Hedge funds eye AI bots to track hundreds of stocks

In just three to five years, hedge funds could have fleets of artificial intelligence bots helping them research and trade hundreds of stocks, according to hedge fund founder Divya Nettimi.

This could take the form of an AI agent that monitors data around a given stock and relays back to traders what it thinks is relevant and what is just noise, said Nettimi, whose Avala Global hedge fund manages $2 billion.

“I could see a world where an analyst who previously covered 20 stocks could cover 200, because they are maybe managing a fleet of agents that look at all these stocks and track them,” Nettimi said.

These would help a fund tackle a far greater number of “top of funnel ideas” and more accurately pick the best 15 to 20 ideas for stocks to hold in a given year, Nettimi said in a panel discussion at the Bloomberg Invest conference in New York Tuesday.

The productivity increase “is not going to be marginal; I think it’s going to be an order of magnitude,” Nettimi said. “It’s not just that people will be a little bit more efficient in what they do; I think there’s going to be entirely new workflows that come of this.”

The comments come as hedge funds, along with many other industries, grapple with how to keep up with the rapid pace of AI technological advancements and sort through ways to integrate it into their business processes.

Nettimi’s Avala has developed its own firm-wide AI model, which it uses as a core input, Bloomberg previously reported. Her previous employer, Viking Global Investors, has its own VikingGPT chatbot to help traders bat around trade ideas. 

Lone Pine Capital’s co-chief investment officer, Kelly Granat, said at the conference that AI technology will elevate investing judgment, because it can “commoditise the base layer of what we do.”

Long-short equity hedge fund Lone Pine, which manages $19.5 billion, said it’s “very easy to get siloed” as an analyst in the sectors they cover, Granat said. She thinks that having a standardised tool set enabled by AI “will be super helpful in people being able to pick up someone else’s work and say, ‘I totally get this because it’s in the same vocabulary that I do with myself’,” she added.

Still, neither thinks the machines will take over anytime soon.

“Reading a management team the right way, knowing what questions to ask, how you put the mosaic together, all of your quantitative and qualitative data points, the investment judgment and the pattern recognition you’ve gained from decades of experience” still matter, Nettimi said. “And I think that’s all harder to replace.”

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