Michael Burry has shared plenty of investing insights since launching Substack in November, but he's not the only “big short” trader to have something to say about current market conditions.
Danny Moses, a former member of Steve Eisman's Frontpoint Partners, which made a successful bet on the housing market in 2008, spoke to Business Insider about the potential issues he sees developing in the AI market and how he thinks investors should navigate this rapidly evolving space.
As the AI boom unfolds, many financial experts are considering two key questions. Is there a bubble in the AI market, and if so, should we compare it to the dot-com era of the early 2000s?
Moses thinks the answer to both questions is “yes.” While he doesn't deny that AI trading is real and a long-term growth story, he also sees strong similarities between the two technology booms that suggest investors need to tread carefully.
“The growth was real, but the math wasn't working,” he said. “And I think we're getting to the point where the math just doesn't work.”
Moses emphasized that his views on potential problems in the AI market are not a call to short the industry. Rather, he said, it's a call to arms for investors to do their homework and find stocks that are a good fit to gain valuable exposure as the market continues to grow.
In his view, that means sticking with the most powerful companies in the technology space that have the resources to continue to scale and aren't bound by the same constraints as some smaller companies. Some of the best examples include Amazon, Google, Meta, and Microsoft.
“They can turn down capital spending at any time and still be cash flow positive, as opposed to other companies that rely on spending on AI,” he said.
However, Moses isn't bullish on all of Big Tech's top names. He cited Oracle as an example of problems in the AI market, noting that the company has high debt levels and needs large amounts of cash to fulfill orders from technology customers. He also highlighted volatile tech stocks Super Micro Computer and Coreweave as examples of risky strategies in AI trading.
But in his view, investors are finally starting to consider the fact that not all AI stocks are created equal, as the disparity between relative outperformers and underperformers becomes increasingly impossible to ignore.
“I think this is evidence that investors are starting to pick out the winners and losers in the industry. Investors would rather see Comfort and other businesses with stronger balance sheets that they can rely on to express the AI theme,” Moses added.
He also said he is bullish on uranium, as it is increasingly being touted as a key element in building the AI needed to sustain the industry in the coming years.
Still, he believes investors should pay close attention to the timeline for when it will start spurring growth, as it can sometimes be misunderstood amidst the AI hype.
“One of my favorite deals is uranium. Thematically it should work, but it will take a long time,” Moses said. “There is a mismatch between when people think companies will experience growth in AI and the timing of the infrastructure needed to actually power AI.”
