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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.”

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Nvidia’s Huang says programming AI is now like training a person

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Nvidia’s Huang says programming AI is now like training a person

Nvidia CEO Jensen Huang says artificial intelligence is the “great equalizer” because it lets anyone program using everyday language.

Speaking at London Tech Week on Monday, Huang said that, historically, computing was hard and not available to everyone. “We had to learn programming languages. We had to architect it. We had to design these computers that are very complicated,” he said on stage alongside U.K. Prime Minister Kier Starmer.

“Now, all of a sudden … there’s a new programming language. This new programming language is called ‘human.'”

Conversational AI models were thrown into the spotlight in 2022 when OpenAI‘s ChatGPT exploded onto the scene. In February, the San Francisco-based tech company said it had 400 million weekly active users.

Users can ask chatbots, such as ChatGPT, Google’s Gemini or Microsoft’s Copilot, questions and they respond in a conversational way that feels more like talking to another human than an AI system.

Jensen Huang, co-founder and chief executive officer of Nvidia, at the London Tech Week exposition in London, UK, on Monday, June 9, 2025.

Bloomberg | Bloomberg | Getty Images

CEO Huang, whose company engineers some of the world’s most advanced semiconductors and AI chips, highlighted that this technology can now be used in programming. He highlighted that very few people know how to use programming languages like C++ or Python, but “everybody … knows ‘human’.”

“The way you program a computer today, to ask the computer to do something for you, even write a program, generate images, write a poem — just ask it nicely,” he said. “And the thing that’s really, really quite amazing is the way you program an AI is like the way you program a person.”

He gave the example of simply asking a computer to write a poem to describe the keynote speech at the London Tech Week event.

“You say: You are an incredible poet … And I would like you to write a poem to describe today’s keynote. And without very much effort, this AI would help you generate such a wonderful poem,” he said.

“And when it answers … you could say: I feel like you could do even better. And it would go off and think about it, and it’ll come back and say, in fact, I I can do better, and it does do a better job.”

Jensen Huang, co-founder and CEO of Nvidia Corp., speaks during a news conference in Taipei on May 21, 2025.

Nvidia CEO says the UK is in a ‘Goldilocks’ moment: ‘I’m going to invest here’

Huang’s comments come as a growing number of companies — such as Shopify, Duolingo and Fiverr — encourage their employees to incorporate AI into their work. Indeed, last week OpenAI announced that it has 3 million paying business users.

Huang regularly touts AI’s ability to help workers do their jobs more efficiently and has encouraged workers to embrace the technology as they look to make themselves valuable employees — especially given the horror stories around AI’s potential to replace jobs. 

“This way of interacting with computers, I think, is something that almost anybody can do, and I would just encourage everybody to engage it,” Huang added on Monday. “Children are already doing that themselves naturally, and this is going to be transformative.

— CNBC’s Cheyenne DeVon and Ashton Jackson contributed to this report.

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Nvidia CEO says the UK is in a ‘Goldilocks’ moment: ‘I’m going to invest here’

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Nvidia CEO says the UK is in a 'Goldilocks' moment: 'I'm going to invest here'

Jensen Huang, co-founder and CEO of Nvidia Corp., speaks during a news conference in Taipei on May 21, 2025.

I-hwa Cheng | Afp | Getty Images

LONDON — Nvidia CEO Jensen Huang poured praise on the U.K. on Monday, promising to boost investment in the country’s artificial intelligence sector with his multitrillion-dollar semiconductor company.

“The U.K. is in a Goldilocks circumstance,” Huang said, speaking on a panel with British Prime Minister Keir Starmer and Investment Minister Poppy Gustafsson. “You can’t do machine learning without a machine — and so the ability to build these AI supercomputers here in the U.K. will naturally attract more startups.”

The Nvidia boss went on to say, “I think it’s just such an incredible, incredible place to invest. I’m going to invest here.”

Huang also stressed that Britain “has one of the richest AI communities anywhere on the planet,” along with “amazing startups” such as DeepMind, Wayve, and Synthesia, ElevenLabs.

“The ecosystem is really perfect for take-off — it’s just missing one thing,” he said, referring to a lack of homegrown, sovereign U.K. AI infrastructure.

Earlier on Monday, Nvidia announced a new U.K. sovereign AI industry forum, as well as commitments from cloud vendors Nscale and Nebius to deploy new facilities in the country with thousands of the semiconductor giant’s Blackwell GPU chips.

The U.K. has been touting its potential as a global AI player in recent months, amid Keir Starmer’s efforts to lead his Labour government with a growth-focused agenda.

In January, Starmer unveiled a bold plan to boost the domestic U.K. AI sector, promising to relax planning rules around new data center developments and increase British computing power by twenty-fold by 2030.

This is a breaking news story. Please check back for updates.

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UK finance watchdog teams up with Nvidia to let banks experiment with AI

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UK finance watchdog teams up with Nvidia to let banks experiment with AI

Jakub Porzycki | Nurphoto | Getty Images

LONDON — Britain’s financial services watchdog on Monday announced a new tie-up with U.S. chipmaker Nvidia to let banks safely experiment with artificial intelligence.

The Financial Conduct Authority said it will launch a so-called Supercharged Sandbox that will “give firms access to better data, technical expertise and regulatory support to speed up innovation.”

Starting from October, financial services institutions in the U.K. will be allowed to experiment with AI using Nvidia’s accelerated computing and AI Enterprise Software products, the watchdog said in a press release.

The initiative is designed for firms in the “discovery and experiment phase” with AI, the FCA noted, adding that a separate live testing service exists for firms further along in AI development.

“This collaboration will help those that want to test AI ideas but who lack the capabilities to do so,” Jessica Rusu, the FCA’s chief data, intelligence and information officer, said in a statement. “We’ll help firms harness AI to benefit our markets and consumers, while supporting economic growth.”

The FCA’s new sandbox addresses a key issue for banks, which have faced challenges shipping advanced new AI tools to their customers amid concerns over risks around privacy and fraud.

Large language models from the likes of OpenAI and Google send data back to overseas facilities — and privacy regulators have raised the alarm over how this information is stored and processed. There have meanwhile been several instances of malicious actors using generative AI to scam people.

Nvidia is behind the graphics processing units, or GPUs, used to train and run powerful AI models. The company’s CEO, Jensen Huang, is expected to give a keynote talk at a tech conference in London on Monday morning.

Last year, HSBC’s generative AI lead, Edward Achtner, told a London tech conference he sees “a lot of success theater” in finance when it comes to artificial intelligence — hinting that some financial services firms are touting advances in AI without tangible product innovations to show for it.

He added that, while banks like HSBC have used AI for many years, new generative AI tools like OpenAI’s ChatGPT come with their own unique compliance risks.

Zopa CEO: Fintechs face challenges when it comes to scaling in the UK

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