Boffins foretell LLMs infiltrating finance and politics with confidently held views
If you want a picture of the future, imagine asking a large language model for a prediction.
Two sets of researchers did so recently and found that large language models (LLMs) like ChatGPT and BERT can enhance the accuracy of predictions about the stock market and public opinion, at least as measured against historical data.
In a paper titled, “Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models,” University of Florida professors Alejandro Lopez-Lira and Yuehua Tang evaluated how OpenAI’s ChatGPT fared when assessing the sentiment of news headlines.
Sentiment analysis – determining whether text like a news headline expresses positive, neutral, or negative sentiment about a subject or company – has become a widely evaluated parameter for quantitative analysis algorithms used by stock traders. It has been found to make market predictions more accurate.
The two University of Florida boffins looked at how ChatGPT performed when prompted to assess the sentiment expressed in news headlines. When they compared ChatGPT’s evaluation of those news stories to the subsequent performance of company shares in their sample, they found the model returned predictions that were statistically significant, which is more than can be said of other LLMs.
“Our analysis reveals that ChatGPT sentiment scores exhibit a statistically significant predictive power on daily stock market returns,” they state in their paper.
“By utilizing news headline data and the generated sentiment scores, we find a strong correlation between the ChatGPT evaluation and the subsequent daily returns of the stocks in our sample. This result highlights the potential of ChatGPT as a valuable tool for predicting stock market movements based on sentiment analysis.”
For example, they prompted ChatGPT thus:
In the paper, ChatGPT responded:
The researchers interpret this to mean that ChatGPT’s analysis assumes the fine could nudge up Oracle’s sales and stock price.
