How DeepSeek Shakes Up Traditional Tech ETF Strategy
China's DeepSeek breakthrough challenges big tech dominance, prompting ETF managers to highlight equal-weight and dynamic strategies for the evolving AI landscape.
DeepSeek's development of an advanced AI model for just $6 million has exposed vulnerabilities in traditional tech-heavy exchange-traded funds, highlighting concentration risks that alternative strategies may help address.
The Chinese startup's ability to match leading AI capabilities at a fraction of U.S. tech giants' costs has revealed how marketcap-weighted indexes have grown increasingly dependent on a handful of tech leaders, pushing investors to reassess how they manage sector exposure and volatility.
"We have historically high concentration, especially among the [Magnificent Seven] names," Nick Kalivas, head of factor and equity ETF strategy at Invesco, told etf.com. "The top 10 names at the end of last year were almost 39% of the S&P 500."
This concentration has made traditional ETFs more vulnerable to AI-driven disruption. "The overlap between the Nasdaq 100 and the S&P 500 has been approaching the 50% area. If you roll back 10-11 years ago, that number was closer to 20%," Kalivas explained.
Alternative ETF Strategies Face AI Challenge
The market response to DeepSeek underscores how quickly tech sector assumptions can shift.
"When you begin realizing you get a shift from innovation to efficiency and utilization, that throws the brakes on pretty quick," Ben Fulton, CEO of WEBs Investments, told etf.com, describing the market's reaction as a "level setting" after an overly frothy period.
Equal-weight funds like Invesco's S&P 500 Equal Weight ETF (RSP) offer one approach to managing these risks. By balancing exposure across the S&P 500, these strategies reduce vulnerability to tech-specific shocks. "You're going to be less subject to the ups and downs that you see in these tech names," Kalivas said.
Dynamic strategies like the WEBs Defined Volatility QQQ ETF (DVQQ) and the WEBs Defined Volatility SPY ETF (DVSP) provide another option, Fulton said. These funds adjust exposure based on volatility signals.
"Our whole model was built with the idea that during low-risk types of markets, we lean into the market," Fulton said. "When uncertainty gets introduced, the model leans out and actually reduces exposure.”
The implications extend beyond immediate market reactions. Microsoft Inc.'s recent comments about slowing capital spending suggest a broader shift in AI investment assumptions. "I think you're going to see more and more focus on what the CapEx spend is," Kalivas noted.
"The best days for AI's pricing in the stock market are behind us," Fulton said. "If it's really worth something, there's going to be duplication and copying. Now it becomes incorporated across and makes all industries more efficient."
This evolving landscape presents challenges for traditional market-cap-weighted approaches. "We're kind of in uncharted territory," Kalivas added. "It's hard to really know how the whole AI trend plays out in terms of winners and losers."