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The purpose of this paper is to examine the behavior of banking risk in the emerging economies, particularly Indonesia and contribute to the discussion on the existing policy debate regarding the impact of capital on bank risk.

This study investigates the relationship between bank risk and capital using data on 15 Indonesian large banks between 2008 and 2015, using z-score and Delta-CoVaR to measure both idiosyncratic and systemic risks.

The empirical investigation suggests that capital has a negative and significant relationship with these risk measures. The authors also find that higher systemic risk encourages banks to increase their capital. However, similar evidence is not found in the idiosyncratic risk models. Finally, the role of capital in reducing risk is considered robust only during the normal periods, as banks may increase their assets risk during times of financial distress.

Systemic risk (CoVaR) is used to represent bank risk. This study focuses on the Indonesian banking sector (capture institutional arrangements and regulatory environment). It covers the period of 2008 GFC and post-crisis period.

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.

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.

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.

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 focus on capital-related macroprudential policies in the context of recent policy discussions on the removal of barriers to the mobility of capital and liquidity of cross-border banks in the European Union (EU).

This study first discusses the link between financial stability and internal resource mobility of cross-border banks. Then, it examines past heterogeneity in structural capital buffers as key macroprudential capital instruments applied in the EU and relate them to costs of policy action, degree of foreign penetration and membership in the Banking Union.

Observed phase-in patterns of structural capital buffers in the EU are broadly consistent with costs of policy action, degree of foreign penetration and membership in the Banking Union as potential factors. The process of financial integration could be further enhanced through reduced uncertainty in the application of macroprudential policies that constrain capital mobility of cross-border banks.

This paper anchors macroprudential policies into a wider discussion on the mechanism and implications of ring-fencing in the EU over time. It discusses two policy areas, macroprudential policies and proposals for deeper financial integration, that share the same financial stability objective but tend to emphasize different implications of the mobility of capital and liquidity of cross-border banks in the EU. The study provides a discussion of potential implications of the recent adoption of the CRRII/CRDV legislation for future heterogeneity of macroprudential policies in the EU.

Lessons from the most recent financial crisis show specific vulnerabilities of financial markets due to weaknesses in the structure of the financial system (structural fragility). As the literature points out, the impact of systemic risk can be closely related to issues of concentration (“too big to fail”) and dependency (“too connected to fail”). However, different structural variables are emphasized in various ways, and most authors analyze each variable separately. This raises the questions of how structural fragility, as a cause of systemic distress, can be assessed more comprehensively and consistently, and what the implications are for modeling it within an integrated systemic risk framework. This paper seeks to address these issues.

On the basis of theoretical considerations and in the light of current transformations in financial markets, this paper explores elements of structural fragility and the requirements for modeling them.

The paper suggests an extended approach for conceptualizing structural fragility, evaluates directions for quantifying structural issues in early warning systems (EWSs) for systemic crises, and lays a theoretical groundwork for further empirical studies.

The need for supervisory actions to prevent crises is urgent, as is the need for integrating structural aspects into EWSs for systemic financial crises. Since a significant aspect of a financial firm's risk comes from outside the firm, individual institutions should understand and monitor the structural aspects of the various risk networks they are in.

The paper aims to investigate whether the value of banks is affected by their financing policies. Higher capital requirements have been invoked by exploiting a renewed edition of the Modigliani–Miller (M&M) theorem. This paper shows the limits of this claim by highlighting that the general statement that “bank equity is not expensive” can be misleading. The authors argue that market prices should play an important role in bank supervision. Expectations of future profits in prices supply timely information on the viability of a bank.

The authors use the Merton model to show the inapplicability of M&M theorem to banks. The long-run viability of a bank is analyzed with a dividend discount model which allows to compare a bank’s long-term profitability with its overall cost of capital implicit in market prices.

The authors show that the M&M framework cannot be applied to banks neither ex-ante nor ex-post. Ex-ante the authors focus on government guarantees, ex-post they emphasize the risk-shifting phenomena that may increase the overall risk of the bank. The authors show that a bank’s stability cannot be achieved if the market expectations of its future profits stay below the cost of funding.

The authors use simple analytical models. In a future study, some key peculiarities of banks, such as the monetary nature of deposits, should be analytically modelled.

The paper contributes to the debate on capital regulation on the level of capital requirements and the instruments to assess the viability/stability of banks.

This paper uses simple models to assess analytically the key issues in the debate on banks’ capital regulation.

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 study aims to analyse the systemic risk emitted by all publicly listed commercial banks in a key emerging economy, India.

The study makes use of the Tobias and Brunnermeier (2016) estimator to quantify the systemic risk (ΔCoVaR) that banks contribute to the system. The methodology addresses a classification problem based on the probability that a particular bank will emit high systemic risk or moderate systemic risk. The study applies machine learning models such as logistic regression, random forest (RF), neural networks and gradient boosting machine (GBM) and addresses the issue of imbalanced data sets to investigate bank’s balance sheet features and bank’s stock features which may potentially determine the factors of systemic risk emission.

The study reports that across various performance matrices, the authors find that two specifications are preferred: RF and GBM. The study identifies lag of the estimator of systemic risk, stock beta, stock volatility and return on equity as important features to explain emission of systemic risk.

The findings will help banks and regulators with the key features that can be used to formulate the policy decisions.

This study contributes to the existing literature by suggesting classification algorithms that can be used to model the probability of systemic risk emission in a classification problem setting. Further, the study identifies the features responsible for the likelihood of systemic risk.