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Finance-specific large language models: Advancing sentiment analysis and return prediction with LLaMA 2

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  • Chiu, I-Chan
  • Hung, Mao-Wei

Abstract

In this study, we develop an AI-driven summarization process for lengthy financial texts to improve our self-trained, finance-specific LLaMA-2 model. This approach allows for precise sentiment analysis, leading to more accurate return predictions on disclosures in the Management Discussion and Analysis sections of 10-K filings. Empirical results indicate that trading strategies based on LLaMA-2 sentiments produce significantly higher buy-and-hold returns (BHRs) compared to those derived from FinBERT (Huang et al., 2023) and traditional models. Furthermore, LLaMA-2 sentiment signals show a strong correlation with cumulative abnormal returns (CARs) and surpass traditional methods in predictive accuracy. The summarization process also enhances traditional models, generating significantly higher BHRs with summarized texts than with full texts. Both BHR and CAR results in our approach show robustness during periods of financial turbulence. These findings underscore the value of generative AI in finance and set a new standard for textual analysis.

Suggested Citation

  • Chiu, I-Chan & Hung, Mao-Wei, 2025. "Finance-specific large language models: Advancing sentiment analysis and return prediction with LLaMA 2," Pacific-Basin Finance Journal, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:pacfin:v:90:y:2025:i:c:s0927538x24003846
    DOI: 10.1016/j.pacfin.2024.102632
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    References listed on IDEAS

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    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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