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Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps?

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  • Baptiste Lefort
  • Eric Benhamou
  • Jean-Jacques Ohana
  • David Saltiel
  • Beatrice Guez
  • Damien Challet

Abstract

We used a dataset of daily Bloomberg Financial Market Summaries from 2010 to 2023, reposted on large financial media, to determine how global news headlines may affect stock market movements using ChatGPT and a two-stage prompt approach. We document a statistically significant positive correlation between the sentiment score and future equity market returns over short to medium term, which reverts to a negative correlation over longer horizons. Validation of this correlation pattern across multiple equity markets indicates its robustness across equity regions and resilience to non-linearity, evidenced by comparison of Pearson and Spearman correlations. Finally, we provide an estimate of the optimal horizon that strikes a balance between reactivity to new information and correlation.

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  • Baptiste Lefort & Eric Benhamou & Jean-Jacques Ohana & David Saltiel & Beatrice Guez & Damien Challet, 2024. "Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps?," Papers 2401.05447, arXiv.org.
    • Handle: RePEc:arx:papers:2401.05447
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    References listed on IDEAS

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    1. Alejandro Lopez-Lira & Yuehua Tang, 2023. "Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models," Papers 2304.07619, arXiv.org, revised Sep 2023.
    2. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
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