【摘要】 传统的资产定价模型从市场的角度对资产价格进行定价，但是市场背后的投资者交互行为与股票资产价格关系密切，仅从市场的角度无法完全解释资产价格。本文使用复杂网络分析方法对投资者线上交互关系进行建模，通过股票论坛投资者交互网络的网络模体结构特征刻画投资者线上交互模式，并在Fama-French三因子模型的基础上加入了投资者交互模式因子构建四因子定价模型，研究发现，投资者交互因子具有较强的定价能力，并且加入交互因子的四因子模型定价效果比传统三因子模型和动量因子四因子模型更好。本研究为大数据框架下非结构化文本信息的市场价值提供了实证依据。更多还原

【Abstract】 The traditional asset pricing model prices assets from the perspective of the market, but asset prices cannot be fully explained because the investor interaction behavior behind the market is closely related to the stock asset price. This paper uses the complex network method to model the investor interaction relationship, describes the interactive patterns of online investors through the motif structure of the investor interaction network in the stock forum. Based on the Fama-French three-factor model, the investor interaction factor is added to construct a four-factor pricing model. It is found that investor interaction factor has certain pricing power, and the pricing effect of the four-factor model with interaction factor is stronger than that of the traditional three-factor model and the four-factor model with momentum factor. This study provides empirical evidence for the market value of unstructured text information under the big data framework.更多还原