Sector connectedness in the Chinese stock markets

Ying-Ying Shen, Zhi-Qiang Jiang (), Jun-Chao Ma, Gang-Jin Wang and Wei-Xing Zhou
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Ying-Ying Shen: East China University of Science and Technology
Zhi-Qiang Jiang: East China University of Science and Technology
Jun-Chao Ma: East China University of Science and Technology

Empirical Economics, 2022, vol. 62, issue 2, No 19, 825-852

Abstract: Abstract Uncovering the risk-transmitting path within economic sectors in China is crucial for understanding the stability of the Chinese economic system, especially under the current situation of the China–US trade conflicts. In this paper, we aim to uncover the risk spreading channels by means of volatility spillovers within the Chinese sectors using stock market data. By applying the generalized variance decomposition framework based on the VAR model and the rolling window approach, a set of connectedness matrices is obtained to reveal the overall and dynamic spillovers within sectors. We find that 17 sectors (mechanical equipment, electrical equipment, utilities, and so on) are risk transmitters and 11 sectors (national defense, bank, non-bank finance, and so on) are risk takers during the whole period. Under the extreme risk events (i.e., the global financial crisis, the Chinese interbank liquidity crisis, the Chinese stock market crash, and the China–US trade war), the connectedness measures significantly increase and the financial sectors play a buffer role in stabilizing the economic system. Our results are robust to changes of the model parameters. Our study not only uncovers the spillover effects within the Chinese sectors, but also highlights the deep understanding of the risk contagion patterns in the Chinese stock markets.

Keywords: Network connectedness; Volatility spillovers; Financial networks; Stock market sectors; Connectedness indexes; G14; C51; C52 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (12)

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Working Paper: Sector connectedness in the Chinese stock markets (2020)
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DOI: 10.1007/s00181-021-02036-0

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