Since the global financial crisis of 2007–2009, preventing financial crises has become one of the most important objectives of regulators and banks. Although previous studies have identified the phenomenon of risk contagion in the banking system, the underlying mechanisms of risk contagion are still unclear. This study delves into the multi-stage contagion mechanism of liquidity risk based on interbank lending linkages and clearing rules and introduces a new index to quantify bank liquidity risk. We find that the contagion of liquidity risk is primarily determined by the network structure of risk exposures between banks in default and is not significantly influenced by the lending relationships of banks that remain solvent. The empirical results suggest that banks with high risk should be prioritized for cash injections to improve system liquidity. These findings offer new insights into financial risk contagion and practical recommendations for regulatory authorities formulating intervention strategies and for banks conducting risk management.

This paper analyzes the amplification characteristics of risk propagation in multi-layer financial networks from the perspective of network topologies. The research finds that, even without feedback pathways, cross-layer links alone can lead to more severe risk contagion than in single-layer networks. More importantly, with increasing connectivity, the formation of cyclic structures in multi-layer networks will significantly exacerbate the systemic risk.

As the world’s two largest economies, China and the US are currently experiencing political and economic friction. This conflict brings high uncertainty to financial markets. Assessing risk spillover effects in a sector level will help us to characterize international risk contagions. We construct a multilayer network to examine tail risk spillovers between China and the US and find that (1) the value of total connectedness rises amidst tensions but declines during reconciliations; (2) interlayer spillovers mainly manifest as extreme pulses instead of steady outflows, which implies a significant increase in the frequency and magnitude of interlayer spillovers requires vigilant monitoring; and (3) compared with the in-strength, the out-strength is more concentrated, which represents that some sectors may play the role of major interlayer transmitter in tail risk spillovers. Monitoring interlayer spillovers helps policymakers and investors respond to emerging systemic threats.

The COVID-19 pandemic has inflicted substantial impacts on global financial markets and the economy. This study explores the impact of two pandemic outbreaks in China on its stock market industries. It employs the Conditional Autoregressive Value at Risk (CAViaR) model to compute tail risks across 16 selected industry sectors. Additionally, risk correlation networks are constructed to illustrate the risk correlations among industry sectors during different phases of the two outbreaks. Furthermore, risk contagion networks are built based on the Granger causality test to examine the similarities and differences in the contagion mechanisms between the two outbreaks. The findings of this study show that (i) the two outbreaks of COVID-19 have resulted in tail risks for most industries in the Chinese stock market. (ii) The risk correlation network became more compact because of both outbreaks. The impact of the second outbreak on the network was less severe than that of the first outbreak. (iii) During the first outbreak of COVID-19, the financial industry was the primary source of risk output; during the second outbreak, the concentrated outbreak in Shanghai led the industries closely related to the city's economy and trade to become the most significant risk industries. These findings have practical implications for researchers and decision-makers in terms of risk contagion among stock market industries under major public emergencies.

This paper researches into development of China’s shadow banking during 2020-2022, a special period marked by COVID-19 and strengthened global regulation on Non-Bank Financial Intermediation (NBFI). Research focus includes balance sheet evolvement, growth dynamics, and relation with macro-finance. Its business model surprisingly resembles western peers. They both fund underserved sectors and have similar exposure to balance sheet mismatch. Massive holding of bond investment (36.6% of total asset) is funded by uninsured interbank fund and wealth management product, which makes it more closely related with banks’ balance sheet and risk contagion from NBFI to traditional commercial banks more easily. This paper then re-summarizes growth dynamics of China’s shadow banking in a “Pull-Push” framework, and proposes concept of reintermediation in respective to disintermediation. Consecutive regulation on NBFI and real estate sector kept dragging on growth of shadow banking, and rendered it in liquidity surplus, which is invested into interbank market. This paper also provides empirical evidence on relation of China’s shadow banking with macro-finance, and notes several empirical breakdowns of pre- COVID relations among economic and financial indicators. Most important breakdown is the non-functionality of monetary policy transmission channel. Besides, it continued to twist de facto financial regulatory indicators, however with fading impact.

This paper investigates the impact of the COVID-19 pandemic on the volatility spillover and dependence structure among the major developed and emerging stock markets. The TVP-VAR connectedness decomposition approach and R-vine copula are implemented in this research. The results of the TVP-VAR connectedness decomposition approach reveal that the volatility spillover among the major developed and emerging stock markets has been significantly strengthened by the outbreak of the COVID-19 pandemic, although it has gradually faded over time. In addition, during the pandemic, the UK, German, French and Canadian stock markets are the spillover transmitters, while the Japanese, Chinese Hong Kong, Chinese and Indian stock markets are the receivers. It is also found that the US and Brazilian stock markets have undergone role shifts after the outbreak of the COVID-19 pandemic. The results of the R-vine copula model indicate that during the pandemic, the Canadian, French, and Chinese Hong Kong stock markets are the most important financial centre in the American, European, and Asian stock markets, respectively. Furthermore, the effect of the extreme risk contagion has been strengthened by the pandemic, particularly the downside risk contagion.