Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps?

Baptiste Lefort, Eric Benhamou, Jean-Jacques Ohana, David Saltiel, Beatrice Guez +1 more
1/9/2024
q-fin.STcs.AI

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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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Cite this paper

@article{lefort2024chatgpt,
  title  = {Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps?},
  author = {Baptiste Lefort and Eric Benhamou and Jean-Jacques Ohana and David Saltiel and Beatrice Guez and Damien Challet},
  year   = {2024},
  eprint = {2401.05447},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.05447v1}
}

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