by Jeff Miller
Caption photo: Prof. Shiller
Yale Professor Robert Shiller is widely celebrated for his Cyclically Adjusted Price Earnings (CAPE) ratio. The method uses ten years worth of trailing earnings to account for the business cycle. This allows you to have a “normalized” growth rate. Prof. Shiller has created a database going back into the 19th century.
To my surprise, many of the skeptics in the trading community that would normally disparage such an effort as an irrelevant ivory tower enterprise have rushed to embrace these findings.
There has been a recent debate about the Shiller method. I was not going to comment– what more is there to say? — but a recent joint appearance of Professors Shiller and Jeremy Seigel created new and important information. No one else seems to have noticed, perhaps because you had to go through 45 minutes of painful political diatribe to get to the main act. Through the wonders of TIVO, I have done the work and you can enjoy the result.
I’ll start with some background on my own interpretation, give a nod to the current debate, and then highlight the key conclusions from the exchange.
The Best Interpretation of CAPE
Since I know that most people do not follow the links and read background, I am going to quote my own article from a year ago. Regular readers understand this theme, and I hope they have joined me in profiting from it.
…right at the market bottom, I wrote an article reviewing the various approaches to valuation and explaining why they would be no help. You needed to step away from backward-looking methods.
A Small (but humorous) Digression
The earnings debate reminded me of an article from decades ago. One of my favorite sportswriters, Pete Axthelm, wrote for the New York Herald Tribune and Sports Illustrated. He brought sports to the masses through Newsweek and also wrote some highly-regarded books. Last year he was inducted into the US Basketball Writers Hall of Fame. He died, far too soon, at age 47 in 1991.
In the days before computers, one of Pete’s columns reviewed a system for betting on NFL games. It was a betting wheel, with cardboard overlays and windows. You lined up one wheel for the point spread, another for the difference in team winning percentage, and a third for…..well, you get the idea. Then you looked at the “result” window and it said either “Bet” or “No Bet.” Pete’s review tried all of the games for that week and he kept getting “No Bet” as the answer. That was probably good advice, but it was frustrating for a man of action. He also was the handicapping expert on some of the networks. His conclusion was that the device must have been put out by Gambler’s Anonymous!
We can now see that this was one of the first examples of multi-variate data mining, a precursor to modern predictive methods in sports and the markets.
The Modern Equivalent
What brought this to mind was the many reminders about how over-valued stocks are if you look at trailing earnings. You can see the Shiller PE ratio in many places, but I favor this chart.
You can see that this approach will make sure that you get a chance to buy stocks every thirty years or so. The author of the article suggests that forward earnings are “notoriously unreliable.” True enough. When Pete tried to pick next week’s football games he was only about 50-50. Even a small edge made a lot of money, but you would have to call the forecasts “unreliable.”
Meanwhile, the scores of last week’s games are available in the newspaper. Unfortunately, the betting window is closed.
For those participating in the stock market, the earnings season will be important. For those who are convinced that stocks are overvalued because of write-downs in 2008, you can wait a long time for those earnings to roll out of the ten-year window.
The Current Debate
Here we are — a year later — and little has changed. Many highly-regarded sources (John Hussman, Henry Blodget, David Rosenberg, and Doug Short come to mind) write repeatedly about excessive market valuations. The Shiller method is the key piece of evidence.
The message, as interpreted by others, is that this is a dangerous time to own stocks. Shiller himself is on record predicting only a 1.3% annualized growth rate for the S&P 500 over the next ten years.
The Wall Street Journal highlighted a challenge from David Bianco and Prof. Seigel. The always provocative Joe Weisenthal explained Why The Shiller P/E Ratio Is Totally Useless For Investors.
Shiller’s Own Advice
A well-staged discussion can provide fresh information. Challenged by Kudlow and Siegel, Shiller stated the following:
- A young person with a long time horizon should have a 50% stock allocation. (This is a dramatic deviation from most interpretations of his findings).
- The market bottom in 2009 was not really a great time to invest. It was only a little better than average.
- If you want to make a big commitment, you should wait for times like 1981. (He did not mention that this would also require a double-digit interest rate).
You can verify all of this by watching the video, especially after the 4 minute mark.
The real test for the equity investor is not overall market valuation, but finding attractive stocks and sectors. For those of us who look forward, there is an abundance of choices. Many names are cheaper in earnings terms than they were two years ago. Meanwhile, the exaggerated use of Shiller’s findings has contributed to a big whiff for the average investor.
Secular Cycles for Stocks by Ed Easterling
Regression to Trend: A Perspective on Long-Term Market Performance by Doug Short (at dshort.com)
Is the Stock Market Cheap? by Doug Short (at dshort.com)
Market Valuation: The Message from the Q Ratio by Doug Short (at dshort.com)
Using Forward Earnings Estimates by Jeff Miller
Profiting from Forward Earnings Estimates by Jeff Miller
Bull or Bear? Let History Be the Guide by John Lounsbury (at Seeking Alpha)
Consensus: A Groundhog Decade for Stocks by Ed Easterling
Jeff Miller has been a partner in New Arc Investments since 1997, managing investment partnerships and individual accounts. He has worked for market makers at the Chicago Board Options Exchange, where found anomalies in the standard option pricing models and developed new forecasting techniques. Jeff is a Public Policy analyst and formerly taught advanced research methods at the University of Wisconsin. He analyzed many issues related to state tax policy and provided quantitative modeling which helped inform state and local officials in Wisconsin for more than a decade. Jeff writes at his blog, A Dash of Insight.