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This study tends to investigate how the outbreak of the coronavirus disease 2019 (COVID-19) pandemic has affected banks' contribution to systemic risk. In addition, the authors examine whether the impact of the pandemic may vary across advanced/emerging economies, and with banks with differed characteristics.

The authors construct the bank-specific conditional value at risk (CoVaR) and marginal expected shortfall (MES) to measure their contribution to systemic risk and define the outbreak of the COVID-19 pandemic by the timing when countries report more than 100 confirmed cases. The authors use the approach of difference-in-differences to assess the impact of the COVID-19 pandemic on banks' contribution to systemic risk. This sample comprises monthly panel data of around 900 listed commercial banks in 39 advanced and emerging economies.

The authors find that, firstly, the COVID-19 pandemic increased banks' contribution to systemic risk significantly around the world. Secondly, the impact of the COVID-19 virus was more pronounced in developed countries than in emerging economies. Finally, banks with a larger size and higher loan-to-deposit ratio are more greatly affected by the COVID-19 pandemic, while a higher capitalization for banks is insufficient to shelter them from the adverse impact of such pandemic.

The authors assess the impact of the COVID-19 pandemic on banks' contribution to systemic risk. Using the conditional value at risk (marginal expected shortfall) of banks as the measure, this study’s results suggest that banks' contribution to systemic risk increases by around 25% (48%) amid the COVID-19 pandemic. This study’s findings may shed some light on the potential policies that financial regulators may employ to ameliorate the adverse outcomes of the ongoing pandemic.

This chapter investigates the presence of a difference in the systemic risk level between Islamic and conventional banks in Bangladesh. The authors compare systemic resilience of three types of banks: fully fledged Islamic banks, purely conventional banks (CB), and CB with Islamic windows. The authors use the market-based systemic risk measures of marginal expected shortfall and systemic risk to identify which type is more vulnerable to a systemic event. The authors also use ΔCoVaR to identify which type contributes more to a systemic event. Using a sample of observations on 27 publicly traded banks operating over the 2005–2014 period, the authors find that CB is the least resilient sector to a systemic event, and is the one that has the highest contribution to systemic risk during crisis times.

Systemic risk has been a cause of concern for the bank regulatory authorities worldwide since the global financial crisis. This study aims to identify systemically important banks (SIBs) in India by using SRISK to measure the expected capital shortfall of banks in a systemic event. The sample size comprises a balanced data set of 31 listed Indian commercial banks from 2006 to 2019.

In this study, the authors have used SRISK to identify banks that have a maximum contribution to the systemic risk of the Indian banking sector. Leverage, size and long-run marginal expected shortfall (LRMES) are used to compute SRISK. Forward-looking LRMES is computed using the GJR-GARCH-dynamic conditional correlation methodology for early prediction of a bank’s contribution to systemic risk.

This study finds that public sector banks are more vulnerable to macroeconomic shocks owing to their capital inadequacy vis-à-vis the private sector banks. This study also emphasizes that size should not be used as a standalone factor to assess the systemic importance of a bank.

Systemic risk has attracted a lot of research interest; however, it is largely limited to the developed nations. This paper fills an important research gap in banking literature about the identification of SIBs in an emerging economy, India. As SRISK uses both balance sheet and market-based information, it can be used to complement the existing methodology used by the Reserve Bank of India to identify SIBs.

Motivated by the growing importance of the expected shortfall in banking and finance, this study aims to compare the performance of popular non-parametric estimators of the expected shortfall (i.e. different variants of historical, outlier-adjusted and kernel methods) to each other, selected parametric benchmarks and estimates based on the idea of forecast combination.

Within a multidimensional simulation setup (spanned by different distributional settings, sample sizes and confidence levels), the authors rank the estimators based on classic error measures, as well as an innovative performance profile technique, which the authors adapt from the mathematical programming literature.

The rich set of results supports academics and practitioners in the search for an answer to the question of which estimators are preferable under which circumstances. This is because no estimator or combination of estimators ranks first in all considered settings.

To the best of their knowledge, the authors are the first to provide a structured simulation-based comparison of non-parametric expected shortfall estimators, study the effects of estimator averaging and apply the mentioned profiling technique in risk management.

We employ three systemic risk measures of banks, including the systemic risk index (SRISK) and marginal expected shortfall (MES) of Brownlees and Engle (2017) and the conditional Value-at-Risk (ΔCoVaR) of Adrian and Brunnermeier (2016), to analyze bank's exposure and contribution to systemic risk in the banking system when a financial crisis occurs. We find evidence that time-varying systemic risk exists, and systemic risk exposures escalate with the interconnectedness of banks. We also find revenue diversification is another significant factor that reduces a bank's exposure to systemic risk but not for banks in Taiwan and Singapore.

Systemic risk is of concern for economic welfare as it can lower the credit supply to all the sectors within an economy. This study examines for the first time the complete hierarchy of variables that drive systemic risk during normal and crisis periods in Pakistan, a developing economy.

Secondary data of the bank, sector and country variables are used for the purpose of the analysis spanning from 2000 to 2020. Systemic risk is computed using marginal expected shortfall (MES). One-step and two-step system GMM is performed to estimate the impact of firm, sector and country-level variables on systemic risk.

The findings of the study highlight that sector-level variables are also highly significant in explaining the systemic risk dynamics along with bank and country-level variables. In addition, economic sensitivity influences the significance level of variables across crisis and post-crisis periods and modifies the direction of relationships in some instances.

The study examines the systemic risk of a developing economy, and findings may not be generalizable to developed economies.

The outcome of the study provides a comprehensive framework for the central bank and other regulatory authorities that can be translated into timely policies to avoid systemic financial crisis.

The negative externalities generated by systemic risk also affect the general public. The study results can be used to avoid the systemic financial crisis and resultantly save the loss of the general public's hard-earned holdings.

The firm, sector and country-level variables are modeled for the first time to estimate systemic risk across different economic conditions in a developing economy, Pakistan. The study can also act as a reference for researchers in developed economies as well regarding the role of sector-level variables in explaining systemic risk.

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 examine the effects of bank mergers on systemic and systematic risks on the relative merits of product and market diversification strategies. It also observes determinants of M&A deals criteria, product and market diversification positioning, crisis threshold and other regulatory and market factors.

This research examines the impact and association between merger announcements and regulatory reforms at bank and system levels by investigating the impact of various bank consolidation strategies on firms’ risks. We estimate beta(s) as an index of financial institutions’ systematic risk. We then develop an index of the estimated equity value loss as the long-rum marginal expected shortfall (LRMES). LRMES contributes to compute systemic risk (SRISK) contribution of these firms, which is the capital that a firm is expected to need if we have another financial crisis.

Large acquiring banks decrease systemic risk contribution in cross-border M&As with a non-bank financial institution, and witness profitability (ROA) gains, supporting geographic diversification stability. Capital requirements, activity restrictions and bank concentration increase systemic risk contribution in national mergers. Bank mergers with investment FIs targets enhance productivity but impair technical efficiency, contrary to bank-real estate deals where technical efficiency change accompanied lower systemic risk contribution.

Financial institutions are recommended to avoid trapped capital and liquidity by efficiently using local balance sheet and strengthening them via implementing models that clearly set diversification and netting benefits to determine capital reserves and to drive capital efficiency through the clarity on product–activity–geography diversification and focus. This contributes to successful ringfencing, decreases compliance costs and maximises returns and minimises several risks including systemic risk.

Policy implications: the adversative properties of bank mergers in respect of systemic risk require strict and innovative monitoring of bank mergers from the bidding level by both acquirers and targets and regulators and competition supervisory bodies. Moreover, emphasis on regulators/governments intervention and role, as it provides a stabilising factor of the markets and consecutively lower systemic risk even if the systematic idiosyncratic risk contribution was significant. However, such roles have to be well planned and scaled to avoid providing motives for banks to seek too-big-too-fail or too-big-to-discipline status.

This research contributes to the renewing regulatory debate on banks sustainable structures by examining the risk effect of bank diversification versus focus. The authors aim to address the multidimensional impacts and risks inherent to M&A deals, by examining the extent of the interconnectedness of M&A and its implications within and beyond the banking sector.

The authors provide a comprehensive study on systemic risk of the banking sectors in the ASEAN-6 countries. In particular, they investigate the systemic risk dynamics and determinants of 49 listed banks in the region over the 2000–2018 period.

The authors employ the market-based SRISK measure of Brownlees and Engle (2017) to investigate the systemic risk of the ASEAN-6's banking sectors.

The authors find that the regional systemic risk fluctuates significantly and currently at par or higher level than that of the recent global financial crisis. Systemic risk is generally associated with banks that have bigger size, more traditional business models, lower quality in their loan portfolios, less profitable and with lower market-to-book values. However, these relationships vary significantly between ASEAN countries.

The research focuses on the systemic risk of ASEAN-6 countries. Therefore, the research results may lack generalizability to other countries.

The authors’ empirical evidence advocates the use of capital surcharges on the systemically important financial institutions. Although the region has been pushing to higher financial integration in recent years, the authors encourage the regional regulators to account for the idiosyncratic characteristics of their banking sectors in designing effective macroprudential policy to contain systemic risk.

This paper provides the first study on the systemic risk of the ASEAN-6 region. The empirical evidence on the drivers of systemic risk would be of interest to the regional regulators.

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.