@inproceedings{rezende-etal-2026-enhancing,
    title = "Enhancing {B}razilian Inflation Forecasts through Sentiment Analysis Using Large Language Models",
    author = "Rezende, Lucas Miranda Mendon{\c{c}}a  and
      Junior, C{\'e}zio Luiz Ferreira  and
      Machado, Mateus Tarcinalli  and
      Ruiz, Evandro Eduardo Seron",
    editor = "Souza, Marlo  and
      de-Dios-Flores, Iria  and
      Santos, Diana  and
      Freitas, Larissa  and
      Souza, Jackson Wilke da Cruz  and
      Ribeiro, Eug{\'e}nio",
    booktitle = "Proceedings of the 17th International Conference on Computational Processing of {P}ortuguese ({PROPOR} 2026) - Vol. 1",
    month = apr,
    year = "2026",
    address = "Salvador, Brazil",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-dnd/2026.propor-1.17/",
    pages = "172--182",
    ISBN = "979-8-89176-387-6",
    abstract = "Reliable inflation forecasts play a critical role in economic stability and policy decisions. Traditional econometric models perform well but often overlook qualitative signals that could improve predictive accuracy. Recent advances in AI-based Natural Language Processing enable the extraction of latent sentiment, offering a promising avenue for inflation forecasting. This study proposes a framework that combines Large Language Models (LLMs) to extract sentiment variables from the Brazilian Monetary Policy Committee (COPOM) minutes, optimize bias to match human-collected sentiment, and integrate them into ARIMA and LSTM models for one-step-ahead monthly IPCA prediction. Results show that LLM-generated sentiment trends are temporally coherent with historical inflation patterns and highly statistically significant (p {\ensuremath{<}} 0.001). Models whose sentiment evaluations aligned more closely with human assessments (e.g., grok-4-fast and llama-4-maverick) achieved superior forecasting performance. ARIMA models consistently benefited from sentiment inclusion, while LSTM results were more variable."
}