The Use and Misuse of the CAPE Ratio

However, as Graham and Dodd noted, there’s really nothing special about using the 10-year average. Other time horizons also provide information on future returns.

For example, research on the expected equity premium, including Aswath Damodaran’s paper “Equity Risk Premiums (ERP): Determinants, Estimation and Implications,” has found that the best predictor of future equity returns is current valuations – whether using measures such as the earnings yield (E/P) derived from the Shiller CAPE 10 (or for that matter, the CAPE 7, 8 or 9) or the current E/P – not historical returns.

A review of the evidence led Damodaran to conclude: “Equity risk premiums can change quickly and by large amounts even in mature equity markets. Consequently, I have forsaken my practice of staying with a fixed equity risk premium for mature markets, and I now vary it year to year, and even on an intra-year basis, if conditions warrant.”

Forecasts of returns are important

It is impossible to build an investment plan without estimating the return to stocks (as well as to bonds and any alternative investments). One reason is that the estimate of returns determines your need to take risk – how high an allocation to equities and other risky assets you will need to reach your goal.

If your estimate is too high, it’s likely you won’t have sufficient assets to reach your retirement goal. If it’s too low, it could lead you to allocate more to equities, which means taking more risk than necessary. Alternatively, it could lead you to lower your goal, save more or plan on working longer.

Unfortunately, there are many mistakes made when looking at the historical record of the CAPE 10 in terms of its forecasting accuracy. The most common error is to cite how much error there is in the forecast – the R-squared value is about 40%.

In a November 2012 paper, “An Old Friend: The Stock Market’s Shiller P/E,” Cliff Asness, of AQR Capital Management, found that the Shiller CAPE 10 provides valuable information. Specifically, he found 10-year-forward average real returns drop nearly monotonically as starting Shiller P/Es increase.

Additional findings

Asness also found that, as the starting Shiller CAPE 10 ratio increased, worst cases became worse, and best cases became weaker. Additionally, he found that, while the metric provided valuable insights, there were still very wide dispersions of returns. For instance:

• 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 that not only are future expected returns lower, but the best outcomes are lower and the worst outcomes worse. And the reverse is true as well – lower starting values mean that not only are future expected returns higher, the best outcomes are higher and the worst outcomes less poor.

However, it’s also extremely important to understand a wide dispersion of potential outcomes, for which we must prepare when developing an investment plan, still exists – high (low) starting valuations don’t necessarily result in poor (good) outcomes. In other words, investors should not think of a forecast as a single point estimate, but only as the mean of a wide potential dispersion of returns.

The reason for the wide dispersion, as Damodaran noted, is mostly that risk premiums are time varying (if they were not, there would be no risk in investing!). It is the time-varying risk premium, what John Bogle called the “speculative return,” that leads to the wide dispersion in outcomes.

Dealing with dispersion

The fact that a wide dispersion of returns occurs around the mean forecast is why a Monte Carlo simulation is a valuable planning tool. While the input includes an estimated return, it recognizes the risks of that mean forecast not being achieved – which is why volatility is another input.

Because most simulators allow you to examine thousands of alternative universes, they allow you to test the durability of your plan – you can see the odds of success (such as not running out of money, or leaving an estate of a certain size) across various asset allocations and spending rates.

The time-varying risk premium is also why an investment plan should include a 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.

That 40% explanatory power provides significant information that investors can use to build plans. However, you must not make the mistake of overestimating the forecasting power of the CAPE 10 metric and treat that forecast as what will happen. Instead, it should be used to help determine your need to take risk and then, with the understanding that risk premiums are time varying and a wide dispersion of potential outcomes is likely, to help build a Plan B.

Another mistake that investors make when criticizing the use of the CAPE 10 is that it doesn’t work as a timing tool.

Timing the market using the CAPE 10

While valuations provide information on future returns, research has found they do not provide information that allows investors to profitably time the market. For example, Cliff Asness, Swati Chandra, Antti Ilmanen and Ronen Israel, authors of the study “Contrarian Factor Timing Is Deceptively Difficult,” which appeared in the 2017 Special Issue of The Journal of Portfolio Management, found “lackluster results” when investigating the impact of value timing (in other words, whether dynamic allocations can improve the performance of a diversified, multistyle portfolio). They write: “Strategic diversification turns out to be a tough benchmark to beat.”

Despite the evidence, many investors ignore the findings and try to use CAPE 10 valuations to time markets. They might shift from stocks to bonds when the CAPE 10 is above its long-term average, and shift from U.S. to international when international valuations are lower (as they have been for a number of years now).

As we just discussed, this has not worked well. However, blaming the CAPE 10 for its failure as a timing tool is like blaming the fork for its failure as a useful tool to eat soup. It is not intended to be used to time markets, only to forecast mean expected returns.

Consider the following example. As of December 2018, the CAPE 10 earnings yields (which provide the best estimate of future real returns) was 3.6% for the U.S., 5.8% for developed non-U.S. markets, and 7.3% for emerging markets. Some investors take this to mean you should underweight U.S. stocks and overweight emerging markets.

This is the wrong use of the CAPE 10 for the simple reason that doing so ignores risk. It’s the equivalent of saying junk bonds with higher yields are better investments than U.S. Treasury bonds with lower yields. The information provided is that investors believe that international stocks are riskier and thus have higher expected returns as compensation for that risk.

The efficiency of the markets means that all risky assets should have similar risk-adjusted returns. Thus, your starting point when determining your asset allocation should be the global market capitalization, which is currently about one-half U.S., three-eighths developed non-U.S. and one-eighth emerging markets. Having set your asset allocation, you should stick with it, rebalancing as needed.

Summary

The CAPE 10 provides us with valuable information (as do other current metrics). However, it’s important that the information be used in the right way, as misusing it can lead to bad outcomes and the failure of plans.

You should not use a valuation metric in a deterministic way (“I’m going to earn X%”). Instead, the forecast should only be used in a probabilistic manner. And you should not use valuations to time the market, meaning shifting allocations toward higher expected returning assets.

Larry Swedroe is the director of research for The BAM Alliance, a community of more than 130 independent registered investment advisors throughout the country.

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