The Network Factor of Equity Pricing: A Signed Graph Laplacian Approach
提出符号图拉普拉斯方法构建动态网络指数（DNI），量化企业关联网络变化，发现对DNI敏感的企业预期收益更低，加入DNI可提升资产定价模型预测力。
Abstract The connections among firms exhibit heterogeneity, complexity, and dynamism, posing a challenge for traditional unsigned network models. This article proposes a signed graph Laplacian approach to construct a dynamic network index (DNI), quantifying the aggregate changes in the market network over time. A larger DNI indicates more significant changes in firms’ interconnectedness and in the market network structure. Firms with higher sensitivity to DNI exhibit lower expected returns. Incorporating DNI into conventional asset pricing models improves return predictability. Results are robust for multiple estimators, various factor models, and different selections of test assets. Our findings suggest that the network factor generates a significant equity risk premium.