The Eight Best Predictors of the Stock Market

In the WSJ, Mark Hulbert look at the eight best metrics to predict the stock market. The best is from the blog Philosophical Economics.

The blog’s indicator is based on the percentage of household financial assets—stocks, bonds and cash—that is allocated to stocks. This proportion tends to be highest at market tops and lowest at market bottoms.

According to data collected by Ned Davis Research from the Federal Reserve, this percentage currently looks to be at 56.3%, more than 10 percentage points higher than its historical average of 45.3%. At the top of the bull market in 2007, it stood at 56.8%.

Ned Davis, the eponymous founder of Ned Davis Research, calls the indicator’s record “remarkable.” I can confirm that its record is superior to seven other well-known valuation indicators analyzed by my firm, Hulbert Ratings.

This metric has an R-square of 0.61. Here are the seven others:

• The Q ratio, with an R-squared of 46%. This ratio—which is calculated by dividing market value by the replacement cost of assets—was the outgrowth of research conducted by the late James Tobin, the 1981 Nobel laureate in economics.

• The price/sales ratio, with an R-squared of 44%, is calculated by dividing the S&P 500’s price by total per-share sales of its 500 component companies.

• The Buffett indicator was the next-highest, with an R-squared of 39%. This indicator, which is the ratio of the total value of equities in the U.S. to gross domestic product, is so named because Berkshire Hathaway Inc.’s Warren Buffett suggested in 2001 that is it “probably the best single measure of where valuations stand at any given moment.”

• CAPE, the cyclically adjusted price/earnings ratio, came next in the ranking, with an R-squared of 35%. This is also known as the Shiller P/E, after Robert Shiller, the Yale finance professor and 2012 Nobel laureate in economics, who made it famous in his 1990s book “Irrational Exuberance.”

The CAPE is similar to the traditional P/E except the denominator is based on 10-year average inflation-adjusted earnings instead of focusing on trailing one-year earnings.

• Dividend yield, the percentage that dividends represent of the S&P 500 index, sports an R-squared of 26%.

• Traditional price/earnings ratio has an R-squared of 24%.

• Price/book ratio—calculated by dividing the S&P 500’s price by total per-share book value of its 500 component companies—has an R-squared of 21%.

According to various tests of statistical significance, each of these indicators’ track records is significant at the 95% confidence level that statisticians often use when assessing whether a pattern is genuine.

However, the differences between the R-squareds of the top four or five indicators I studied probably aren’t statistically significant, I was told by Prof. Shiller. That means you’re overreaching if you argue that you should pay more attention to, say, the average household equity allocation than the price/sales ratio.

For the record, I’m a bit skeptical of these metrics. Sure, they’re interesting to look at, but I try to place them within a larger framework.

It’s not terribly hard to find a measure that shows an overvalued market and then use a long time period to show the market has performed below average during your defined overvalued period. That’s easy.

The difficulty is in timing the market. For example, during the housing bubble, what I found interesting was how many people were right that housing was indeed in a bubble.

Lots of people realized it. Also, lots of people thought it would burst in 2004. Then in 2005. Then in 2006. They were right, but their timing was way off. This happened to Michael Burry of The Big Short fame. Even if you know the market is overpriced, that doesn’t tell you much about how to invest today.

Posted by on August 6th, 2018 at 11:48 am


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