ChatGPT may be able to predict stock movements, finance professor shows
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
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