Exchange-traded funds that borrow a page from quant funds' playbook.
A version of the following article appeared in Morningstar ETFInvestor, a monthly publication that offers our latest thinking on the ETF market, including two model ETF portfolios.
Actively managed exchange-traded funds--the so-called holy grail of the ETF industry--thus far remain elusive. Several roadblocks have kept them from getting off the ground, including significant regulatory hurdles that may take some time to surmount. While an active ETF may be months or years away, ETF providers are getting as close to active management as they can by constructing indexes that are shaped by quantitative models, which use many of the same criteria that active managers do. And like active managers, these ETFs aim to outperform conventional benchmarks.
A Little Background
Using quantitative models to pick stocks is nothing new. Quantitative strategies have been around for a while, and they've also grown in popularity among conventional fund investors. Many big firms, including Vanguard, Schwab, and American Century, include quantitative funds in their lineups. And a few fund shops, such as Bogle and Bridgeway, specialize exclusively in quantitative strategies. Conventional quantitative funds use computer models to screen and rank stocks based on a variety of investment metrics, including relative valuation, fundamental strength, and technical and momentum factors. ETFs that track enhanced indexes use similar techniques to construct their benchmarks.
PowerShares has the largest lineup of quasi-active ETFs. After the launch of a slate of sector funds last year, the Dynamic lineup now includes 36 funds. (More on the PowerShares Dynamic methodology follows.) Most of the Claymore stable of ETFs is dedicated to quantitative strategies; its lineup includes the likes of Claymore/Sabrient Insider
Pros and Cons
Like any investment process, quantitatively driven strategies have their strengths and weaknesses. On the plus side, the quantitative process enforces investment discipline--the computer models are consistent and repeatable. There also are some advantages to removing the "human element" from investing. Computer models don't get swept up in market mania or investing fads to which human managers might fall prey.
On the negative side, left to its own devices, a model will gradually lose effectiveness because, when a fund's approach is working, others will try to copy what it's doing, thereby eroding its advantage. Consequently, it's imperative for quant teams to continually evaluate and enhance their models. The best active quantitative managers are constantly testing their models and looking for ways to improve their effectiveness. It's not yet clear how much effort ETF providers are devoting to testing and enhancing the models behind these funds.
As another drawback, quant funds have above-average turnover rates, which could impair their tax efficiency. So far, no quasi-active ETF has distributed capital gains, but the oldest of these funds has only been around for three years. The ETF providers I've talked to are confident that the ETF in-kind creation and redemption process should be sufficient to absorb any capital gains, but I'm still cautious. These funds have seen a lot of trading. For example, PowerShares Dynamic Market
The Need for High Standards
Quant firms keep their computer models private because they understandably don't want to reveal their methods to the competition. Accordingly, anyone who analyzes quant funds operates in a vacuum to a certain extent. There's a point at which investing in quant funds comes down to an act of faith. That's why I think you need to have high standards when it comes to other factors like the management's experience, the analytical resources that support the model, the strategy's track record, and expenses.