual investment return of 7% to 6% per year in nominal terms.
They settle on this 6% nominal return as their point forecast for the next decade.
One-tenth of that decade has passed so we can do a preliminary check on how things are going, keeping in mind that these are extremely preliminary results and their forecast wasn’t for a straight line of 6% nominal returns every year.
I’ll use September 2015 to September 2016 as the window to look at. I chose September because the article was published in the fall edition, with no better evidence of a good start date I chose the beginning of fall.
Over that period the S&P 500 had a total return (i.e. including dividends) of 13.366% according to https://dqydj.com/sp-500-return-calculator/
Obviously, that’s quite a bit ahead of the 6% average return Bogle predicted. Of course, we could still hit that 6% average if the next nine years’ returns are low enough.
What kind of 9-year forecast do we need to stay on target with the original 10-year forecast of 6%?
It is obviously still very possible to hit the original 6% forecast but each week & month that goes by without the low returns we’re warned against showing up makes hitting the 6% target harder.
And the months since September 2016 have only increased the trend: now the annualised return is up to 14.155%. Which would require the next 8 years and 8 months to be even lower than 5.2%. That is still possible — a 10% drop is enough to wipe out the gains of the past year and drops like that are likely some time in the next decade.
But that’s the other hard part of predictions: you also have to get the timing right. Did the decade of low returns start in 2015? Or will they start in 2017? Is Bogle’s 10-year forecast correct but just off by 2 or 3 years?
Bogle doesn’t claim that his predictions are 100% accurate. He actually says they are only about 65% accurate.
But the gap between 65% accurate and 100% accurate is pretty large. It means forecasting 3.5% returns and they turn out to be 11.1% or 3% returns and they turn out to be 9.3% returns. Or forecasting 17.9% and they turn out to be only 6.7%.
Given a margin of error that large, it is hard to say what actions an actual investor should take based on a prediction like that.
It is a slightly different context (talking about the equity risk premium rather than forecasted equity returns) but a recent article by Aswath Damodaran about the resilience of US equities has an example of the difference between point estimates and margins of error.
if you decide to use 6.24%, the difference between the arithmetic average returns on stocks and bonds from 1928–2016, as your historical risk premium, that number comes with a standard error of 2.26%. That would mean that your true equity risk premium, with 95% confidence, could be anywhere from 1.72% to 10.76% (plus and minus two standard errors).
What do you do with a forecast that says “the real value is somewhere between 1% and 11%”? That’s essentially what Bogle — and most other forecasters — are saying.
(And note that, in that article, Damodaran is forecasting 8.14% returns for stocks in 2017; which would put Bogle’s 6% even further out of reach.)