---
title: AI Sentiment Analysis
url: https://www.ml-quant.com/papers/ssrn/4984337/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4984337
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4984337
featured: 2024-10-17
citations: unknown
topic: LLMs & Text
---


# AI Sentiment Analysis

The study shows that AI-rewritten SEC filings increase positive sentiment, positively affecting stock prices, emphasizing the need for careful AI use in financial disclosures.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4984337
- Identifier: SSRN 4984337
- Released: 2024-10-11
- First featured: Quant Letter No. 70 (2024-10-17): https://www.ml-quant.com/issues/2024-10-17/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: LLMs & Text

## Related

- [Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models](https://www.ml-quant.com/papers/ssrn/4412788/): ChatGPT predicts stock market returns using sentiment analysis, outperforming traditional methods.
- [Sentiment trading with large language models](https://www.ml-quant.com/papers/doi/10-1016-j-frl-2024-105227/): The OPT model, a large language model, has proven superior in predicting stock market returns using sentiment analysis of U.S. financial news, outdoing traditional methods like the Loughran-McDonald dictionary model.
- [Designing Heterogeneous LLM Agents for Financial Sentiment Analysis](https://www.ml-quant.com/papers/arxiv/2401.05799/): A study suggests using large language models without fine-tuning for financial sentiment analysis, offering a design framework that enhances accuracy.
- [Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models](https://www.ml-quant.com/papers/arxiv/2306.12659/): A new approach improves financial sentiment analysis by addressing limitations of language models.
- [Blending Ensemble for Classification with Genetic-algorithm generated Alpha factors and Sentiments (GAS)](https://www.ml-quant.com/papers/arxiv/2411.03035/): The article introduces a Genetic Algorithm-generated Alpha Sentiment (GAS) model that uses advanced learning techniques and sentiment analysis to predict Bitcoin market trends and price changes.
- [InkubaLM: A small language model for low-resource African languages](https://www.ml-quant.com/papers/arxiv/2408.17024/): African Language Model: InkubaLM, a language model for African languages, is introduced, performing well in tasks like machine translation and sentiment analysis despite limited resources.
