Sectoral risk contagion and quantile network connectedness on Chinese stock sectors after the COVID-19 outbreak

IF 9 1区 经济学 Q1 BUSINESS, FINANCE China Finance Review International Pub Date : 2023-07-14 DOI:10.1108/cfri-02-2023-0039
Yang Gao, Wanqi Zheng, Yaojun Wang
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引用次数: 1

Abstract

PurposeThis study aims to explore the risk spillover effects among different sectors of the Chinese stock market after the outbreak of COVID-19 from both Internet sentiment and price fluctuations.Design/methodology/approachThe authors develop four indicators used for risk contagion analysis, including Internet investors and news sentiments constructed by the FinBERT model, together with realized and jump volatilities yielded by high-frequency data. The authors also apply the time-varying parameter vector autoregressive (TVP-VAR) model-based and the tail-based connectedness framework to investigate the interdependence of tail risk during catastrophic events.FindingsThe empirical analysis provides meaningful results related to the COVID-19 pandemic, stock market conditions and tail behavior. The results show that after the outbreak of COVID-19, the connectivity between risk spillovers in China's stock market has grown, indicating the increased instability of the connected system and enhanced connectivity in the tail. The changes in network structure during COVID-19 pandemic are not only reflected by the increased spillover connectivity but also by the closer relationships between some industries. The authors also found that major public events could significantly impact total connectedness. In addition, spillovers and network structures vary with market conditions and tend to exhibit a highly connected network structure during extreme market status.Originality/valueThe results confirm the connectivity between sentiments and volatilities spillovers in China's stock market, especially in the tails. The conclusion further expands the practical application and theoretical framework of behavioral finance and also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management across stock sectors.
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新冠肺炎疫情后中国股市的行业风险传染和分位数网络连通性
目的本研究旨在从互联网情绪和价格波动两方面探讨新冠肺炎疫情爆发后中国股市不同行业之间的风险溢出效应。作者开发了用于风险传染分析的四个指标,包括由FinBERT模型构建的互联网投资者和新闻情绪,以及由高频数据产生的实现和跳跃波动率。作者还应用基于时变参数向量自回归(TVP-VAR)模型和基于尾部的连通性框架来研究灾难性事件中尾部风险的相互依赖性。实证分析提供了与COVID-19大流行、股市状况和尾部行为相关的有意义的结果。结果表明,新冠肺炎疫情爆发后,中国股市风险溢出之间的连通性增强,表明连接系统的不稳定性增加,尾部的连通性增强。新冠肺炎疫情期间网络结构的变化不仅体现在外溢连通性增强,还体现在部分行业之间的联系更加紧密。作者还发现,重大公共事件会显著影响整体联系。此外,溢出效应和网络结构随市场条件的变化而变化,在极端市场状态下往往呈现高度连接的网络结构。研究结果证实了情绪与中国股市波动溢出之间的联系,特别是在尾部。结论进一步拓展了行为金融学的实际应用和理论框架,也为投资者关注波动性预测和风险管理跨板块的实际应用奠定了理论基础。
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来源期刊
CiteScore
12.40
自引率
1.20%
发文量
112
期刊介绍: China Finance Review International publishes original and high-quality theoretical and empirical articles focusing on financial and economic issues arising from China's reform, opening-up, economic development, and system transformation. The journal serves as a platform for exchange between Chinese finance scholars and international financial economists, covering a wide range of topics including monetary policy, banking, international trade and finance, corporate finance, asset pricing, market microstructure, corporate governance, incentive studies, fiscal policy, public management, and state-owned enterprise reform.
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