The time-varying spillover effect of China’s stock market during the COVID-19 pandemic

Liu, Xueyong; Chen, Zhihua; Chen, Zhen‐Song; Yao, Yiming

doi:10.1016/j.physa.2022.127821

Cited by 8 publications

(2 citation statements)

References 42 publications

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“…Subsequently, Cheng et al (2021) and Aloui et al (2022) respectively examined China's risk spillovers to the G7 and BRICS stock markets and found that China's dependence and risk spillovers to both G7 and BRICS stock markets significantly increased during the COVID-19 pandemic. Moreover, Liu et al (2022) used the GARCH-BEKK model to build an interaction network and found that the COVID-19 outbreak increased the volatility spillovers of the Chinese stock market, and it weakened rapidly in the middle and late stages of the pandemic. In contrast, through the TVP-VAR-connectedness method, Tan et al (2022) argued that China's spillover effects on developed countries significantly increased in the post-COVID-19 era.…”

Section: Literature Reviewmentioning

confidence: 99%

Bidirectional Risk Spillovers between Chinese and Asian Stock Markets: A Dynamic Copula-EVT-CoVaR Approach

Zhao,

Park

2024

JRFM

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This study aims to investigate bidirectional risk spillovers between the Chinese and other Asian stock markets. To achieve this, we construct a dynamic Copula-EVT-CoVaR model based on 11 Asian stock indexes from 1 January 2007 to 31 December 2021. The findings show that, firstly, synchronicity exists between the Chinese stock market and other Asian stock markets, creating conditions for risk contagion. Secondly, the Chinese stock market exhibits a strong risk spillover to other Asian stock markets with time-varying and heterogeneous characteristics. Additionally, the risk spillover displays an asymmetry, indicating that the intensity of risk spillover from other Asian stock markets to the Chinese is weaker than that from the Chinese to other Asian stock markets. Finally, the Chinese stock market generated significant extreme risk spillovers to other Asian stock markets during the 2007–2009 global financial crisis, the European debt crisis, the 2015–2016 Chinese stock market crash, and the China–US trade war. However, during the COVID-19 pandemic, the risk spillover intensity of the Chinese stock market was weaker, and it acted as the recipient of risk from other Asian stock markets. The originality of this study is reflected in proposing a novel dynamic copula-EVT-CoVaR model and incorporating multiple crises into an analytical framework to examine bidirectional risk spillover effects. These findings can help Asian countries (regions) adopt effective supervision to deal with cross-border risk spillovers and assist Asian stock market investors in optimizing portfolio strategies.

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Section: Literature Reviewmentioning

confidence: 99%

Bidirectional Risk Spillovers between Chinese and Asian Stock Markets: A Dynamic Copula-EVT-CoVaR Approach

Zhao,

Park

2024

JRFM

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“…X. Liu et al (2022) stated that the BEKK-GARCH model is used to extract the interactions between financial time series. Moreover, the following distinguishing advantage of BEKK-GARCH is notable: the positive definiteness of the variance-covariance matrix and its efficiency in reducing parameters for estimation (Chen et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Stock Market Volatility Response to COVID-19: Evidence from Thailand

Suwannapak

Chancharat

2022

JRFM

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This study investigated how stock market volatility responded dynamically to unexpected changes during the COVID-19 pandemic and the resulting uncertainty in Thailand. Using a multivariate GARCH-BEKK model, the conditional volatility dynamics, the interlinkages, and the conditional correlations between stock market volatility and the increasing rate of COVID-19 infection cases are examined. The increased rate of COVID-19 infections impacts stock returns detrimentally; in Thailand, stock market volatility responses are asymmetric in the increase and decline situations. This disparity is due to the unfavourable impact of the pandemic’s volatility. Finally, we acknowledge that directional volatility spillover effects exist between the increase in COVID-19 cases and stock returns, suggesting that time-varying conditional correlations occur and are generally positive. Using this study’s results, governments and financial institutions can devise strategies for subsequent recessions or financial crises. Furthermore, investment managers can manage portfolio risk and forecast patterns in stock market volatility. Academics can apply our methodology in future investment trend studies to analyse additional variables in the economic system, such as the value of the US dollar, the price of commodities, or GDP.

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Evidence of the fractal market hypothesis in European industry sectors with the use of bootstrapped wavelet leaders singularity spectrum analysis

Lahmiri¹,

Bekiros²,

Bezzina³

2022

Chaos, Solitons & Fractals

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The time-varying spillover effect of China’s stock market during the COVID-19 pandemic

Cited by 8 publications

References 42 publications

Bidirectional Risk Spillovers between Chinese and Asian Stock Markets: A Dynamic Copula-EVT-CoVaR Approach

Bidirectional Risk Spillovers between Chinese and Asian Stock Markets: A Dynamic Copula-EVT-CoVaR Approach

Stock Market Volatility Response to COVID-19: Evidence from Thailand

Evidence of the fractal market hypothesis in European industry sectors with the use of bootstrapped wavelet leaders singularity spectrum analysis

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