Markets: News  

By Brett Arends

Can an ordinary investor beat the market without being very lucky?

Invest in stocks that have low volatility. Invest in stocks that are cheap in relation to current profits and sales. Invest in stocks of companies with strong balance sheets and stable, growing businesses.

And then comes the critical bit: Wait for a bear market.

Because it's not until a bear market that these stocks will really shine, crushing the market indexes and setting you on the path to an early and prosperous retirement.

This at least is the theory laid out in a new paper by David Blitz, head of quantitative research at Netherlands-based fund management firm Robeco. Blitz, a highly-regarded number-cruncher who has been producing interesting research papers for the better part of 20 years, has taken a deep dive into the oldest debate on the Street: Can an ordinary investor beat the market, meaning the indexes like the S&P 500, or not?

(Or, more to the point: Can an ordinary investor beat the market without being very lucky?)

For a long time, especially during the 1970s, 1980s and 1990s, the conventional wisdom among financial theorists was that you couldn't. The market was "efficient," meaning, in effect, that when it comes to stocks, "the price is right." The theory was that stock market prices reflect all publicly known information, including risks. You might think you knew better than the market, but you didn't. Stock pickers would end up underperforming the basic indexes, especially after costs.

Read:Vanguard index funds lose out to its own stock-picking fund

But around the mid-1990s some top theorists, including efficient market gurus Eugene Fama and Kenneth French, were forced to admit that this wasn't quite right. Stocks with certain types of characteristics had beaten the market, and had done so predictably or quite regularly, over long periods of time, analysts found.

These included, for example, the stocks in companies that were cheap in relation to current sales, profits and assets--known as "value" stocks. And they included "momentum" stocks, which had outperformed the market indexes over various stretches of recent time up to about a year. And so on.

By about a decade ago, the number of these so-called "factors" that allegedly produced outperformance was over 100. Fund management companies seized on them as a marketing gimmick, calling them "smart beta" and launching funds applying this apparent alchemy.

Some analysts began referring, disparagingly, to the "factor zoo."

Around this time--and those of us in the news business might call this a news "factor," because it was so, so predictable--these factors stopped working.

Many of them, it turned out, hadn't really worked at all. They had simply been the result of data-mining. (Imagine, for example, if I claimed that technology companies "named after deciduous fruit" have beaten the stock market by a wide margin.) They couldn't be replicated in further studies.

So someone who bought "value" or "low volatility" U.S. stocks a decade ago would be poorer today than someone who just bought a simple stock market index fund, such as the State Street SPDR S&P 500 ETF (SPY) or Vanguard Total Stock Market Index Fund . And that's before costs--including fund management fees, trading costs and taxes.

Actually, the only "factor" that seems to have kept performing is so-called "quality."

So is that it?

Not so fast, argues Blitz in his paper this week. Crunching numbers back to the 1960s he's found that overall some of these factors really have worked--but that their outperformance has mainly come during bear markets.

And since 2009, apart from some brief market tumbles along the way, we haven't really had one.

"The average annual return across all factors is a mere 0.9% in bull markets, versus a solid 8.6% in bear markets," he writes. "In other words, factors appear to generate most of their return in bear markets, while barely delivering in bull markets...The results suggest that mispricing builds up gradually during prolonged bull markets (resulting in weak factor returns) and tends to get corrected relatively quickly in bear markets (resulting in large factor payoffs)."

And, he adds, "This result also sheds a new light on factor performance decay, as we estimate that about half of the decay after 2004 can be attributed to a decline in bear markets during this period."

(For a normal investor, as opposed to someone running a "long-short" hedge fund, you have to halve the numbers: So the average gain for factors was about 0.45% a year in bull markets, and around 4.3% in bear markets.)

Blitz finds that overall the most successful factors over time have included quality, low volatility and value.

MSCI has been tracking many of these indexes since the mid-1990s, so I decided to have a look. Very roughly, we've had about six broad periods on the stock market since then: The bull markets of 1994-2000, 2003-7 and 2009-2021, and the bear markets of 2000-3, 2007-9 and (sort of) last year, 2021.

Bottom line? There are huge differences in how these factors performed during bull and bear markets. Even since the mid-1990s, "value" and "low volatility" have beaten the overall market index handily during bear markets. But they have lagged behind it, significantly, during bull markets.

Quality, meanwhile, has beaten the market indexes during both bull and bear markets.

By a curious coincidence, this week white-shoe Boston fund company GMO published a research paper also pointing out that "quality" stocks have tended to outperform. As with low volatility, it is a bizarre anomaly, GMO's Tom Hancock and Lucas White write, because it means investors are earning more over time while taking less risk.

There is, David Blitz tells me, no guarantee that the future will look like the past. So even if quality, value and low-volatility stocks have earned their keep--and then some--in the past by beating the street during bear markets, there is no guarantee they will do so again. Nor, naturally, do we have any idea when the next bear market will begin anyway.

-Brett Arends

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May 27, 2023 14:21 ET (18:21 GMT)

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