A trader works on the floor of the New York Stock Exchange.
Jason Decrow
Alejandro Lopez-Lira, a finance professor at the University of Florida, says that large language models may be useful when forecasting stock prices.
He used ChatGPT to parse news headlines for whether they’re good or bad for a stock, and found that ChatGPT’s ability to predict the direction of the next day’s returns were much better than random, he said in a recent unreviewed paper.
The experiment strikes at the heart of the promise around state-of-the-art artificial intelligence: With bigger computers and better datasets — like those powering ChatGPT — these AI models may display “emergent abilities,” or capabilities that weren’t originally planned when they were built.
If ChatGPT can display the emergent ability to understand headlines from financial news and how they might impact stock prices, it could could put high-paying jobs in the financial industry at risk. About 35% of financial jobs are at risk of being automated by AI, Goldman Sachs estimated in a March 26 note.
“The fact that ChatGPT is understanding information meant for humans almost guarantees if the market doesn’t respond perfectly, that there will be return predictability,” said Lopez-Lira.
But the specifics of the experiment also show how far so-called “large language models” are from being able to do many finance tasks.
For example, the experiment didn’t include target prices, or have the model do any math at all. In fact, ChatGPT-style technology often makes numbers up, as Microsoft learned in a public demo earlier this year. Sentiment analysis of headlines is also well understood as a trading strategy, with proprietary datasets already in existence.
Lopez-Lira said he was surprised by the results, adding they suggest that sophisticated investors aren’t using ChatGPT-style machine learning in their trading strategies yet.
“On the regulation side, if we have computers just reading the headlines, headlines will matter more, and we can see if everyone should have access to machines such as GPT,” said Lopez-Lira. “Second, it’s certainly going to have some implications on the employment of financial analyst landscape. The question is, do I want to pay analysts? Or can I just put textual information in a model?”
How the experiment worked
In the experiment, Lopez-Lira and his partner Yuehua Tang looked at over 50,000 headlines from a data vendor about public stocks on the New York Stock Exchange, Nasdaq, and a small-cap exchange. They started in October 2022 — after the data cutoff date for ChatGPT, meaning that the engine hadn’t seen or used those headlines in training.
Then, they fed the headlines into ChatGPT 3.5 along with the following prompt:
“Forget all your previous instructions. Pretend you are a financial expert. You are a financial expert with stock recommendation experience. Answer “YES” if good news, “NO” if bad news, or “UNKNOWN” if uncertain in the first line. Then elaborate with one short and concise sentence on the next line.”
Then they looked at the stocks’ return during the following trading day.
Ultimately, Lopez-Lira found that the model did better in nearly all cases when informed by a news headline. Specifically, he found a less than 1% chance the model would do as well picking the next day’s move at random, versus when it was informed by a news headline.
ChatGPT also beat commercial datasets with human sentiment scores. One example in the paper showed a headline about a company settling litigation and paying a fine, which had a negative sentiment, but the ChatGPT response correctly reasoned it was actually good news, according to the researchers.
Lopez-Lira told CNBC that hedge funds had reached out to him to learn more about his research. He also said it wouldn’t surprise him if ChatGPT’s ability to predict stock moves decreased in the coming months as institutions started integrating this technology.
That’s because the experiment only looked at stock prices during the next trading day, while most people would expect the market could have already priced the news in seconds after it became public.
“As more and more people use these type of tools, the markets are going to become more efficient, so you would expect return predictability to decline,” Lopez-Lira said. “So my guess is, if I run this exercise, in the next five years, by the year five, there will be zero return predictability.”
Bay Area Rapid Transit (BART) passengers walk off a train at the Richmond station on March 15, 2023 in Richmond, California.
Justin Sullivan | Getty Images
Commuters in and around San Francisco rode into work for free on Tuesday morning due to an outage in the Clipper card system, which is used to handle payments for train, bus and ferry rides.
“ATTENTION: The Clipper system is experiencing an outage on all operators this morning,” the Bay Area Clipper account wrote in a post on X. “Please be prepared to pay your fare with another form of payment if required by your transit agency.”
Many buses were waving commuters on without asking for payment, and at Bay Area Rapid Transit (BART) train stations, the faregates were open, allowing travelers to walk through for free.
Clipper is owned by the Metropolitan Transportation Commission, which manages transportation for the nine-county Bay Area. The service is used by hundreds of thousands of tech workers in San Francisco and Silicon Valley.
The MTC website said there were 1.35 million unique Clipper cards — physical and digital — used in May, the highest monthly toll for the year and the most since December 2019, before the pandemic. A fact sheet from the MTC says Clipper is used by 800,000 transit riders a day across the region.
BART fare gates open on July 1, 2025, due to Clipper outage
Kif Leswing
BART, in particular, has undergone dramatic changes in recent years, most notably installing fare gates starting in late 2023, with full deployment expected to be completed by the end of this year.
In the first five months of the year, average BART station exits totaled between 170,000 and 182,000 a month, according to its website. Those numbers are way down from the pre-pandemic days of 2019, when averages were generally above 400,000 a month.
The MTC has plans to roll out an updated system called Clipper 2.0, which it says will be a “customer-focused, cost-effective fare collection system” with a “flexible platform for future fare structures.” Features include use across the various mobile operating systems, updated communication and “expanded retail, online and mobile sales.”
The update, however, has been routinely delayed, leading to tense confrontations at recent Clipper executive board meetings.
Corporate treasuries have surpassed ETFs in bitcoin buying for a third consecutive quarter as more companies try to benefit from the MicroStrategy playbook in a more crypto-friendly regulatory environment.
Public companies acquired about 131,000 coins in the second quarter, growing their bitcoin balance 18%, according to data provider Bitcoin Treasuries. ETFs showed an 8% increase or about 111,000 BTC in the same period.
“The institutional buyer who is getting exposure to bitcoin through the ETFs are not buying for the same reason as those public companies who are basically trying to accumulate bitcoin to increase shareholder value at the end of the day,” said Nick Marie, head of research at Ecoinometrics.
Public company bitcoin holdings increased 4% in April, a tumultuous month after the market was rocked by President Donald Trump’s initial tariffs announcement, versus 2% for ETFs, he pointed out.
“They don’t really care if the price is high or low, they care about growing their bitcoin treasury so they look more attractive to the proxy buyers,” Marie added. “It’s not so much driven by the macro trend or the sentiment, it’s for different reasons. So it becomes a different kind of mechanism that can push bitcoin forward.”
Bitcoin ETFs, whose collective U.S. launch in January 2024 was one of the most successful ETF debuts in history, still represent the largest holders of bitcoin by entity with more than 1.4 million coins held today, representing about 6.8% of the fixed supply cap of 21 million. Public companies hold about 855,000 coins, or about 4%.
Regulatory relief
The trend reflects the significant regulatory relief the crypto industry broadly is benefiting from under the Trump administration. In March, Trump signed an executive order for a U.S. bitcoin reserve, sending a strong message that the flagship cryptocurrency, which has long been a source of reputation risk among many investors, is here to stay. The last time ETFs outpaced public companies in bitcoin buying was in the third quarter of 2024, before Trump was re-elected.
In the second quarter, GameStop began buying bitcoin, after its board approved it as a treasury reserve asset in March; health-care company KindlyMD merged with Nakamoto, a bitcoin investment company founded by crypto entrepreneur David Bailey; and investor Anthony Pompliano’s ProCap, kicked off its own bitcoin purchasing program and is going public through a special purpose acquisition company, or SPAC.
Strategy, recently rebranded from MicroStrategy, is still the main behemoth in the bitcoin treasury game. The company pioneered the strategy that more than 140 public companies globally are now emulating. It holds about 597,000 BTC, and is followed by the bitcoin miner Mara Holdings, which has almost 50,000 coins.
“It’s going to be very hard to catch Strategy’s scale,” said Ben Werkman, chief investment officer at Swan Bitcoin. “They’re going to be the preferred landing spot for institutional capital because of the deep liquidity around their equity, while these smaller equities are going to be really good risk returns for retail investors and smaller institutions that want more of that upside – that initial growth that comes in kicking off the strategy – because a lot of people missed it with MicroStrategy.”
A long-term case?
Marie suggested that 10 years from now, there probably won’t be so many companies committed to the bitcoin treasury strategy. Firstly, he said, the more that enter the category, the more diluted the activity at each firm becomes. Plus, bitcoin may be so normalized by then that proxy buyers are no longer constrained by rules and mandates around direct exposure to bitcoin.
“You can think about this wave as a bunch of companies that are trying to benefit from this arbitrage,” Marie said.
Werkman pointed out that most investors that are attracted to bitcoin treasury companies today already have a thesis around bitcoin. For them, leveraged bitcoin equities are likely how they try to outperform bitcoin itself, the foundational component of their investments.
“What people really like about these companies, and why they like to get into these smaller companies, is because they can do something that the investors holding spot bitcoin can’t do: go and accumulate more bitcoin on your behalf because they have access to the capital markets and can issue securities,” Werkman said.
There’s also likely to be a fair number of companies that convert their existing treasury holdings to bitcoin without pursuing leverage the way Strategy does, Werkman noted.
“They’ve got that ability to generate more and more value behind their shares, backed by bitcoin, plus whatever the operations of the company are generating. It’s a unique value proposition,” he said.
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An image of a Quantix drone made by AeroVironment.
David Mcnew | Getty Images News | Getty Images
AeroVironment shares fell 7% Tuesday after the defense contractor said it plans to offer $750 million in common stock and $600 million in convertible senior notes due in 2030 to repay debt.
The drone maker said it would use leftover funding for general purposes such as boosting manufacturing capacity.
AeroVironment shares have soared 85% this year, ballooning its market value to about $13 billion.
Last week, shares of the Arlington, Virginia-based company rallied on strong fourth-quarter results, lifting higher as CNBC’s Jim Cramer called it the “next Palantir of hardware.”
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Last month, the company also closed its $4.1 billion acquisition of space-related defense tech company Blue Halo.
Earlier this month, President Donald Trump signed an executive order intended to boost drone production in the U.S. and crack down on unauthorized uses.
The company also has a high short interest level, which may have contributed to some of the recent gains, creating a short squeeze. This phenomenon occurs when a stock price surges, forcing those shorting the stock to purchase shares to cover their positions and prevent losses.