摘 要
行为金融学作为现代金融理论的重要分支，为理解投资者情绪对资产定价的影响提供了全新视角。本研究基于行为金融学理论框架，探讨了投资者情绪在资产定价中的作用机制及其市场表现。研究以中国A股市场为样本，选取2010年至2022年的高频交易数据，结合文本挖掘技术量化投资者情绪，并通过面板数据模型和事件分析法考察其对资产价格波动的动态影响。结果表明，投资者情绪显著影响资产定价，且这种影响具有非线性特征，在市场不确定性较高时尤为明显。此外，不同情绪维度（如乐观与悲观）对资产价格的作用方向和强度存在差异，这进一步验证了情绪驱动的异质性效应。本研究的创新点在于首次将文本情绪指标与传统金融变量相结合，构建了多维度的情绪综合测度体系，从而更全面地捕捉市场参与者的行为特征。同时，研究发现情绪效应对短期资产价格的影响更为显著，而长期价格仍主要由基本面因素主导，这一结论为市场有效性和行为偏差之间的关系提供了新的证据支持。总体而言，本研究不仅丰富了行为金融学的理论内涵，还为投资者决策及市场监管政策的制定提供了实践参考。
关键词：行为金融学；投资者情绪；资产定价；文本挖掘；市场有效性
Abstract
Behavioral finance, as a critical branch of modern financial theory, offers a novel perspective for understanding the impact of investor sentiment on asset pricing. This study investigates the mechanism and market implications of investor sentiment in asset pricing within the theoretical fr amework of behavioral finance. Using the Chinese A-share market as a sample, the research analyzes high-frequency trading data from 2010 to 2022, employing text mining techniques to quantify investor sentiment. The dynamic influence of sentiment on asset price volatility is examined through panel data models and event study methodologies. The findings indicate that investor sentiment significantly affects asset pricing, with this influence exhibiting nonlinear characteristics, particularly pronounced during periods of high market uncertainty. Moreover, different dimensions of sentiment, such as optimism versus pessimism, demonstrate varying directions and intensities in their effects on asset prices, further validating the heterogeneous effects driven by sentiment. An innovation of this study lies in its integration of textual sentiment indicators with traditional financial variables to construct a multidimensional composite sentiment measurement system, enabling a more comprehensive capture of market participants' behavioral traits. Additionally, the study reveals that sentiment effects are more pronounced on short-term asset prices, while long-term prices remain predominantly influenced by fundamental factors, providing new evidence regarding the relationship between market efficiency and behavioral biases. Overall, this research not only enriches the theoretical underpinnings of behavioral finance but also offers practical implications for investor decision-making and the formulation of regulatory policies.
Keywords: Behavioral Finance; Investor Sentiment; Asset Pricing; Text Mining; Market Efficiency
目 录
1绪论 1
1.1行为金融学与资产定价研究背景 1
1.2投资者情绪对资产定价的意义 1
1.3国内外研究现状综述 1
1.4本文研究方法与创新点 2
2投资者情绪的理论基础与测量方法 2
2.1行为金融学中的投资者情绪概念 2
2.2投资者情绪的主要驱动因素分析 3
2.3投资者情绪的量化与测量方法 3
2.4情绪指标在金融市场中的应用现状 4
2.5理论框架与研究假设构建 4
3投资者情绪对资产定价的影响机制 5
3.1资产定价的传统模型与局限性 5
3.2投资者情绪如何影响市场效率 5
3.3情绪偏差导致的资产价格偏离分析 6
3.4不同情绪状态下的投资者行为特征 6
3.5情绪影响机制的实证研究设计 7
4实证分析与结果讨论 7
4.1数据来源与样本选择标准 7
4.2投资者情绪与资产收益的相关性检验 8
4.3情绪波动对市场波动性的具体影响 8
4.4行业间情绪效应的异质性分析 9
4.5实证结果的稳健性与政策启示 9
结论 11
参考文献 12
致 谢 13
