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Investment Truths Aren't Always Bite-Size

Often, things aren't as simple as they are presented.

Perhaps Not Twins There are several billion differences between your writer and AQR chief Cliff Asness. One of us attained a finance Ph.D., worked for Goldman Sachs, founded a business, and became exceedingly wealthy. The other read Shakespeare, until landing an $18,000 position from a startup that didn’t hire people who expected more.

We do, however, agree that much that passes for investment knowledge comes with asterisks. As with this column, Cliff's notes frequently poke at conventional wisdom. Financial pundits tend to present issues as being more straightforward than they are, because, of course, that is what the public wants. According to her website, Suze Orman sold 3 million copies of The 9 Steps to Financial Freedom. In contrast, the world's leading academic investment publication, The Journal of Finance, has a circulation of … 8,000.

Two Topics Cliff's latest missive, "It Ain't What You Don't Know That Gets You Into Trouble," tackles two subjects:

1) Can current stock valuations be used to forecast future returns?

2) What is the size of the small-company effect?

His answers:

1) Probably yes, but not for the reason that you think.

2) Nothing.

Both arguments are based on recent AQR papers, which do the dredging. Of course, the topics are not novel; people have wondered for decades if stocks' price/earnings multiples predict their futures, and for a quarter century now, researchers have chipped away at the small-company effect. (The effect was originally documented in a dissertation by Rolf Banz and later certified by professors Ken French and Eugene Fama.) But in each case, AQR's researchers offer fresh insights.

Storytelling "Long Horizon Predictability: A Cautionary Tale" addresses the obvious problem with making predictions from long-term stock market figures, such as the Shiller P/E ratio (which uses the past decade's worth of inflation-adjusted earnings): There aren't enough data points. Not within a single country, and combining countries within a study is, to put the matter mildly, problematic.

Previous researchers compensated for the shortage of evidence through statistical dodges, such as using overlapping time periods to raise the number of semi-independent observations. AQR's authors are unimpressed. "Intuitively, no matter how the data is broken down, you can't get around the issue of short sample sizes. Therefore, findings of long-horizon predictability are illusory and reported statistical significance levels are way off."

They concluded, "We show that the benefit to using overlapping observations is marginal because the predictive variable tends to be highly persistent. This statement is a fact and, without building economic structure into the modeling, there is little hope of documenting reliable statistical evidence of long-horizon predictability. Standard statistical packages that calculate t-statistics based on adjustments for overlapping observations do not help."

This finding echoes my thoughts from this 2014 column, although we arrived at those views in very different ways. Beliefs that high stock-market prices lead to lower future returns (and vice versa) are based more on intuition than they are on hard evidence. The relationship seems logical; we notice apparent confirmations (for example, 1999's steep P/E ratios signaling poor future results, and 2009's lower values indicating stronger performances); and we arrive at a theory. But the theory has little scientific grounding.

However, writes Cliff, if the utility of the Shiller P/E ratio (and other similar measurements) is more of a story than a demonstrated fact, it is nonetheless a useful story. Statistical significance aside, it remains true that U.S. stocks have tended to perform better after they are priced modestly, and worse after they have been priced steeply. In addition, this behavior accords with "economic intuition." Thus, he states, "We'd still go with a lower forecast for long-horizon equity returns today because CAPE [cyclically adjusted price/earnings] is high … we're just a bit less sure now than before."

Nothing There? He is considerably more certain about the small-company effect. "There isn't one … In fact, there never was a size effect. Among other issues, the data used to discover it was flawed (though no fault of the author, that was the data back then) in a way that favored small stocks."

"There never was a size effect" seems to me a trifle strong. (Another thing that Cliff and I have in common: Neither of us is immune to, on occasion, oversimplifying matters.) "Fact, Fiction, and the Size Effect," by three AQR employees, reports that from 1936 through 1975, there was a "weak" size effect. The effect did not deliver much, and it wasn't statistically significant by all measures, but one could reasonably argue that it existed.

But not in the strong form that was originally promulgated. A major reason for the discrepancy, suggest the paper's authors, is that the early studies neglected companies that were delisted--that is, stocks that dropped off the exchanges. Such was not their intent, but the database that they used (CRSP) was not then complete. When the true, lower returns for the delisted stocks are considered, what once appeared to be a fat advantage for small firms dwindles to slender.

Over the past 30 years, state the authors, the effect has further weakened. (This should come as no surprise to anybody who owns a small-company stock fund!) Since 1986, there is not even slight evidence of a small-cap effect. The authors hint that the act of observation may be to blame. "Since the slew of publications on the size effect, there has been no significant positive premium associated with small-cap strategies." Perhaps. On the other hand, momentum strategies have been documented for more than 20 years, and they continue to hum along.

"You get what you pay for" fits neatly onto a bumper sticker, and requires no further explanation. In most cases, though, an investment "truth" is not as absolute as would first appear.

First-Name Basis Until recently, this column would have referred to AQR's founder as "Mr. Asness," rather than "Cliff." However, after spending five hours in the same room with him on Monday of last week, I feel entitled to use the familiar. Cliff, of course, is welcome to call me John. It is the least that I can do.

(Here is a picture of the soiree. You may be able to identify some of the attendees. As for me, yes, I know--my photo needs updating!)

John Rekenthaler has been researching the fund industry since 1988. He is now a columnist for and a member of Morningstar's investment research department. John is quick to point out that while Morningstar typically agrees with the views of the Rekenthaler Report, his views are his own.

The opinions expressed here are the author’s. Morningstar values diversity of thought and publishes a broad range of viewpoints.

The author or authors do not own shares in any securities mentioned in this article. Find out about Morningstar’s editorial policies.

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John Rekenthaler

Vice President, Research
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John Rekenthaler is vice president, research for Morningstar Research Services LLC, a wholly owned subsidiary of Morningstar, Inc.

Rekenthaler joined Morningstar in 1988 and has served in several capacities. He has overseen Morningstar's research methodologies, led thought leadership initiatives such as the Global Investor Experience report that assesses the experiences of mutual fund investors globally, and been involved in a variety of new development efforts. He currently writes regular columns for and Morningstar magazine.

Rekenthaler previously served as president of Morningstar Associates, LLC, a registered investment advisor and wholly owned subsidiary of Morningstar, Inc. During his tenure, he has also led the company’s retirement advice business, building it from a start-up operation to one of the largest independent advice and guidance providers in the retirement industry.

Before his role at Morningstar Associates, he was the firm's director of research, where he helped to develop Morningstar's quantitative methodologies, such as the Morningstar Rating for funds, the Morningstar Style Box, and industry sector classifications. He also served as editor of Morningstar Mutual Funds and Morningstar FundInvestor.

Rekenthaler holds a bachelor's degree in English from the University of Pennsylvania and a Master of Business Administration from the University of Chicago Booth School of Business, from which he graduated with high honors as a Wallman Scholar.

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