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The authors estimate systemic risk in the Korean economy using the econometric measures of commonality and connectedness applied to stock returns. To assess potential systemic risk concerns arising from the high concentration of the economy in large business groups and a few export-oriented sectors, the authors perform three levels of estimation using individual stocks, business groups, and industry returns. The results show that the measures perform well over the study’s sample period by indicating heightened levels of commonality and interconnectedness during crisis periods. In out-of-sample tests, the measures can predict future losses in the stock market during the crises. The authors also provide the recent readings of their measures at the market, chaebol, and industry levels. Although the measures indicate systemic risk is not a major concern in Korea, as they tend to be at the lowest level since 1998, there is an increasing trend in commonality and connectedness since 2017. Samsung and SK exhibit increasing degrees of commonality and connectedness, perhaps because of their heavy dependence on a few major member firms. Commonality in the finance industry has not subsided since the financial crisis, suggesting that systemic risk is still a concern in the banking sector.

The paper models the financial interconnectedness and systemic risk of shadow banks using Granger-causal network-based measures and takes the Indian shadow bank crisis of 2018–2019 as a systemic event.

The paper employs pairwise linear Granger-causality tests adjusted for heteroskedasticity and return autocorrelation on a rolling window of weekly returns data of 52 financial institutions from 2016 to 2019 to construct network-based measures and calculate network centrality. The Granger-causal network-based measure ranking of financial institutions in the pre-crisis period (explanatory variable) is rank-regressed with the ranking of financial institutions based on maximum percentage loss suffered by them during the crises period (dependent variable).

The empirical result demonstrated that the shadow bank complex network during the crisis is denser, more interconnected and more correlated than the tranquil period. The closeness, eigenvector, and PageRank centrality established the systemic risk transmitter and receiver roles of institutions. The financial institutions that are more central and hold prestigious positions due to their incoming links suffered maximum loss. The shadow bank network also showed small-world phenomena similar to social networks. Granger-causal network-based measures have out-of-sample predictive properties and can predict the systemic risk of financial institutions.

The study considers only the publicly listed financial institutions. Also, the proposed measures are susceptible to the size of the rolling window, frequency of return and significance level of Granger-causality tests.

Supervisors and financial regulators can use the proposed measures to monitor the development of systemic risk and swiftly identify and isolate contagious financial institutions in the event of a crisis. Also, it is helpful to policymakers and researchers of an emerging economy where bilateral exposures' data between financial institutions are often not present in the public domain, plus there is a gap or delay in financial reporting.

The paper is one of the first to study systemic risk of shadow banks using a financial network comprising of commercial banks and mutual funds. It is also the first one to study systemic risk of Indian shadow banks.

This paper aims to analyze systemic risk in and the effect of capital regulation on the European insurance sector. In particular, the evolution of an exposure measure (SRISK) and a contribution measure (Delta CoVaR) are analyzed from 1985 to 2016.

With the help of multivariate regressions, the main drivers of systemic risk are identified.

The paper finds an increasing degree of interconnectedness between banks and insurance that correlates with systemic risk exposure. Interconnectedness peaks during periods of crisis but has a long-term influence also during normal times. Moreover, the paper finds that the insurance sector was greatly affected by spillovers from the process of capital regulation in banking. While European insurance companies initially at the start of the Basel process of capital regulation were well capitalized according to the SRISK measure, they started to become capital deficient after the implementation of the model-based approach in banking with increasing speed thereafter.

These findings are highly relevant for the ongoing global process of capital regulation in the insurance sector and potential reforms of Solvency II. Systemic risk is a leading threat to the stability of the global financial system and keeping it under control is a main challenge for policymakers and supervisors.

This paper provides novel tools for supervisors to monitor risk exposures in the insurance sector while taking into account systemic feedback from the financial system and the banking sector in particular. These tools also allow an evidence-based policy evaluation of regulatory measures such as Solvency II.

In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.

By the means of RAS algorithm, the interconnection among financial institutions are illustrated. Different methods, including Linear Granger, Systemic impact index (SII), vulnerability index (VI), CoVaR, and MES are used to measure the systemic risk exposures across different institutions.

The results illustrate that big banks are more interconnected and hold the biggest scales of inter-bank transactions in the financial network. The institutions which have larger size tend to have more connection with others. Insurance and security companies contribute more to the systemic risk where as other institutions, such as trusts, financial companies, etc. may bring about severe loss and endanger the financial system as a whole.

Since other institutions with low levels of regulation may bring about higher extreme loss and suffer the whole system, it deserves more attention by regulators considering the contagion of potential risks in the financial system.

This study builds a valuable contribution by examine the systemic risks from the perspectives of both interconnection and tail risk measures. Furthermore; Four types financial institutions are investigated in this paper.

This paper aims to investigate the drivers of systemic risk and contagion among European banks from 2007 to 2012. The authors explain why some banks are expected to contribute more to systemic events in the European financial system than others by analysing the tail co-movement of banks’ security prices.

First, the authors derive a systemic risk measure from the concepts of marginal expected shortfall and conditional value at risk analysing tail co-movements of daily bank stock returns. The authors then run panel regressions for the systemic risk measure using idiosyncratic bank characteristics and a set of country and policy control variables.

The results comprise highly significant drivers of systemic risk in the European banking sector with important implications for research and banking regulation. Using a set of panel regressions, the authors identify bank size, asset and income structure, loss and liquidity coverage, profitability and several macroeconomic conditions as drivers of systemic risk.

Analysing the tail co-movement of security prices excludes a number of “smaller” institutions without publicly listed securities. The other shortfall is that we do not assess the systemic impact of non-bank financial institutions.

Regulators have to consider a broad variety of indicators for assessing systemic risks. Existing microprudential-oriented rules are less effective, and policymakers may consider new measures like asset diversification to mitigate systemic risks in the banking system.

The authors contribute to existing empirical analyses in three ways. First, they propose a method to identify systemically important banks (SIBs). Second, they develop two measures to assess their potential negative impact on the system. Third, they contribute to the closing of the research gaps by analysing which macroprudential regulations for SIBs are most effective without hampering free market forces.

The purpose of this paper is to investigate the effects of audit client importance on future bank risk and systemic risk in US-listed commercial banks.

The authors use archival research method.

The authors mainly find that client importance is negatively related with future bank-specific crash risk and distress risk, and also with sector-wide systemic crash risk and systemic distress risk in the future. The authors also report some evidence that these relations become more pronounced during the crisis period than during the non-crisis period. Moreover, the effect of client importance on systemic risk is found to strengthen in banks audited by Big-N auditors, by auditors without clients who restate earnings, and by auditors with more industry expertise.

These findings contribute to the auditing and systemic risk literature.

This study has implications for regulating the banking industry.

This study provides original evidence on how client importance affects bank-specific risk and systemic risk of the banking industry.

The purpose of this paper is to measure a single financial institution's contribution to systemic risk by using extremal quantile regression and analyzing the influential factors of systemic risk.

Extreme value theory is applied when measuring the systemic risk of financial institutions. Extremal quantile regression, where extreme value distribution is assumed for the tail, is used to measure the extreme risk and analyze the changes in and dependencies of risk. Furthermore, influential factors of systemic risk are analyzed using panel regression.

The key findings of the paper are that value at risk and contribution to systemic risk are very different when measuring the risk of a financial institution; banks’ contributions to systemic risk are much higher; and size and leverage ratio are two significant and important factors influencing an institution's systemic risk.

Characterizing variables of financial institutions such as size, leverage ratio and market beta should be considered together when regulating and constraining financial institutions.

To take extreme risk into account, this paper measures systemic financial risk using extremal quantile regression for the first time.

There is an emerging consensus that systemically important banks should face stricter regulations and systemic surcharges. To make this latter principle operational the regulator will need to quantify the systemic importance of individual banks. The purpose of this paper is to review the proposed measures of systemic importance from the research community and discuss their merits relative to how a regulator would ideally wish to calibrate surcharges on systemically important banks, and to evaluate how useful proposed measures of the systemic importance of financial institutions will be to regulators.

The author reviews the main contributions to the research literature and discusses their relevance for the problem faced by regulators.

There are five main caveats that make the proposed measures of systemic importance less useful for regulators.

The proposed measures may help identify relevant aspects of systemic importance, but the regulators will need to construct their own measures for practical use.

The paper provides a critical review of a research literature that could potentially have large practical implications.

This paper sheds light on the impact of market risk measures on systemic risk. Market risk, which is captured by the volatility of stock market returns, is also decomposed into systematic and idiosyncratic risks.

The author uses the five-factor asset pricing model and systemic risk methodologies to derive market and systemic risk measures, respectively. Using a sample of 2,667 US banks for over 30 years and employing panel data estimation techniques, the author tests the said relationship.

It is shown that idiosyncratic risk can surge systemic risk, while systematic risk plays a less important role. Results survive a battery of tests, including different systemic risk measures, controlling causality and interacting with bank size, market fear and crisis periods.

These findings call for regulatory intervention, especially for large banks with high idiosyncratic risk.

This is the first paper that provides a more granular picture of the relationship between market and systemic risk from the US banking industry for more than 30 years.

Viewing the domestic downside risk as a “pushing” factor for outward foreign direct investment (OFDI), this study aims to examine the surge in Chinese cross-border acquisitions (CBAs) between 2008 and 2017, a unique window when private firms in China were allowed to conduct CBAs.

This study examines the effect of down-side risk on cross-border acquisition performance by using the sample of Chinese A-share listed companies from 2008 to 2017. Specifically, this study considers three kinds of systemic risk, systematic risk and idiosyncratic risk, and respectively examines their impact on CBAs activities; this study also investigates their subsequent results after CBAs activities. The contingency effect of state ownership on the above relationship is also discussed.

The findings reveal that pre-CBA systemic risk explains the volume of CBA activities; CBAs are followed by a reduction in systemic risk; the interactions between systemic risk and CBAs decrease with the level of state ownership; and the above results do not hold for traditional risk measures (i.e. systematic risk and idiosyncratic risk).

This study contributes to the literature by revealing the role of systemic risk as a “pushing” factor in the context of OFDI and suggesting an alternative explanation for CBAs from China: Chinese firms (especially private firms) took advantage of the rare opportunity between 2008 and 2017 given by the government to transfer assets overseas through CBA.