Envestnet has long had an ETF ranking system that analyzes passive ETFs and offers advisors guidance on which ones they see as best in class. The firm has now expanded that evaluation process to the smart-beta ETF space, boiling down a universe of about 800 ETFs into an initial list of 33 recommended funds from 10 different issuers. (The issuers included in the list are Alps, FlexShares, First Trust, iShares, PowerShares, Schwab, State Street, VanEck, Vanguard and WisdomTree.)
That list of funds—not disclosed to the public—reaches 50,000-plus advisors that use Envestnet’s platform or that have access to the firm’s research. According to Envestnet’s co-founder and Chief Investment Officer Brandon Thomas, the impetus of this new effort is to digest a quickly growing number of smart-beta ETFs, and to help advisors navigate this “very complex” and “still evolving” area of the ETF market.
ETF.com: There are some 800 smart-beta ETFs on the market today. They’re hugely diverse. How do you go about evaluating these funds?
Brandon Thomas: We want to identify products that have good characteristics in three areas. First, we want to make sure they’re low cost. Second, we want to make sure the ETFs are liquid. And third, we want to make sure the performance of the ETF is line with what we’d expect. And here’s where we diverge a little bit from our traditional ETF ranking. In our traditional ETF ranking process, we look primarily at tracking error for performance.
But with strategic beta, it’s tracking error plus two additional components: we measure risk-adjusted return— or the alpha of the ETF—to see if the ETF is generating excess return; and we measure the factor exposure.
Our performance dimension includes tracking error, alpha and exposure to the risk factor, such momentum or quality.
From a product screening perspective, we need to screen out products, and for that we use several screens:
- We look at the legal structure of the ETFs. Is it an open-end investment company? Is it an uncollateralized debt obligation? Is it a limited partnership? ETNs are then excluded from the mix.
- We screen out actively managed ETFs.
- We require 24 months of data history to conduct our regressions, so ETFs that don’t have that data history, or are missing one month in a 24-month period, are screened out.
- We screen out ETFs with less than $100 million in assets under management (AUM).
- We look for at least four products in a given peer group to evaluate that peer group.
ETF.com: So you need at least four competing ETFs—say, four momentum ETFs—to recommend one fund to advisors?
Thomas: That’s right.