关键词: 网络, 时变空间因子模型, 风险暴露分解, 行业收益率

Abstract: A complex and closely related production network has been formed in the industry through the input-output relationship, which has an important impact on the financial market. Meanwhile, the traditional factor pricing model ignores the influence of the production network, which can easily lead to model misspecification and confusion of systemic risk sources. Therefore, this paper constructs a spatial factor pricing model based on the time-varying network dependent parameters of the production network, by embedding into the traditional factor pricing model the time-varying production network constructed based on the input-output table released by the National Bureau of Statistics. By using this new pricing model, this paper studies the impact of the interaction between production networks and systemic risk factors on the rate of return of industries in China, by discomposing the total risk exposure of industry returns to factors into direct risk exposure and indirect risk exposure. The results show that compared with the traditional factor models, the spatial factor pricing model is more applicable to the rate of return and asset pricing of the industry in China. Compared with developed countries, China’s industrial structure has undergone significant changes in the past two decades, and the production network formed based on input-output relationship has also changed greatly. Therefore, the assumption of setting time-varying parameters as the spatial dependence parameters is more applicable to the economic reality in China, which will produce better empirical results. The decomposition of factor risk exposure also indicates that the spillover effect of the production network can amplify the risk exposure of industry returns to factors.

Key words: production network, time-varying spatial factor model, risk exposure decomposition, industry stock returns