Smart beta ETFs are generally geared for outperformance. They invest in pools of securities with a rules-based methodology that can be hard to beat. But as an ETF investor, it can be difficult to objectively evaluate smart beta ETFs with so many available in the marketplace and relatively small sample sizes used to compare live performance.

The idea behind modeling factors is that it can avoid some of these challenges by decomposing an ETF’s holdings based on common risks likely driving returns. However, the challenge for most investors is that they either a) don’t have access to cost-effective tools that provide them this type of portfolio lens and b) the output of such an analysis is not as intuitive as comparing excess returns versus a benchmark. Assuming an investor can get over these hurdles, the question is simple: Should a smart beta ETF behave the way the label suggests it will?

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