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Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps?
[ChatGPT peut-il calculer des scores de sentiment dignes de confiance à partir de Bloomberg Market Wraps ?]

Author

Listed:
  • Baptiste Lefort

    (MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec - Université Paris-Saclay, A.I. For Alpha)

  • Eric Benhamou

    (A.I. For Alpha, Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres)

  • Jean-Jacques Ohana

    (A.I. For Alpha)

  • David Saltiel

    (A.I. For Alpha)

  • Beatrice Guez

    (A.I. For Alpha)

  • D Challet

    (MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec - Université Paris-Saclay)

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.

Suggested Citation

  • Baptiste Lefort & Eric Benhamou & Jean-Jacques Ohana & David Saltiel & Beatrice Guez & D Challet, 2024. "Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps? [ChatGPT peut-il calculer des scores de sentiment dignes de confiance à partir de Bloomberg Market Wraps ?]," Working Papers hal-04739906, HAL.
    • Handle: RePEc:hal:wpaper:hal-04739906
    Note: View the original document on HAL open archive server: https://hal.science/hal-04739906v1
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    References listed on IDEAS

    as
    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 2024.
    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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    Cited by:

    1. Baptiste Lefort & Eric Benhamou & Jean-Jacques Ohana & David Saltiel & Beatrice Guez, 2024. "Optimizing Performance: How Compact Models Match or Exceed GPT's Classification Capabilities through Fine-Tuning," Papers 2409.11408, arXiv.org.

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