Robos Haven’t Failed – They Get an "A" for Being Average

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A recent article in Advisor Perspectives, using data from Backend Benchmarking (BEB), noted that robos had significantly underperformed and suggested that they had “failed” investors. The conclusion is not robust, though, because the findings are based entirely on performance comparisons against BEB’s benchmarks and no alternative tests were conducted or considered. Unlike traditional indexes that tend to be relatively similar (e.g., for large cap equities), there is significantly more ambiguity when creating (and implementing) any multi-asset benchmarking strategy (e.g., for a 60/40 portfolio)1 and using only BEB’s approach could have biased the findings.

An alternative way to assess robo performance would be to see how they fared against other portfolios with similar risk levels, such as balanced mutual funds and models (i.e., their peers). If robos collectively underperformed their peers, the initial “failure” conclusion would hold additional weight; if not, it should be revisited.

After completing such an analysis, I find no economically or statistically significant difference in performance, which suggests the “failure” diagnosis is premature. My findings were consistent with my expectations, though, since it is questionable that any group of investments (or strategies) should systematically underperform (or outperform) on risk-adjusted basis.

It’s too early to know how robos are going to impact investors, especially versus alternatives (i.e., do-it-yourself-or financial advisor-constructed portfolios); however, from a performance perspective, I give robos an “A” for being average, so far, and hope that future research can make more meaningful statements as to how robos truly impact investor outcomes.

Robo portfolios

Robo portfolios are usually pretty boring. Boring is typically a good thing when it comes to investing, though, since boring strategies tend to do pretty well over time. Robos tend to invest in ETFs and are unlikely to be alpha-generating machines, at least among some of the more established/larger players. While it’s possible the style tilts and timing choices of the robos might help performance, the alpha expectation should be pretty close to zero before fees, especially across a wide number of providers (it is unlikely everyone is going to time the market correctly), and negative after fees.