The Risk of Incorrect Return Assumptions
"It is better to be roughly right than precisely wrong."
-John Maynard Keynes
Historically, the S&P 500, a common benchmark for the US stock market has returned approximately 10% annualized (1926-2015). After accounting for inflation (CPI) over the same period, the real return of the S&P 500 was ~7%. Over the same time period, US bonds (represented by Five-Year US Treasury Notes) returned approximately 5% before inflation and ~2% after.
Determining the correct return assumptions to use in a forward-looking financial plan is impossible. Without knowing the future, we’re required to make a [hopefully educated] guess. One of the easiest ways to do this is to use historical returns, such as those noted above, which is precisely what many online calculators and financial advisors do. After all, it’s simple and defensible. Unfortunately, it may also be overly optimistic and could result in running out of money long before your financial plan projected. This is only truer when you realize that simply using historical market returns doesn't account for the costs of actually implementing an investment plan, such as the advisor’s own fee.
Some might argue that the investments they choose will outperform, thus making up for any fees, and that by performing a Monte Carlo Analysis (a stress test that models thousands of random scenarios) they can properly simulate the uncertainty of future returns. Both arguments are faulty. First, study after study has illustrated the difficulty and unlikelihood or persistently outperforming appropriate benchmarks. Second, while a Monte Carlo simulation is incredibly useful for modeling sequence of return risk and the probability of unfavorable outcomes, one of the primary assumptions driving the simulation is the average annual return. If the average return assumption is inappropriately optimistic, all the results will be upwardly biased.
If it’s dangerously optimistic to use historical return assumptions in forward-looking financial plans, what are we to do? Most importantly, we need to give up our desire for precision. The world of finance is filled with mathematics and vast data sets, which often gives the false impression that we can engineer plans and portfolios with the same level of precision that goes into designing bridges. However, unlike gravity, market assumptions are not a constant. As a result, we should formulate reasonable but conservative assumptions, build flexibility into our plans, and be willing to adapt along the way.
Models that attempt to calculate the expected return of stock markets are very noisy and imprecise as there are so many factors to account for, but many indicate that future stock returns are expected to be lower than they have been historically. How much lower is up for debate and also depends on the time period considered. The important takeaway is simply that the historical figure of 10% (7% after inflation) seems too high by almost all accounts.
Models that predict future returns for high-quality bonds tend to be less noisy than stocks as the future interest payments are known (barring any default). As a result, a relatively simple and historically accurate measure for high-quality bonds has simply been to look at the current yield-to-maturity. As of 12/31/2015, the yield of Five-Year US Treasuries was 1.76% and the yield for Thirty-Year US Treasuries was 3.01%. While it may be reasonable to assume that bond yields will eventually increase toward historical levels, the reality, at least for the short and intermediate term, appears to be that bonds also have an expected return several percentage points lower than the historical figure of 5%.
Any financial plan that uses historical returns as a direct proxy for future returns (which based on discussions with colleagues appears to be many) has significant hidden risks. While your assumptions will have no effect on the actual returns delivered by the market, they will impact many other aspects of your financial plan including how much you need to save and how much you can spend. Using more conservative "expected” returns instead of optimistic historical returns reduces the likelihood that you’ll need to work longer or spend less than you planned for. If it turns out that you estimated too low then you’ll end up with more money than you expected and have greater flexibility in the future.