Given the name, investors considering the Goldman Sachs New Age Consumer ETF (GBUY) can be forgiven for wondering if their investment comes with cleansing crystals and a Tarot deck (It doesn’t). GBUY tracks a bespoke index that seeks exposure to some familiar segments of the market — like e-commerce, social media, health and wellness, and online games, music and video — as well as a few less familiar concepts like “evolution of education” and “experiences over goods.” Goldman’s own marketing materials describe the investment thesis this way: “We believe that people are best suited to forecast change that is radically different from the past.”
The clearest explanation from Goldman is that GBUY provides “exposure to the beneficiaries of technological innovation, regardless of sector, geography or market capitalization.” The contents of its portfolio provide a bit more clarity, and top holdings include familiar names like Facebook, Amazon, Tencent, Alibaba and Netflix. Investments are selected and weighted “by a function of ‘thematic’ beta.’” GBUY’s management fee isn’t outrageous, but it’s high for the world of indexing, especially when many of the top holdings can be found in other ultra-low-cost vanilla index bunds. This may be why GBUY has been slow to gain assets.
If some of GBUY’s marketing lingo doesn’t sound like the Goldman Sachs you think you know, there’s a good reason. GBUY is one of five ETFs that Goldman launched in 2019 with indexes designed by Motif Investing Inc. The indexes selected stocks using artificial intelligence and machine learning. Goldman worked with Motif to design indexes that aim to identify companies that fit with broad themes that Goldman’s money managers thought would drive growth. (The “Motif” moniker was removed from the fund name in May 2020 when Motif dropped out as the index provider.) The funds were yet another example of Wall Street’s increased use of sophisticated automation. Computers read faster than human analysts, quickly scouring regulatory filings, company reports and news stories for information on a company’s prospects. Using AI and machine learning isn’t that much of a divergence — after all, most factor funds and smart-beta ETFs are really just attempts to codify investing strategies employed by human stock pickers. Whether it’s a plain-vanilla index or something more sophisticated, index methodology is basically just programmed code that tells the index what to buy and sell.