In the opinion of Alejandro Lopez-Lira, a finance professor at the University of Florida, huge language models could be effective for forecasting stock values.
He utilized ChatGPT to interpret news headlines to determine if they were positive or negative for a stock, and discovered that ChatGPT’s ability to forecast the direction of the next day’s returns was substantially better than random, he said in a recent unreviewed work.
The experiment gets to the heart of the promise of cutting-edge artificial intelligence: These AI models may exhibit “emergent abilities,” or capabilities that were not originally envisaged when they were constructed, with larger computers and better datasets, such as those powering ChatGPT.
If ChatGPT demonstrates an emerging capacity to interpret headlines from financial news and how they may affect stock prices, it may jeopardize high-paying positions in the finance industry. Goldman Sachs forecast in a March 26 paper that AI could automate 35% of finance jobs.
“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.
However, the experiment’s specifics demonstrate how distant “large language models” are from being capable of doing many banking jobs. The experiment, for example, did not include t
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