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English(EN) Augmenting Fundamental Analysis with Large Language Models: A RAG-Based System for Generating Investor Briefs

LLM和RAG系统从金融数据生成投资者简报

研究人员开发了一个使用大型语言模型(LLM)和检索增强生成(RAG)从金融和宏观经济数据创建投资者简报的系统。该系统处理报告、EDGAR的SEC文件以及宏观经济指标,然后使用GPT-4o生成摘要。九位个人投资者在为期四周的时间里评估了这些自动化简报,以评估它们在数据分析中的实用性。 AI

影响 这项研究展示了LLM在金融分析中的实际应用,有可能为投资者简化数据处理。

排序理由 该集群包含一篇学术论文,详细介绍了LLM和RAG在金融分析中的新颖应用。

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

LLM和RAG系统从金融数据生成投资者简报

报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Bartosz Zi\'o{\l}ko, Kacper Dobrzeniewski ·

    Augmenting Fundamental Analysis with Large Language Models: A RAG-Based System for Generating Investor Briefs

    arXiv:2607.09121v1 Announce Type: cross Abstract: In this study, we examine the opportunities brought by Large Language Models (LLMs) to various aspects of fundamental analysis of companies based on their reports as well as data and documents describing macroeconomic situation li…

  2. arXiv cs.AI TIER_1 English(EN) · Kacper Dobrzeniewski ·

    利用大型语言模型增强基本面分析:基于RAG的生成投资者简报系统

    In this study, we examine the opportunities brought by Large Language Models (LLMs) to various aspects of fundamental analysis of companies based on their reports as well as data and documents describing macroeconomic situation like GDP and inflation changes as well as documents …