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股票市场中的大型语言模型:应用,技术和见解

Aakanksha Jadhav¹, Vishal Mirza¹

¹Independent Researcher, New York, NY, United States.

Frontiers in artificial intelligence

|September 12, 2025

概括

大型语言模型 (LLM) 正通过先进的数据分析和交易来改变股票投资. 这份对84项研究的综述绘制了LLM应用程序,方法和数据集,突出了未来AI在金融领域的研究方向.

科学领域:

人工智能的人工智能
计算金融是指计算金融.
金融中的机器学习

背景情况:

大型语言模型 (LLM) 展示了通过复杂的数据分析,市场预测和自动交易来彻底改变股票投资的巨大潜力.
法律法规的快速发展需要对其在金融领域的当前和潜在应用有全面的了解.

研究的目的:

对2022年至2025年初的股票投资中大语言模型 (LLM) 应用的84项研究进行全面审查.
根据金融任务和技术方法对LLM应用进行分类,并分析所使用的数据集和模型类型.
确定关键的研究趋势,优势,缺口,并为人工智能驱动的金融策略提出未来研究方向.

主要方法:

84项研究研究的系统文献综述.
应用程序 (股票价格预测,情绪分析,投资组合管理,算法交易) 和方法 (提示,微调,多代理框架,强化学习,定制架构) 的双层分类.
数据集 (财务报表,多式联络数据) 和LLM类型 (通用与金融专业) 的整合和比较.

主要成果:

在股票投资领域的LLM应用包括预测,情绪分析,投资组合管理和算法交易.
研究利用从财务报表到多式联络数据的各种数据集,采用各种LLM技术,如微调和强化学习.
主要优势包括改进的情绪分析和市场反集成,而在可扩展性,可解释性和现实世界的验证方面存在差距.

结论:

法学士课程为股票投资提供了强大的工具,正在进行的研究探索各种应用和方法.
未来的研究应该专注于混合模型,具有大型上下文窗口的高级架构和强大的评估框架.
本综述为推进人工智能驱动的金融策略和在金融部门的实际实施提供了基础路线图.

关键词:

在LLMS中,LLMS是最重要的.大型语言模型在NLP中,我们使用了NLP.算法交易是一种算法交易.股权资本股权资本金融金融金融金融金融投资投资是投资.公司股票股票股票股票

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