What is the systemic risk exposure of financial institutions?

I compare the performance of three measures of institution-level systemic risk exposure — Exposure CoVaR (Adrian and Brunnermeier, 2016), systemic expected shortfall (Acharya et al., 2016), and Granger causality (Billio et al., 2012). I modify Exposure CoVaR to allow for forecasting, and estimate the ability of each measure to forecast the performance of financial institutions during systemic crisis periods in 1998 (LTCM) and 2008 (Lehman Brothers). I find that Exposure CoVaR forecasts the within-crisis performance of financial institutions, and provides useful forecasts of future systemic risk exposures. Systemic expected shortfall and Granger causality do not forecast the performance of financial institutions reliably during crises. I also find, using cross-sectional regressions, that foreign equity exposure and securitization income determine systemic risk exposure during the 1998 and 2008 crises, respectively; financial institution size determines systemic risk exposure during both crisis periods; and executive compensation does not determine systemic risk exposure.     

Deposit insurance around the world: A comprehensive analysis and database

This paper provides a comprehensive, global database of deposit insurance arrangements as of 2013. We extend our earlier dataset by including recent adopters of deposit insurance and information on the use of government guarantees on banks’ assets and liabilities, including during the recent global financial crisis. We also create a Safety Net Index capturing the generosity of the deposit insurance scheme and government guarantees on banks’ balance sheets. The data show that deposit insurance has become more widespread and more extensive in coverage since the global financial crisis, which also triggered a temporary increase in the government protection of non-deposit liabilities and bank assets. In most cases, these guarantees have since been formally removed but coverage of deposit insurance remains above pre-crisis levels, raising concerns about implicit coverage and moral hazard going forward.     

A comprehensive approach to measuring the relation between systemic risk exposure and sovereign debt

Using an integrated model to control for simultaneity, as well as new risk measurement techniques such as Adapted Exposure CoVaR and Marginal Expected Shortfall (MES), we show that the aggregate systemic risk exposure of financial institutions is positively related to sovereign debt yields in European countries in an episodic manner, varying positively with the intensity of the financial crisis facing a particular nation. We find evidence of a simultaneous relation between systemic risk exposure and sovereign debt yields. This suggests that models of sovereign debt yields should also include the systemic risk of a country's financial system in order to avoid potentially important mis-specification errors. We find evidence that systemic risk of a country's financial institutions and the risk of sovereign governments are inter-related and shocks to these domestic linkages are stronger and longer lasting than international risk spillovers. Thus, the channel in which domestic sovereign debt yields can be affected by another nation's sovereign debt is mostly an indirect one in that shocks to a foreign country's government finances are transmitted to that country's financial system which, in turn, can spill over to the domestic financial system and, ultimately, have a destabilizing effect on the domestic sovereign debt market.     

The contribution of (shadow) banks and real estate to systemic risk in China

We empirically evaluate how accounting and financial variables affect the level of systemic risk in traditional and shadow banks, and in real estate finance services in China over the period 2006–2019. We also conduct some stability analysis by evaluating the impact of crisis sub-periods. We find that systemic risk increases in the Size of large financial institutions, particularly shadow entities, while it is insensitive to the Size of real estate finance services. Real estate finance services are instead particularly sensitive to Maturity Mismatch and Leverage. Finally, systemic risk differs across state and non state owned banks.     

Can CoCo-bonds mitigate systemic risk?

After the 2008 financial crisis, the idea of contingent convertible (CoCo) capital was revived as a means to stabilize individual banks, and hence the entire banking system. The purpose of this paper is to empirically test, whether CoCo-bonds indeed improve the stability of the banking system and reduce systemic risk. Using the broadly applied SRISK metric, we obtain contradicting results, which are based on the accounting of the CoCo-bond as debt or equity. This observation is problematic, as CoCo-bonds generally increase the loss-absorbing capacity of a bank. We remedy this shortcoming by proposing an adjustment to the original SRISK formula. Using empirical tests, we show that the undue disparity has been solved by our adjustment, and that CoCo-bonds reduce systemic risk, irrespective of their accounting. Our results are robust to different parametrizations and accounting standards, as well as issuance effects.     

An analysis of the literature on systemic financial risk: A survey

This article presents an analysis of the literature on systemic financial risk. To that end, we analyze and classify 266 articles that were published no later than September 2016 in the databases Scopus and Web of Knowledge; these articles were identified using the keywords “systemic risk”, “financial stability”, “financial”, “measure”, “indicator”, and “index”. They were evaluated based on 10 categories, namely, type of study, type of approach, object of study, method, spatial scope, temporal scope, context, focus, type of data used, and results. The analysis and classification of this literature made it possible to identify the remaining gaps in the literature on systemic risk; this contributes to a future research agenda on the topic. Moreover, the most influential articles in this field of research and the articles that compose the mainstream research on systemic financial risk were identified.     

Financial stress transmission between the U.S. and the Euro Area

This paper examines financial stress transmission between the U.S. and the Euro Area. To better understand the linkages between financial stress in the two regions, we construct a financial stress index for the U.S. similar to the Composite Indicators of Systemic Stress (CISS) that has been developed for the Euro Area with a focus on systemic risk. Using weekly data from 2000 to 2021 and Granger predictability in distribution test, we analyze stress transmission in “normal” times as well as under unusually high and low stress episodes. While we document unilateral transmission from the U.S. to the Euro Area under normal conditions based on the center of the distribution, tail dependence tests and impulse response analysis show significant bilateral transmission, particularly in unusually high financial stress episodes. This holds true for aggregate indices as well as the subindicators of financial stress in various financial markets. As such, there must be global efforts to contain financial crises and ensure a strong and resilient financial system.     

Fragility,stress, and market returns

We propose a novel risk measure that relates to subsequent negative conditional stock market returns. Our risk measure considers both the fragility and stress of the market. Fragility is measured by the Fragility Index developed by Berger and Pukthuanthong (2012) and market stress is based on several economic variables. Results show that incorporating both market stress and fragility improves the information content of a risk measure. Our risk measure relates to poor subsequent monthly market returns. We show the risk measure contains predictive information in a purely ex-ante specification.     

Market procyclicality and systemic risk

We develop a model that captures, at the same time, the temporal dynamics of single-firm credit risk and the contagion across banks via a network of obligations and common assets. In particular, we enrich the continuous-time modelling approach of default by accounting explicitly for the procyclical loop between asset prices and leverage. Contagion can spread well before any default occurs, through the value of the obligations held by counterparties. Moreover, the extent of procyclicality effects depends explicitly on the structure of both the interbank network and the asset bank network. We analyse the model in a simplified scenario of a densely connected core of banks and we carry out a systematic investigation of how procyclicality emerges from the multiplicative interplay of market illiquidity and tightness of capital requirements.     

Tail dependence and indicators of systemic risk for large US depositories

In this study, we investigate the extreme loss tail dependence between stock returns of large US depository institutions. We find that stock returns exhibit strong loss dependence even in their limiting joint extremes. Motivated by this result, we derive extremal dependence-based systemic risk indicators. The proposed systemic risk indicators reflect downturns in the US financial industry very well. We also develop a set of firm-level average extremal dependence measures. We show that these firm-level measures could have been used to identify the firms that were more vulnerable to the 2007–2008 financial crisis. Additionally, we explore the performance of selected systemic risk indicators in predicting the crisis performance of large US depository institutions and find that the average stock return correlations are also good predictors of crisis period returns. Finally, we identify factors predictive of extremal dependence for the US depository institutions in a panel regression setting. Strength of extremal dependence increases with asset size and similarity of financial fundamentals. On the other hand, strength of extremal dependence decreases with capitalization, liquidity, funding stability and asset quality. We believe the proposed indicators have the potential to inform the prudential supervision of systemic risk.     

Assessing the contribution of banks,insurance and other financial services to systemic risk

The aim of this paper is to contribute to the debate on systemic risk by assessing the extent to which distress within the main different financial sectors, namely, the banking, insurance and other financial services industries contribute to systemic risk. To this end, we rely on the $\mathrm{\Delta }\mathit{CoVaR}$ systemic risk measure introduced by Adrian and Brunnermeier (2011). In order to provide a formal ranking of the financial sectors with respect to their contribution to systemic risk, the original $\mathrm{\Delta }\mathit{CoVaR}$ approach is extended here to include the Kolmogorov–Smirnov test developed by Abadie (2002), based on bootstrapping. Our empirical results reveal that in the Eurozone, for the period ranging from 2004 to 2012, the other financial services sector contributes relatively the most to systemic risk at times of distress affecting this sector. In turn, the banking sector appears to contribute more to systemic risk than the insurance sector. By contrast, the insurance industry is the systemically riskiest financial sector in the United States for the same period, while the banking sector contributes the least to systemic risk in this area. Beyond this ranking, the three financial sectors of interest are found to contribute significantly to systemic risk, both in the Eurozone and in the United States.     

Good for one,bad for all: Determinants of individual versus systemic risk

We analyze a sample of large international banks in major advanced economies and examine the impact that bank-specific factors have on an institution's solvency risk and its contribution to systemic risk. We focus on the five categories that the Basel Committee on Banking Supervision has recently proposed as indicators of systemic importance. Our findings suggest that unstable funding is the main factor driving systemic risk. Furthermore, the combination of significant trading activities with global presence appears to exacerbate spillover risks to the global financial system. Interestingly, whereas trading activities contribute to the build-up of correlated or ‘wrong-way’ risk they help to mitigate individual solvency risk. Conversely, a decentralized approach to liquidity management seems to alleviate individual solvency risk but amplifies the transmission of financial distress across the financial system. This suggests that a macro-prudential approach to financial regulation should focus not only on scaling up micro-prudential measures but also on enabling the efficient transfer of risk between financial institutions.     

From me to you: Measuring connectedness between Eurozone financial institutions

This paper aims to analyse the tail risk spillover between banks, insurance companies and the shadow banking system in the Eurozone contest. These intra-sectoral interdependencies between financial market participants have contributed to the spread of instability in the financial system. Therefore mapping these links is important for policy-makers to provide supervisory tools and can be a key input into the design of macroprudential policies. For this purpose, we adopt the Tail-Event driven NETwork (TENET) risk model. The TENET is a useful method to map the tail interconnection between the three sectors and to provide systemic risk measures that take into account the “too big to fail” and “too big to interconnected” concepts. The results suggest that each financial sector has a significant impact on the other. By comparing the contribution of each sector, we show that banks are the largest emitters of risk. However, also shadow banking firms are systemic important, given their high level of connection. The work provides a clear view of risk spillovers and interconnection dynamics during the crisis providing a meaningful ranking of the systemic important financial institutions.     

Optimal regulation,executive compensation and risk taking by financial institutions

We present an equilibrium model of financial institutions to examine the optimal regulation of risk taking. Shareholders provide incentives for management to increase risk to excessive levels. Regulators use caps on asset risk and compensation to achieve the socially optimal risk level. This level trades off costs of risk shifting and costs of bank default. Without regulation, equilibrium risk lies above the optimal level. If information and enforcement are perfect, either policy tool (caps on asset risk or compensation) achieves the optimal risk level. If there are frictions – if enforcement is limited, if there is uncertainty about the incentives facing management and costs of risk shifting, or if regulation cannot be bank specific – welfare can be improved by employing both policy tools.     

Liquidity risk and policy options

On the basis of a liquidity management model, liquidity risks, defined as the probability of payment failures in a real-time gross settlement (RTGS) payment system, may either stem from liquidity management inefficiencies or insufficient cash balances. I will show that penalties charged on the amount of payment failures minimise liquidity risks without interfering with the bank’s technology preferences. I will instead show that liquidity requirements, although as effective as penalties to contain the risk of liquidity shortage, may distort the bank’s technology preferences and cannot stem liquidity management inefficiencies. I will also show that liquidity risks within RTGS payment systems are potentially smaller because they depend more on the liquidity management efficiency than on the randomness of cash inflows and outflows.     

Optimal equity infusions in interbank networks

We study optimal equity infusions into a financial network prone to the risk of contagious failures, which may be due to insolvency or to bank runs by short term creditors. Bank runs can be triggered by failures of connected banks.Under complete information on interbank linkages, we show that the problem reduces to a combinatorial optimization problem. Subject to budget constraints, the government chooses the set of minimal cost whose survival induces the maximum network stability. Our results demonstrate that the optimal equity infusion might significantly mitigate failure contagion risk and stabilize the system. In the case of partial information on the network, the controllers’ focus swiftly changes from preventing insolvencies to preventing runs by short term creditors.     

Multilayer networks in the frequency domain: Measuring extreme risk connectedness of Chinese financial institutions

We propose multilayer networks in the frequency domain, including the short-term, medium-term, and long-term layers, to investigate the extreme risk connectedness among financial institutions. Using the conditional autoregressive value at risk (CAViaR) tool to measure the extreme risk of financial institutions, we construct extreme risk networks and inter-sector extreme risk networks of 36 Chinese financial institutions through the proposed approach. We observe that the extreme risk connectedness across financial institutions is heterogeneous in the short-, medium-, and long-term. In general, the long-term connectedness among financial institutions rises sharply during times of financial stress, such as the 2015 Chinese stock market turbulence and the 2020 COVID-19 pandemic. Moreover, we note that the insurers are key players in driving the inter-sector extreme risk networks, because the inter-sector systemic importance of insurance institutions is dominant. Finally, our conclusions provide valuable information for regulators to prevent systemic risk.