Analyzing the Stock Volatility Spillovers in Chinese Financial and Economic Sectors

被引:7
|
作者
Li, Jingyu [1 ]
Cheng, Lu [1 ]
Zheng, Xiaolong [2 ,3 ]
Wang, Fei-Yue [2 ,3 ]
机构
[1] Beijing Univ Technol, Sch Econ & Management, Beijing 100124, Peoples R China
[2] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
[3] Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China
基金
中国博士后科学基金;
关键词
COVID-19; financial and economic system; network analysis; stock volatility spillover; variational mode decomposition (VMD); EMPIRICAL MODE DECOMPOSITION; IMPULSE-RESPONSE ANALYSIS; SYSTEMIC RISK; BUSINESS CYCLES; CONNECTEDNESS; MARKET; MACROECONOMY; INFORMATION; PREDICTION; EFFICIENCY;
D O I
10.1109/TCSS.2021.3134487
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
By regarding the Chinese financial and economic sectors as a system, this article studies the stock volatility spillover in the system and explores its effects on the overall performance of the macroeconomy in China. The recent outbreak of COVID-19, U.S.-China trade friction, and three historical financial turbulences are involved to distinguish the changes in the spillover in these distinct crises, which has seldom been unveiled in the literature. By considering that the stock volatility spillover may vary over distinct timescales, the spillovers are disclosed through innovatively constructing the multi-scale spillover networks, followed by connectedness computation, based on variational mode decomposition (VMD) and generalized vector autoregression (GVAR) process. Our empirical analysis first demonstrates the different levels of increases in the total sectoral volatility spillover and changes in the roles of the sectors in the system under the aforementioned crises. Besides, the increases in the sectoral spillover in the long-term are verified to negatively impact the macroeconomy and can thereby act as warning signals.
引用
收藏
页码:269 / 284
页数:16
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