“ChatGPT outperforms traditional sentiment analysis methods” to forecast stock prices | Forexlive

Here’s a link to an academic paper that examined:

The abstract reads:

We examine the potential of ChatGPT, and other large language models, in predicting stock market returns using sentiment analysis of news headlines.

We use ChatGPT to indicate whether a given headline is good, bad, or irrelevant news for firms’ stock prices. We then compute a numerical score and document a positive correlation between these “ChatGPT scores” and subsequent daily stock market returns.

Further, ChatGPT outperforms traditional sentiment analysis methods.

We find that more basic models such as GPT-1, GPT-2, and BERT cannot accurately forecast returns, indicating return predictability is an emerging capacity of complex models. Our results suggest that incorporating advanced language models into the investment decision-making process can yield more accurate predictions and enhance the performance of quantitative trading strategies.