“Smart beta” has become a buzzword in investing circles, especially among pension funds and other institutional investors. The term may be new, but the idea isn’t: it’s about looking for ways to capture the returns of an asset class with a strategy other than traditional cap-weighting. These alternatives include fundamental indexing, equal-weighted indexes, low-volatility strategies and a few more exotic techniques.
A growing body of evidence has highlighted the inherent flaws in cap-weighted indexes, which are undeniable. By their nature, cap-weighted indexes give the most influence to the largest companies, as well as any that happen to be overvalued. That’s a potential problem because these are companies that are most likely to underperform the broad market over long periods.
A second potential problem with cap-weighted indexes is concentration. This isn’t an issue in huge markets like the US, or in a multi-country index like the MSCI EAFE. But it’s a concern in small countries like Canada (where Nortel once represented about a third of our entire stock market) and in individual sector funds.
These flaws are real, but if you listen to the chatter of investment firms these days you’d think cap-weighting is a strategy for dunces. This spring the Cass Business School of City University London published a pair of research papers comparing traditional indexing to 13 alternatives. The results were jaw-dropping. Every single one of the alternative strategies produced better backtested results in U.S. markets from 1968 through 2011. During this period, a cap-weighted strategy delivered an annualized return of 9.4%, while all the others came in between 9.8% and 11.5%.
It gets worse. The papers also presented a simulation involving randomly generated portfolios of 1,000 stocks each, which were then equally weighted. “Effectively we programmed the computer to simulate the stock picking abilities of ten million monkeys,” the researchers wrote. And guess what? “Nearly every monkey beats the performance of the market-cap index.” Remember that old joke about active managers losing to monkeys throwing darts at the stock pages? Apparently the monkeys are beating the index funds, too.
I’ve been getting a steady stream of email from readers asking what I think of “smart beta” strategies. They want to know if it’s time to toss aside the cap-weighted Couch Potato portfolios and embrace these new alternatives? I have no plans to do so, and in the next couple of posts I’ll explain why.
No magic in the results
Let’s start by addressing the most obvious question: how is it possible that all of the alternative indexes in the Cass papers beat the cap-weighted benchmark? The answer is actually straightforward: the strategies all tap into “factor premiums” that have been known for decades. That is, they give greater weight to small-cap, value or low volatility stocks, all of which have tended to outperform over long periods.
Fundamental indexes have a built-in value tilt, since they give added weight to companies with low price-to-book ratios, higher dividend yields or other traditional value factors. Equal-weighted indexes give added influence to smaller firms. Other methodologies in the Cass backtests were based on concepts similar to those used by low-volatility ETFs that have appeared during the last year or so.
So there’s no magic here, and there’s nothing wrong with looking for added exposure to one or more of these factors. I’ve often written about Dimensional Fund Advisors, whose funds are designed to capture the value and small-cap premiums. If you understand the risk factors, you’re willing to pay the higher costs, and you have the discipline to stick with the strategies during their inevitable periods of underperformance, I won’t try to talk you out of it.
But for the majority of DIY investors, I’ll continue to recommend simple portfolios with low-cost, cap-weighted index funds. And that’s the way I invest the my own savings. In my next post, I’ll look at whether “smart beta” strategies are really as appealing as they appear on the surface.