When does low interconnectivity cause systemic risk?

We analysed a systemic liquidity crisis by using a unique money market data-set in which the coded identity of the counterparties of each trade is known. Contrary to recent findings, we did not observe a positive relationship between interconnectivity and systemic risk. We have concluded that our conflicting findings can be related to the degree of market concentration on the borrowing side of the funding market. High level of concentration in the borrowing side led to lower interconnectivity but higher systemic risk prior to the crisis. We conclude that measures of market heterogeneity should be used to generalize the relationship between systemic risk and interconnectivity.     

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.     

A risk assessment model for banks

Summary. This paper proposes a model to assess risk for banks. Its main innovation is to incorporate endogenous interaction among banks, where the actual risk an individual bank bears also depends on its interaction with other banks and investors. We develop a two-period general equilibrium model with three active heterogeneous banks, incomplete markets, and endogenous default. The model is calibrated against UK banking data and therefore can be implemented as a risk assessment tool for regulators and central banks. We address the impact of monetary and regulatory policy, credit and capital shocks in the real and financial sectors.We are grateful to Lea Zicchino, an anonymous referee, seminar participants at the Bank of England, and the third Conference in Research in Economic Theory and Econometrics, Syros, for helpful comments. The views expressed are those of the authors and do not necessarily reflect those of the Bank of England.This revised version was published online in January 2005 with corrections to the Cover date.     

The concentration–stability controversy in banking: New evidence from the EU-25

This study explores whether the concentration–stability relation is affected by the level of analysis; i.e., bank-level versus country-level stability. The diverging results in the literature suggest that we may indeed expect differences between the two levels. With the z-score as the measure of financial stability, our theoretical analysis confirms that we may find such differences. Yet our empirical analysis for the EU-25 during the 1998–2014 period finds no economically significant effect of concentration on either the bank-level or the country-level z-score. The finding that concentration hardly affects stability at both levels of analysis is an indication of robustness in the empirical concentration–stability relation not previously established in the literature. This finding further suggests that neither supervisory restructuring, nor normal market-driven mergers, are likely to be substantially harmful to financial stability.     

Systemic risk and the refinancing ratchet effect

The combination of rising home prices, declining interest rates, and near-frictionless refinancing opportunities can create unintentional synchronization of homeowner leverage, leading to a “ratchet” effect on leverage because homes are indivisible and owner-occupants cannot raise equity to reduce leverage when home prices fall. Our simulation of the U.S. housing market yields potential losses of $1.7 trillion from June 2006 to December 2008 with cash-out refinancing vs. only $330 billion in the absence of cash-out refinancing. The refinancing ratchet effect is a new type of systemic risk in the financial system and does not rely on any dysfunctional behaviors.     

建立和完善农村合作金融治理结构防范化解金融风险

建立和完善农村合作金融治理结构,就是建立决策、执行、监督、激励相结合的内控机制.它主要体现为自我约束的一种自律行为,是为完成既定的工作目标和防范风险,对内部各职能部门及其工作人员从事的业务活动进行风险控制、制度管理和相互制约的方法、措施和程序.对于防范和化解金融风险,保护存款人和其他客户的合法权益,促进农村合作金融健康发展有着重要作用.     

Econometric measures of connectedness and systemic risk in the finance and insurance sectors

We propose several econometric measures of connectedness based on principal-components analysis and Granger-causality networks, and apply them to the monthly returns of hedge funds, banks, broker/dealers, and insurance companies. We find that all four sectors have become highly interrelated over the past decade, likely increasing the level of systemic risk in the finance and insurance industries through a complex and time-varying network of relationships. These measures can also identify and quantify financial crisis periods, and seem to contain predictive power in out-of-sample tests. Our results show an asymmetry in the degree of connectedness among the four sectors, with banks playing a much more important role in transmitting shocks than other financial institutions.     

Assessing financial instability: The case of Brazil

In this paper we use the arbitrage pricing theory to infer the probability of financial institution failure for banks in Brazil. We build an index of financial stability for Brazilian banks. Empirical results seem to provide evidence that after the Russian crisis in 1998, systemic risk has increased in the country but this risk has decreased over time through 2002. Furthermore, for individual major banks the probability of failure has decreased monotonically after the Russian crisis with the adoption of a floating exchange rate regime, an inflation-targeting framework and the introduction of the new payment system.     

How likely is contagion in financial networks?

Interconnections among financial institutions create potential channels for contagion and amplification of shocks to the financial system. We estimate the extent to which interconnections increase expected losses and defaults under a wide range of shock distributions. In contrast to most work on financial networks, we assume only minimal information about network structure and rely instead on information about the individual institutions that are the nodes of the network. The key node-level quantities are asset size, leverage, and a financial connectivity measure given by the fraction of a financial institution’s liabilities held by other financial institutions. We combine these measures to derive explicit bounds on the potential magnitude of network effects on contagion and loss amplification. Spillover effects are most significant when node sizes are heterogeneous and the originating node is highly leveraged and has high financial connectivity. Our results also highlight the importance of mechanisms that go beyond simple spillover effects to magnify shocks; these include bankruptcy costs, and mark-to-market losses resulting from credit quality deterioration or a loss of confidence. We illustrate the results with data on the European banking system.     

Has the financial system become safer after the crisis? The changing nature of financial institution risk

Six years after the collapse of Lehman Brothers, the question of whether the U.S. financial system has become less risky remains unanswered. On the one side, new regulations including Dodd-Frank and Basel III have made improvements by requiring higher bank capital, and financial institutions themselves have reduced risk-taking activities. On the other side, it has been argued that “the fundamental risks remained and the efforts of regulators and politicians were simply rearranging the deckchairs on the Titanic.” (Baily and Elliott, 2013) This paper highlights the changing nature of financial institution risk from 2005 to 2011. It finds that while these institutions have become less risky individually after the crisis, the financial market has become more vulnerable to systemic contagion. The causal inference that the crisis and the post-crisis legislation have gradually changed the nature of financial institution risk is drawn from a quasi-experimental design. This finding suggests that the ever more integrated financial system might experience more synchronized contractions in future crises, providing empirical support for the proposals of the inter-bank collective regulation of banks by Acharya (2009) in addition to the intra-bank collective regulations as in Froot and Stein (1998) and BIS (1996, 1999).     

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.     

The stability–concentration relationship in the Brazilian banking system

In this article, the relation between non-performing loans (NPL) of the Brazilian banking system and macroeconomic factors, systemic risk, and banking concentration is empirically tested. In evaluating this relation, we use a dynamic specification with fixed effects, while using a panel data approach. The empirical results suggest that the banking concentration has a statistically significant impact on NPL, suggesting that more concentrated banking systems may improve financial stability. These results are important for the design of banking regulation policies.     

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.     

Diversification disasters

The recent financial crisis has revealed significant externalities and systemic risks that arise from the interconnectedness of financial intermediaries’ risk portfolios. We develop a model in which the negative externality arises because intermediaries’ actions to diversify that are optimal for individual intermediaries may prove to be suboptimal for society. We show that the externality depends critically on the distributional properties of the risks. The optimal social outcome involves less risk-sharing, but also a lower probability for massive collapses of intermediaries. We derive the exact conditions under which risk-sharing restrictions create a socially preferable outcome. Our analysis has implications for regulation of financial institutions and risk management.     

A computational view of market efficiency

We study market efficiency from a computational viewpoint. Borrowing from theoretical computer science, we define a market to be efficient with respect to resources S (e.g., time, memory) if no strategy using resources S can make a profit. As a first step, we consider memory-m strategies whose action at time t depends only on the m previous observations at times t???m,?…?,?t???1. We introduce and study a simple model of market evolution, where strategies impact the market by their decision to buy or sell. We show that the effect of optimal strategies using memory m can lead to ‘market conditions’ that were not present initially, such as (1) market spikes and (2) the possibility for a strategy using memory m′?>?m to make a bigger profit than was initially possible. We suggest ours as a framework to rationalize the technological arms race of quantitative trading firms.