Research Affiliates: How Can ‘Smart Beta’ Go Horribly Wrong?

February 23, 2016

The lofty past returns not only laid a foundation for lofty expectations, but also led to valuations that virtually guaranteed far lower future returns. As noted by Arnott and Bernstein (2002), investors in 1999 should not only have adjusted past returns to remove the impact of rising valuation levels, they should also have adjusted expectations to reflect the lowest-ever stock market yields and the above-average real bond yields.6 Investors could even have gone further, adjusting expectations to reflect the substantial likelihood of mean reversion. The higher equity valuations of today continue to translate into lower future returns than most investors expect.

Nowadays, astute observers increasingly "get it," at least to the point of subtracting valuation gains from past returns. A 2015 survey of investment consultant return expectations produced an average forward "long-term" (10-year) U.S. nominal equity return of 6.8% a year7; at the start of the century, return expectations over a similar horizon were in the double digits.8,9 After 15 years and two punishing bear markets, investors are figuring out past returns need to be adjusted for the sometimes large impact of rising valuations, and expected returns need to be adjusted for the sometimes large impact of mean reversion. Even after the stellar bull market since early 2009, the annualized real return on U.S. stocks from 2000 to 2015 has averaged a scant 1.9% (not even matching the average dividend yield), while U.S. bonds have delivered an outsized real return of 3.6%. The "excess return" for stocks has been negative by a daunting 1.7% a year.

Our parable holds a relevant lesson for smart beta investors: a lengthy return history, even 50 years, does not guarantee a correct conclusion. Investors need to look under the hood to understand how a strategy or factor produced its alpha. We compare several popular strategies' current valuations relative to history, and find that for many, much of the historical value-add—in some cases, all!—has come primarily from the "alpha mirage" of rising valuations.

Academia is no less prone than the practitioner community to be a slave to past returns. Anomalies and factor returns tend to appear and then fade, depending on recent performance. Of course, no one will bother to publish a factor or a strategy that fails to add value historically; this encourages data mining and selection bias. In recent years, several hundred "factors" have been published, most showing statistically significant "alpha" and a path to higher future returns.10

Value-add can be structural (hence, plausibly a source of future alpha) or situational (a consequence of rising enthusiasm for, and valuation of, the selected factor or strategy). Few, if any, of the research papers in support of newly identified factors make any effort to determine whether rising valuations contributed to the lofty historical returns. The unsurprising reality is that many of the new factors deliver alpha only because they've grown more expensive—absent rising relative valuations, there's nothing left!

The Impact Of Valuations On Returns: The Value Factor

The value effect was first identified in the late 1970s, notably by Basu (1977), in the aftermath of the Nifty Fifty bubble, a period when value stocks were becoming increasingly expensive, priced at an ever-skinnier discount relative to growth stocks. More recently, for the past eight years, value investing has been a disaster with the Russell 1000 Value Index underperforming the S&P 500 by 1.6% a year, and the Fama–French value factor in large-cap stocks returning −4.8% annually over the same period. But, the value effect is far from dead! In fact, it's in its cheapest decile in history. In Figure 1 we compare the performance of the classic Fama–French value factor11 (black line) with changes in its relative price-to-book (P/B) valuation levels (red line) from January 1967 to September 2015. When the black line is rising, value stocks are becoming more richly priced (i.e., the market is paying a shrinking premium for growth) and value is outperforming. Conversely, when the black line is falling, value stocks are almost always getting cheaper (i.e., the market is paying up for growth stocks) and value is underperforming. (Click here for a full description of the simulation methodology.)

Research Affiliates

For a larger view, please click on the image above.

The red line shows the relative P/B valuation level (the average P/B ratio for the value portfolio divided by the average P/B ratio for the growth portfolio) as it changes over time. Because value always trades cheaper than growth—by its very definition—the valuation ratio, shown on the right scale, often is far lower than 1.0. When the red line is rising, value is winning (i.e., getting more richly priced than it was before, relative to growth), and when the red line is falling, growth is winning (i.e., getting more expensive, relative to value). Not surprisingly the black and red lines move up and down together. The lines diverge, however, which means value has historically had a structural alpha, not wholly reliant on becoming more expensive.

How many practitioners who rely on the value factor take the time to gauge whether the factor is expensive or cheap relative to historical norms? If they took the time to do so today, they would find value is currently cheaper than at any time other than the height of the Nifty Fifty13 (1972–73), the tech bubble (1998–2003), and the global financial crisis (2008–09).

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