Peter Hafez, Chief Data Scientist at RavenPack, looks back on a year of rich research insights and charts the course for 2024.

Promising results in the realm of stock price predictions using LLMs have been showcased in the now-famous paper Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models" . This paper, released earlier this year, has garnered significant attention, becoming one of the Top 40 most downloaded papers of all time on SSRN with over 56,000 downloads. While the paper demonstrates encouraging results in predicting future stock returns, caution is warranted in drawing strong conclusions.

Internal research within RavenPack suggests that the outcomes can be sensitive not only to the version of the GPT model they used but also to the strategy implementation. The robust performance depicted in the paper relies heavily on the assumption of attaining the open-price, a scenario proven impractical in real-world contexts. Even with an alternative 15-minute VWAP implementation, the value diminishes.

In the figure below, we illustrate the impact of the expanded VWAP on the open-strategy performance applying the same prompt as in the paper , revealing a distinct deterioration evident even with a shift to a 15-minute VWAP. The results also highlight variations in the open-price implementation between the March and June GPT 3.5 Turbo versions. Due to the black-box nature of the models, explaining the shift in performance becomes impractical. Nonetheless, we presume the utilization of the March version in the paper.

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It’s important to note that this analysis doesn't diminish the potential value of LLMs in systematic investing . While achieving Sharpe Ratios above 3 may pose challenges, the RavenPack Data Science team remains optimistic about the applications of LLMs in finance based on internal research and we anticipate sharing more of our findings on this topic throughout 2024.

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Please use your business email. If you don't have one, please email us at info@ravenpack.com .

By providing your personal information and submitting your details, you acknowledge that you have read, understood, and agreed to our Privacy Statement and you accept our Terms and Conditions . We value your privacy and assure you that we will handle your personal information with the utmost care and in compliance with our Privacy Statement. You can exercise your rights of access, rectification, erasure, restriction of processing, data portability, and objection by emailing us at privacy@ravenpack.com in accordance with the General Data Protection Rules (GDPR). You also are agreeing to receive occasional updates and communications from RavenPack about resources, events, products, or services that may be of interest to you.