Over the past few months, ETFs focused on innovative technologies have been all the rage, headlined by the meteoric rise of Ark Investment’s active ETFs managed by Cathie Wood.
But a recently launched, more passive-oriented Direxion ETF has recently outperformed Ark’s $22 bilion flagship Ark Innovation ETF (ARKK). The $178 million Direxion Moonshot Innovators ETF (MOON) has offered a 29.12% return year-to-date as of this morning, compared to the 0.50% return of ARKK, according to ETF Database.
“Our greatest differentiator is that we have a pure focus on early-stage innovation, in micro- , small- and some mid-caps,” said Dave Mazza, head of product at Direxion. “What we’re doing is a combined quantitative and qualitative process to arrive at just 50 stocks that display the most innovative qualities.”
ETF Database says that over the past 13 weeks, MOON as offered 43.84% in returns to ARKK’s 13.15%. What’s more, MOON is doing so with a 0.65% expense ratio compared to ARKK’s 0.75% annual cost. Since Nov. 12 inception, MOON offered an over 70% return on its net asset value as of Feb. 28.
Purely passive methods wouldn’t work to identify small, innovative companies that have an opportunity to grow into the next big technology stocks, said Mazza, because they couldn’t be targeted enough.
“Innovation is a buzzword. It’s’ being used all over the place and not just for ETFs,” he said. “When we think about investing in innovation, we think it’s about divining the early stage innovators.”
MOON tracks the S&P Kensho Moonshot Index, which purports to offer exposure to the 50 “most innovative” companies in the U.S., excluding large- and mega-cap companies like the FAANG stocks.
It scores small- and mid-cap U.S. companies along two criteria: allocation to innovation and innovation sentiment.
Allocation to innovation is measured by ranking companies based on the ratio of their research and development expenses to their revenue compared to peer companies in the same industry.
Innovation sentiment is scored by an AI algorithm that uses natural language processing to pore through a company’s recent regulatory filings for language related to innovation, using a variety of terms.
“Using sentiment on its own would not be a good thing. You could end up with a universe of securities that are focused on innovation and talk the talk but aren’t doing anything,” said Mazza. “It’s the combination of allocation and sentiment that makes this method powerful. My background is in quantitative portfolio management, and I feel like there’s a lot of potential for systematic, rules-based approaches in this space to remove behavioral biases in this space.”