Evaluating Financial Sentiment in the Age of AI
Financial sentiment measures are widely used in empirical finance, but it remains unclear whether general-purpose large language models (LLMs) improve on existing finance-specific methods. This paper evaluates twelve sentiment models, including dictionary-based methods, finance-specific transformers, and open-source LLMs, using two criteria: linguistic validity and economic validity. We find that general-purpose LLMs achieve classification performance comparable to finance-specific transformer models without task-specific fine-tuning. However, higher classification accuracy does not translate into stronger economic relationships. Several models produce sentiment measures that are signific...
| Authors | Arslan Bisharat, Oudom Hean |
|---|---|
| Primary category | cs.LG |
| Published | 29 July 2026 |
| Last updated at source | 29 July 2026 |
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