Even if a strategy is theoretically sound, not all funds that purport to harness it are.
This article originally appeared in the April/May 2014 issue of Morningstar magazine.
Disenchanted with high fees and unreliable performance from professional security selectors, investors have increasingly adopted index funds over the years. But because most assets in the investing world are still actively managed, it is clear that many investors are not ready to settle for “average” performance. Strategic beta funds attempt to improve upon the risk-return characteristics of traditional index funds, while retaining benefits such as transparency, tax efficiency, and low fees. However, a healthy dose of skepticism is in order. If a simple formulaic approach works well without increasing risk, investors may crowd the trade, reducing its effectiveness.
A fund sponsor would not bring a new strategic beta product to market if it did not have appealing back tests. But the results of these back tests may be no more than an exercise in data mining, with no validity out of sample. Consequently, it is prudent to discount back-tested performance. Investors should demand a plethora of evidence from independent sources, such as academic research, that a strategy has worked consistently across different markets and time periods in the past and solid economic intuition about why it should continue to work in the future. There are only a handful of equity strategies that meet this hurdle: value, momentum, quality/profitability, and low volatility. While some researchers may also include a small-cap strategy in this group, the small-cap premium has diminished in recent decades and is unreliable at best. However, a small-cap tilt may still be useful when combined with another strategy.
There are three possible reasons each of these strategies has worked: they may collect a risk premium, harness behavioral biases, or exploit institutional frictions. While investor behavior is not likely to change overnight, strategies that work primarily as a result of behavioral biases, such as momentum, may become less effective as more investors adopt them.
Of course, no strategy will work in every market environment. Each carries unique risks. Investors should be comfortable with these active bets and the intuition behind them. But even if a strategy is theoretically sound, not all funds that purport to harness it are. Funds with similar names can behave very differently from one another. It is necessary to evaluate the portfolio-construction methodology, portfolio characteristics, and sources of past returns to assess whether a fund can meet its stated objective and gauge how it may perform in the future.
To give an example of the type of analysis that is needed to research these funds, let’s study the S&P 500 High Quality Index, which PowerShares S&P 500 High Quality SPHQ tracks. This index targets stocks in the S&P 500 Index with above-average growth and stability of earnings and dividends per share over the most recent trailing 10 years. It assigns its holdings one of three quality grades. Those with the highest grade receive the greatest weights in the portfolio. However, the index assigns equal weights to all stocks with the same grade, which gives it a smaller-cap tilt than that of the S&P 500 Index. This could work against the index’s quality objective because smaller stocks tend to be less profitable than their larger counterparts.
For instance, a smaller portion of the fund is invested in firms that enjoy wide economic moats, or sustainable competitive advantages, than its peers, as illustrated in Exhibit 2. It even has slightly less exposure to wide moat stocks than the S&P 500 Index. Wide moats are a reasonable proxy for quality because companies that can keep their competitors at bay tend to generate relatively high and stable profits. This suggests the quality of the fund’s holdings may not be as strong as advertised.
A closer look at its benchmark’s performance is necessary to evaluate whether it has effectively captured a quality premium.