@inproceedings{paris-etal-2025-financial,
    title = "Financial News as a Proxy of {E}uropean Central Bank Interest Rate Adjustments",
    author = "Paris, Davide  and
      Menzio, Martina  and
      Fersini, Elisabetta",
    editor = "Angelova, Galia  and
      Kunilovskaya, Maria  and
      Escribe, Marie  and
      Mitkov, Ruslan",
    booktitle = "Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era",
    month = sep,
    year = "2025",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd., Shoumen, Bulgaria",
    url = "https://preview.aclanthology.org/corrections-2026-01/2025.ranlp-1.104/",
    pages = "907--914",
    abstract = "This paper examines the relationship between news coverage and the European Central Bank{'}s (ECB) interest rate decisions. In particular, the hypothesis of a linear relationship between financial news and ECB indications regarding interest rate variations is investigated by leveraging state-of-the-art large language models combined with domain experts and automatically selected keywords. The analysis revealed two key findings related to how news contents can signal the ECB{'}s decisions to raise or lower interest rates: (1) Sentence Transformer models, when combined with domain-specific keywords, exhibit a higher correlation with ECB decisions than state-of-the-art financial BERT architectures; (2) employing a grid search strategy to select subsets of informative keywords strengthened the relationships between news contents and ECB{'}s decisions, highlighting how media narratives can anticipate or reflect central bank policy actions."
}