Evaluating risk dynamics in Shanghai composite and China sectoral markets

COVID-19 has affected China's financial markets; accordingly, we investigate the effect of COVID-19 on the risk spillover between fintech and traditional financial industries. Using data from April 25, 2012 to April 22, 2022, which we divide into two parts (before and during the COVID-19 periods), we model the dynamic risk spillover relationship following the DCC-GARCH-BEKK and MMV-MFDFA methods. The results show that: (1) The dynamic relationship between fintech and traditional finance is almost positive most of the time, and the dynamic correlations between fintech and realty (real estate development and operation) are the largest. The dynamic linkage between fintech and traditional finance declines after the COVID-19 outbreak. (2) There exists a risk spillover from fintech to every type of bank before and during the COVID-19 periods. Notably, the risk spillover effect of fintech to large state-owned banks and city commercial banks is the largest separately before and during the COVID-19 periods. Meanwhile, there exist a two-way risk spillover between fintech and almost all other traditional financial industries before and during the COVID-19 periods. (3) Owing to the COVID-19 pandemic, the risk spillover relationship, which is in pairs and in the system become more complex. (4) Regarding the whole system, the correlation in the system is anti-persistent most of the time. Moreover, there are large fluctuations and more complex characteristics during the COVID-19 outbreak. However, the whole system was smooth most of the time before the outbreak of the COVID-19 pandemic.

This article adopts the new point of view on dynamic time‐varying based research, combined with the Copula and CoVaR model, to analyse the risk spillover effect of mainland China, Hong Kong and the US stock markets as well as the multi‐dimensional formation mechanism from the perspective of macroeconomic variables (VXFXI, EER, EPU and Liquidity) using TVP‐VAR‐SV and impulse response model. First, we find that the constructed copula models can address the asymmetry of stock market systemic risk spillover and the characteristics of co‐movement with better tail dependence estimation. Second, there is an obvious risk spillover effect between the Shanghai Composite Index (SSEC) and Shenzhen Component Index (SZEC). Due to the development of two connect programs, systemic risk can spread quickly from the Hang Seng Index (HSI) to SSEC and SZEC. Third, since the structure and participants of Chinese stock market, all macroeconomic variables make strongly positive and significant nonlinear impact on ΔCoVaR and exhibit significant non‐symmetric characteristics in the long‐ and short‐term perspectives, especially for EPU. These results indicate that strengthening the interconnections among systemically global stock markets is of important practical significance. Also, regulators should pay more attention on the policy uncertainty between economic and financial policy released time and lag 4‐month period.

This Special Issue was conceived and developed following a series of international conferences held in Asia, with a particular focus on critically reflecting upon higher education development in the region from broader social and political economy perspectives. Some of the papers in this Special Issue were selected from presentations in the East Asia Social Policy (EASP) Research Network Conference successfully held in Taiwan in 2018, while others were chosen from international events held at Lingnan University in Hong Kong presenting critical reviews and reflections on internationalization, marketization and graduate employment of higher education in Asia. This introductory article puts the discussions of the selected papers in this issue in context, with critical reflections on the key issues being examined in these papers. The Special Issue is published when the world is still confronting the unprecedented global health crisis resulted from the outbreak of the COVID‐19 pandemic. This article discusses the higher education development trends in Asia through the massification, diversification and internationalisation processes in transforming the higher education system and examines how these development trends are affected by the COVID‐19 crisis.

Tail-risk spillovers from China to G7 stock market returns during the COVID-19 outbreak: A market and sectoral analysis

Systemic risk spillover across global and country stock markets during the COVID-19 pandemic

PurposeThis paper examines the extreme dependence and asymmetric risk spillovers between crude oil futures and ten US stock sector indices (consumer discretionary, consumer staples, energy, financials, health care, industrials, information technology, materials, telecommunication and utilities) before and during COVID-19 outbreak. This study is based on the rationale that stock sectors exhibit heterogeneity in their response to oil prices depending on whether they are classified as oil-intensive or non-oil-intensive sectors and the possible time variation in the dependence and risk spillover effects.Design/methodology/approachThe authors employ static and dynamic symmetric and asymmetric copula models as well as Conditional Value at Risk (VaR) (CoVaR). Finally, they use robustness tests to validate their results.FindingsBefore the COVID-19 pandemic, crude oil returns showed an asymmetric tail dependence with all stock sector returns, except health care and industrials (materials), where an average (symmetric tail) dependence is identified. During the COVID-19 pandemic, crude oil returns exhibit a lower tail dependency with the returns of all stock sectors, except financials and consumer discretionary. Furthermore, there is evidence of downside and upside risk asymmetric spillovers from crude oil to stock sectors and vice versa. Finally, the risk spillovers from stock sectors to crude oil are higher than those from crude oil to stock sectors, and they significantly increase during the pandemic.Originality/valueThere is heterogeneity in the linkages and the asymmetric bidirectional systemic risk between crude oil and US economic sectors during bearish and bullish market conditions; this study is the first to investigate the average and extreme tail dependence and asymmetric spillovers between crude oil and US stock sectors.

Risk spillover from crude oil prices to GCC stock market returns: New evidence during the COVID-19 outbreak

Purpose: In the current era of information, global stock market interconnections significantly influence investment decisions. Changes in one market rapidly affect others. The co-movement of stock markets presents challenges and opportunities for investors, whereas volatility spillovers complicate risk management and investment strategies. Research Methodology: This study examines the influence of the Nikkei 225, Straits Times Index, and Shanghai Composite Index on the Jakarta Composite Index across the pre-pandemic, pandemic, and post-pandemic phases. Results: Utilizing the hidden Markov model with regime-switching regression, this study identifies changes in market behavior due to economic shifts during the pandemic, revealing two regimes: synchronization and desynchronization. Limitations: Pre-COVID-19, the Jakarta Composite Index shows strong synchronization with the Nikkei 225 and Straits Times Index, while the Shanghai Composite Index has an insignificant impact. During the COVID-19 pandemic, frequent desynchronization occurred due to high uncertainty and volatility, with only the Straits Times Index significantly influencing the Jakarta Composite Index. Post-pandemic, synchronization between the JCI and regional markets strengthened again. This study highlights the consistent influence of the Nikkei 225 and Straits Times Index, while the Shanghai Composite Index remains insignificant. Contributions: This study contributes significantly to the understanding of regional stock market relationships and offers valuable insights for academia and practice.

Purpose: In the current era of information, global stock market interconnections significantly influence investment decisions. Changes in one market rapidly affect others. The co-movement of stock markets presents challenges and opportunities for investors, whereas volatility spillovers complicate risk management and investment strategies. Research Methodology: This study examines the influence of the Nikkei 225, Straits Times Index, and Shanghai Composite Index on the Jakarta Composite Index across the pre-pandemic, pandemic, and post-pandemic phases. Results: Utilizing the hidden Markov model with regime-switching regression, this study identifies changes in market behavior due to economic shifts during the pandemic, revealing two regimes: synchronization and desynchronization. Conclusions: The N225 and STI indices have a consistently positive and significant influence on the JCI, whereas SCI shows a negative but statistically insignificant impact. During the pandemic (March 2020 to April 2021), market desynchronization increased, reducing the significance of N225 while STI remained impactful. Post-pandemic, synchronization improved, and both N225 and STI regained their significant influence on JCI, indicating strengthened regional market integration. Limitations: Pre-COVID-19, the Jakarta Composite Index shows strong synchronization with the Nikkei 225 and Straits Times Index, while the Shanghai Composite Index has an insignificant impact. During the COVID-19 pandemic, frequent desynchronization occurred due to high uncertainty and volatility, with only the Straits Times Index significantly influencing the Jakarta Composite Index. Contributions: This study contributes significantly to the understanding of regional stock market relationships and offers valuable insights for academia and practice.

Do cryptocurrencies provide better hedging? Evidence from major equity markets during COVID-19 pandemic

Does the asymmetric dependence volatility affect risk spillovers between the crude oil market and BRICS stock markets?

Risk spillovers across geopolitical risk and global financial markets

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.

Researchers and authorities have become increasingly interested in how the COVID-19 pandemic has profoundly impacted the real economy and financial markets around the world since its outbreak in late 2019. Applying the methods of multifractal analysis, this paper investigates the fluctuation characteristics and market risks of Chinese industry and stock markets under the COVID-19 pandemic, and reveals the whole dynamics of industry and stock markets from the perspective of system theory. The empirical results show that the multifractal strength of the industry market has significantly increased during the pandemic with elevated systematic risk, while the situation is different for the stock market. Specifically, the Hurst surfaces generated using the multiscale technique intuitively visualize the dynamical behaviors of the systematic fluctuation of the Chinese industry and stock markets at various scales under the COVID-19 pandemic. Furthermore, it is found that the sources of multifractality of the two types of markets include long-range correlation and fat-tailed distribution, with the contribution of fat-tailed distribution being greater. The chi-square test is promoted in this paper to measure the contribution of the internal components of the multivariate system to the multifractality sources of the whole system, revealing that the real estate industry has a greater impact on the multifractality of the whole industry system, while the Shanghai Composite Index has a stronger influence on the whole stock system.

Exploring interconnectedness between climate change, renewable energy, technological innovation, and G-17 banking stock markets