基于GPT模型的基金经理情绪对基金超额收益的影响分析

本研究旨在探讨基金经理情绪状态对其管理基金超额收益的影响，并深入分析各类宏观经济因素和基金经理个人特征在其中的作用。基于易方达基金官方网站公布的50位基金经理225次言论数据，我们构建了基于GPT大模型的情绪评分系统，量化评估了基金经理的情绪状态。运用LASSO回归模型，本文实证检验了基金经理情绪评分与基金当月超额收益之间的关系，以及宏观经济指标、市场指标等因素的影响。研究发现，基金经理的积极情绪与基金超额收益呈显著正相关，且情绪评分每提高一个标准差，当月超额收益率提升空间平均增加0.977%。我们还发现，宏观经济因素如M2增速的上升、中小企业景气指数的下降，会显著调节情绪评分对基金业绩的积极影响。而基金经理的高学历和专业背景有助于提升基金业绩，而兼任其他职务则可能产生负面影响。本文的发现不仅丰富了行为金融学和基金管理的文献，也为量化投资实践提供了新的视角和方法，具有重要的理论价值和现实意义。

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