Research on stock volatility risk and investor sentiment contagion from the perspective of multi-layer dynamic network |
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| Affiliation: | 1. School of Economics, Qingdao University, Qingdao 266061, China;2. College of Management and Economics, Tianjin University, Tianjin 300072, China;3. China Center for Social Computing and Analytics, Tianjin 300072, China;1. Central Bank of Turkey, Ümraniye, İstanbul, Turkey;2. Department of Business Administration, Middle East Technical University, 06800 Ankara, Turkey;1. School of International Economics and Trade, Nanjing University of Finance and Economics, Nanjing, China;2. Rotman Commerce, University of Toronto, Toronto, Canada;3. SHU-UTS SILC Business School, Shanghai University, 99 Shangda Road, Shanghai, China;1. School of Economics and Management, Southwest Jiaotong University, Chengdu, China;2. Service Science and Innovation Key Laboratory of Sichuan Province, China;1. School of Economics and Management, Beijing University of Chemical of Technology, Beijing, China;2. School of Economics and Management, Beijing Jiaotong University, Beijing, China;1. China Academy of West Region Development, Zhejiang University, No. 866, Yuhangtang Road, Hangzhou, Zhejiang, China, 310058;2. The Wang Yanan Institute for Studies in Economics, Xiamen University, No. 422, Simingnan Road, Xiamen, Fujian, China, 361005 |
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| Abstract: | In the post-epidemic period, the international economic structure has been readjusted, with risks contagious across financial and economic systems. This paper primarily uses the high-frequency TENET network and the Granger-causality network to describe the interconnectedness between the tail risk of stock volatility and investor sentiment, then the two-layer network is constructed by the generalized variance decomposition method to examine the inter-layer connectedness. Based on the two-layer network, the heterogeneity frequency response of network connectedness and dynamic network structure are further analyzed from the perspective of frequency domain. The study found that the tail risk of high-frequency stock volatility displays industry heterogeneity and time-varying property, and investor sentiment contagion network provides information transmission medium for stock risk. The double-layer network study found that stock volatility in consumer goods industry exhibits higher risk spillover to investor sentiment. The diversified financial industry, real estate industry and energy industry in the two-layer network are systemically important industries. In addition, the study of the frequency domain dynamic network found that the connectedness volatility in the short-term risk network of stock volatility was significantly higher than that of the investor sentiment network, and the short-term risk spillover effect of the network played a leading role in the total risk spillover. The research conclusions provide reference for preventing systemic risks from the perspective of systemically important industries and cyclical fluctuations. |
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