- When the CAPE 10 was below 9.6, 10-year-forward real returns averaged 10.3%. In relative terms, that is more than 50% above the historical average of 6.8% (9.8% nominal return less 3.0% inflation). The best 10-year-forward real return was 17.5%. The worst 10-year-forward real return was still a pretty good 4.8%, just 2.0 percentage points below the average and 29% below it in relative terms. The range between the best and worst outcomes was a 12.7 percentage point difference in real returns.
- When the CAPE 10 was between 15.7 and 17.3 (about its long-term average of 16.5), the 10-year-forward real return averaged 5.6%. The best and worst 10-year-forward real returns were 15.1% and 2.3%, respectively. The range between the best and worst outcomes was a 12.8 percentage point difference in real returns.
- When the CAPE 10 was between 21.1 and 25.1, the 10-year-forward real return averaged just 0.9%. The best 10-year-forward real return was still 8.3%, above the historical average of 6.8%. However, the worst 10-year-forward real return was now -4.4%. The range between the best and worst outcomes was a difference of 12.7 percentage points in real terms.
- When the CAPE 10 was above 25.1, the real return over the following 10 years averaged just 0.5%—virtually the same as the long-term real return on the risk-free benchmark, one-month Treasury bills. The best 10-year-forward real return was 6.3%, just 0.5 percentage points below the historical average. But the worst 10-year-forward real return was now -6.1%. The range between the best and worst outcomes was a difference of 12.4 percentage points in real terms.

What can we learn from the preceding data? First, starting valuations clearly matter, and they matter a lot. Higher starting values mean not only are future expected returns lower (and vice versa), but the best outcomes are lower and the worst outcomes worse. However, a wide dispersion of potential outcomes, for which we must prepare when developing an investment plan, still exists—high starting valuations don’t necessarily result in poor outcomes.

It’s also why an investment plan should include what we call “Plan B,” a contingency plan that lists the actions to take if financial assets were to drop below a predetermined level. Actions might include remaining in or returning to the workforce, reducing current spending, reducing the financial goal, selling a home and/or moving to a location with a lower cost of living.

**Buckingham’s Track Record**

Let’s turn now to Buckingham’s prior forecasts of long-term, unconditional (meaning regardless of the horizon) expected returns. Before jumping into the data, however, I’ll describe the framework we use. An acceptable range for the expected return is 1 standard deviation divided by the square root of the number of years in the sample (the standard error of the mean). For example, if we look at a nine-year period, the expected return should be within one-third of 1 standard deviation of the actual return.

The following table presents returns for each of the periods for which we have *at least* 10 years of results available. Each period ends in 2018. Note that over shorter periods, returns are so volatile that measuring the quality of a forecast is not as meaningful an exercise.

For example, while the compound return to U.S. stocks (S&P 500) has been about 10%, there have been very few years (just six of the last 93) in which the return actually fell between 8% and 12%. There have been just 20 years over the last 93 in which the return fell between 0% and 12%. With that caveat in mind, the appendix following this article shows our forecasts and the results for the years 2009 through 2014 (which gives us at least five years of data).

The actual returns data is based on the MSCI All Country World Index. As you review the results, keep in mind that we began the period in 2003, when the U.S. Shiller CAPE 10 was about 23. It reached a nadir of about 14 in February 2009. As of March 7, 2019, it was about 30, almost 40% above the level it was at the start of the period. That increase gave an “unforecastable” tail wind to stock returns, helping to explain why our forecasts generally were below the actual return.

Changes in valuation are what John Bogle called the “speculative return,” by which I believe he meant unforecastable. The record shows there are no good forecasters of changes in valuations, which is why we assume no change.

The table provided is for illustrative purpose only. Expected returns assumptions are based on statistical modeling and are therefore hypothetical in nature and do not reflect actual investment results and are not a guarantee of future results.

As you can see, in all seven cases, the actual annualized returns were inside the acceptable range. The average error in absolute terms was 2.1%. In addition, generally, the longer the period, the more accurate the forecasts. Given that the volatility of equity returns is about 20% a year, this looks like an excellent result. Importantly, especially because the periods all include the 2008 bear market, the worst in the post-World War II era, all the results were well within the expectations set in Monte Carlo simulations. Of course, this finding is not a guarantee that future estimates will have the same degree of accuracy.

The bottom line is that the evidence demonstrates that current valuations have provided useful information in estimating future returns and helps us understand how wide the potential dispersion around those estimates can be.