After our inaugural article on a new way to look at ETFs, “Introducing Smart Beta Ranking – A More Intuitive Roadmap for Value Investing,” we decided to apply this same framework to U.S. Large Cap ETFs .
Our new Smart Beta Rankings offer a transparent and simple way to start investing in ETFs. Up until now, there hasn’t been a clear and systematic methodology investors could use when comparing different types of ETFs. While investors are currently forced to blindly pick and choose ETFs, without knowledge of how they’re constructed or how they compare to each other, Q.ai’s new Smart Beta Scores is changing the game.
With Smart Beta Scores, investors don’t have to focus on assets under management (AUM$), expense ratios or fund flows — none of which explain ETF performances. We think it makes sense to focus on what really matters: the “betas” that are really driving the performances of the ETFs.
Using the same methods we already use to measure mutual funds and other traditional investment funds, we measure ETFs. We’ve created a unique portfolio attribution system based on our AI factor models to unpack the risk measures behind ETFs’ performances. These measures include small-cap stocks exposure, interest rate exposure, exposure to oil, etc. From there, we measure whether an ETF is overweight, neutral, or underweight in our factor groups. And, based on exposures to particular factor groups, we rank them in various categories.
With Smart Beta Scores, investors can have transparency and trust in the ETFs in which they invest.
Our top-rank U.S. Large Cap ETFs is First Trust Large Cap (FEX)
The worst-ranked U.S. Large Cap ETF is Morningstar U.S. Large Cap (JKD)
Our Smart Beta ETF Rankings are updated every two weeks on Forbes AI Investor.