Exploiting staggered interstate banking deregulation as exogenous shocks to bank geographic expansion, we examine the causal effect of geographic diversification on systemic risk. Using the gravity-deregulation approach, we find that bank geographic diversification leads to higher systemic risk measured by the change in conditional value at risk (ΔCoVaR) and financial integration (Logistic(R^2)). Furthermore, we document that geographic diversification affects systemic risk via its impact on asset similarity. The impact of geographic diversification on systemic risk is stronger in BHCs located in states comoving less with the U.S. aggregate economy

This paper aims to assess the level of systemic risk of China's financial system along with the main systemic risk contributors over the period from January 2010 to December 2016, a period spanning the deflation of China's property bubble, the banking liquidity crisis, and the stock market crash. To this end we divide the financial system into three sectors, namely: banks, insurance and brokerage industries, and real estate, applying the ΔCoVaR introduced by Adrian and Brunnermeier (2016) as the measure for systemic risk. Our findings show that the systemic risk level of China's financial system reacted to the main systemic events covered by our sample period, reaching a major peak during the stock market crash of 2015. We further show, through the Wilcoxon signed rank test, that the systemic risk level of the financial system and sectors significantly increased after the main systemic events. In order to provide a formal systemic risk ranking of the financial sectors, we apply the bootstrap Kolmogorov-Smirnov test as developed by Abadie (2002), finding that the banking sector contributed the most, followed by real estate and subsequently insurance and brokerage industries. Finally, comparing banks systemic risk's determinants between China and the US, the reduced level of competition among banks in China is found to increase banks’ systemic risk, contrary to what is found in the US

We analyze the relationship between asset price bubbles and systemic risk, using bank-level data covering almost 30 years. Banks’ systemic risk already rises during a bubble’s buildup and even more so during its bust. The increase in risk strongly differs across banks and by bubble. It depends on bank characteristics (especially bank size) and bubble characteristics and can become very large: in a median real estate bust, systemic risk increases by almost 70% of the median for banks with unfavorable characteristics. These results emphasize the importance of bank-level factors in the buildup of financial fragility during bubble episodes

Abundant references to threats to financial stability likely posed by systemic risk-taking in the euro area investment fund industry in an era of persistent low interest rates have not been accompanied by robust supportive empirical evidence. This is the first study that assesses the effects of euro area conventional and unconventional monetary policy shocks on coherent systemic risk measures applied to the investment fund industry. This research finds evidence of systemic risk-taking notably in the forms of contagion and increased vulnerability. It seems more material following conventional than unconventional monetary policy shocks. There is heterogeneity in the results, as the investment focus is important for assessing investment funds’ contribution to systemic risk. Fund types most affected by significant systemic risk-taking are bond funds, mixed funds and real estate funds. Some evidence of heightened vulnerability in equity funds is also present. Increase in leverage is part of the risk-taking mechanism. A key policy implication is that persistently accommodative monetary policy geared toward preserving price stability may face an intertemporal trade-off with financial stability, making it necessary to coordinate monetary and macroprudential policies

Theory suggests that government aid to banks may either reduce or increase systemic risk. We are the first to address this issue empirically, analyzing the Troubled Assets Relief Program (TARP). Analysis suggests that TARP significantly reduced contributions to systemic risk, particularly for larger and safer banks, and those in better local economies. This occurred primarily through a capital cushion channel that reduced market leverage by increasing the value of common equity. Results are robust to endogeneity and selection bias checks. Findings yield policy conclusions about whether to aid banks, the best targets for future assistance, and short-term versus long-term effects

In this paper we develop an in-depth analysis of the systemic risk and contagion determinants through the differential effects of excluding one bank on the banking system. The measure allows for splitting the contribution of individual banks into systemic risk as the sum of two components—the stand-alone bank risk and the contagion risk—and measuring the role of assets, riskiness, capitalization, and interconnectedness as determinants of each of the two components. Results show that the variables determining the stand-alone risk component are different from those determining the contagion risk component, so that a bank which is relatively safe with respect to stand-alone risk, can be an important contagion vehicle, or vice versa. Results also show that crisis severity significantly affects results, so that the severity of different crises results in different weights for the input variables and different contributions for the banks considered. These results add highly significant information for macroprudential regulation, not only from the cross-sectional point of view, but also with reference to the time dimension

We evaluate the performance of two popular systemic risk measures, CoVaR and SRISK, during eight financial panics in the era before FDIC insurance. Bank stock price and balance sheet data were not readily available for this period. We rectify this shortcoming by constructing a novel dataset for the New York banking system before 1933. Our evaluation exercise focuses on two challenges: ranking systemically important financial institutions (SIFIs) and financial crisis prediction. We find that CoVaR and SRISK meet the SIFI ranking challenge. That is, they help identify systemic institutions in periods of distress beyond what is explained by standard risk measures up to six months before panics. In contrast, aggregate CoVaR and SRISK are only somewhat effective at predicting financial crises

Based on the twin sovereign-banking crisis nexus evolution of the Euro debt crisis era, we address the (volatility) mitigation of credit risk, measured by Credit Default Swap spreads (CDS) in both the banking and sovereign sectors within the Eurozone and the US/UK. Secondly, we highlight the volatility interconnectedness or the risk pass-through between sovereign-bank CDS markets with reference to the core vs. periphery EMU. Moreover, we identify the regime states of crises and recovery periods based on the bivariate CDS dynamic correlation series, categorized as the endogenous EMU sovereign risk coherence index. Finally, we investigate the “efficient” (parity) sovereign credit risk pricing during the post-crisis spillover period identified by the CDS and bond markets. We find heterogeneity between markets in pricing the sovereign risk in the regional tier (core-periphery EMU), emphasized by the absence of long-term association. Cointegration results are country-dependent as well as maturity-dependent. Empirical results reject the “no arbitrage” approach

We investigate whether and how the uniqueness of banking activities affects the performance and systemic risk of U.S. banks. We find that banks performing more unique activities exhibit higher profitability and lower risk, controlling for size, diversification, and other key characteristics. We further find that banks’ sensitivity to systemic risk displays an inversely U-shaped relation with activity uniqueness. We interpret the impact of uniqueness in analogy to recent theories showing that systemic diversity promotes financial stability. Our study highlights the role of uniqueness in banking and has important implications for policy makers and banking regulators

To capture systemic risk related to network structures, this paper introduces a measure that complements direct exposures with common exposures, as well as compares these to each other. Trying to address the interconnected nature of financial systems, researchers have recently proposed a range of approaches for assessing network structures. Much of the focus is on direct exposures or market-based estimated networks, yet little attention has been given to the multivariate nature of systemic risk, indirect exposures and overlapping portfolios. In this regard, we rely on correlation network models that tap into the multivariate network structure, as a viable means to assess common exposures and complement direct linkages. Using BIS data, we compare correlation networks with direct exposure networks based upon conventional network measures, as well as we provide an approach to aggregate these two components for a more encompassing measure of interconnectedness