Leverage-induced systemic risk under Basle II and other credit risk policies

We use a simple agent based model of value investors in financial markets to test three credit regulation policies. The first is the unregulated case, which only imposes limits on maximum leverage. The second is Basle II and the third is a hypothetical alternative in which banks perfectly hedge all of their leverage-induced risk with options. When compared to the unregulated case both Basle II and the perfect hedge policy reduce the risk of default when leverage is low but increase it when leverage is high. This is because both regulation policies increase the amount of synchronized buying and selling needed to achieve deleveraging, which can destabilize the market. None of these policies are optimal for everyone: risk neutral investors prefer the unregulated case with low maximum leverage, banks prefer the perfect hedge policy, and fund managers prefer the unregulated case with high maximum leverage. No one prefers Basle II.     

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.     

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.     

Leverage,balance-sheet size and wholesale funding

Positive co-movements in bank leverage and assets are associated with leverage procyclicality. As wholesale funding allows banks to quickly adjust leverage, banks with wholesale funding are expected to exhibit higher leverage procyclicality. Using Canadian data, we analyze (i) if leverage procyclicality exists and its dependence on wholesale funding, (ii) market factors associated with this procyclicality, and (iii) if banking-sector leverage procyclicality forecasts market volatility. The findings suggest that procyclicality exists and that its degree positively depends on use of wholesale funding. Furthermore, funding-market liquidity matters for this procyclicality. Finally, banking-sector leverage procyclicality can forecast volatility in the equity market.     

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.     

The multi-layer network nature of systemic risk and its implications for the costs of financial crises

The inability to see and quantify systemic financial risk comes at an immense social cost. Systemic risk in the financial system arises to a large extent as a consequence of the interconnectedness of its institutions, which are linked through networks of different types of financial contracts, such as credit, derivatives, foreign exchange, and securities. The interplay of the various exposure networks can be represented as layers in a financial multi-layer network. In this work we quantify the daily contributions to systemic risk from four layers of the Mexican banking system from 2007 to 2013. We show that focusing on a single layer underestimates the total systemic risk by up to 90%. By assigning systemic risk levels to individual banks we study the systemic risk profile of the Mexican banking system on all market layers. This profile can be used to quantify systemic risk on a national level in terms of nation-wide expected systemic losses. We show that market-based systemic risk indicators systematically underestimate expected systemic losses. We find that expected systemic losses are up to a factor of four higher now than before the financial crisis of 2007–2008. We find that systemic risk contributions of individual transactions can be up to a factor of one thousand higher than the corresponding credit risk, which creates huge risks for the public. We find an intriguing non-linear effect whereby the sum of systemic risk of all layers underestimates the total risk. The method presented here is the first objective data-driven quantification of systemic risk on national scales that reveal its true levels.     

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.     

Double leverage cycle,interest rate,and financial crisis

We view mortgage as a risky derivative of its underlying house collateral and combine no-arbitrage valuation with equilibrium valuation approaches to develop a dynamic model of leverage cycle and interest rate. This model provides a unified explanation to pro-cyclical optimism, asset prices, and leverage, and counter-cyclical volatility and interest rate. In addition, the model shows that tightening funding margin in the mortgage securities market dampens optimism, asset prices, and leverage, whereas it raises volatility and interest rate in the housing market. A double leverage cycle leads to more volatile markets and a severe leverage cycle, thus resulting in worse financial crises.     

监测系统性金融风险——中国金融市场压力指数构建和状态识别

对系统性金融风险进行识别和评估,日益成为各国中央银行的核心关切。囿于数据频率,基于金融机构经营稳健性评估的金融系统性风险监测存在一定的滞后性,不利于中央银行及时进行风险应对,利用金融市场交易数据进行风险监测可极大程度克服滞后性问题。本文根据中国金融市场特点,选取债券市场、股票市场、货币市场和外汇市场17个有代表性的指标,运用经验累积分布函数法分别构造了各子市场的压力指数,以各子市场之间时变的相关关系刻画系统性金融风险的跨市场传染特征,合成金融市场压力指数,并通过建立马尔可夫区制转换模型,对金融市场压力状态进行识别。金融市场压力指数能有效反映样本域内的压力事件,并兼具稳健性、能逐日监测等优点,为监测评估系统性金融风险、选择政策实施窗口和评估政策实施效果等提供了有力工具。     

Elimination of systemic risk in financial networks by means of a systemic risk transaction tax

Financial markets are exposed to systemic risk (SR), the risk that a major fraction of the system ceases to function, and collapses. It has recently become possible to quantify SR in terms of underlying financial networks where nodes represent financial institutions, and links capture the size and maturity of assets (loans), liabilities and other obligations, such as derivatives. We demonstrate that it is possible to quantify the share of SR that individual liabilities within a financial network contribute to the overall SR. We use empirical data of nationwide interbank liabilities to show that the marginal contribution to overall SR of liabilities for a given size varies by a factor of a thousand. We propose a tax on individual transactions that is proportional to their marginal contribution to overall SR. If a transaction does not increase SR, it is tax-free. With an agent-based model (ABM) (CRISIS macro-financial model), we demonstrate that the proposed ‘Systemic Risk Tax’ (SRT) leads to a self-organized restructuring of financial networks that are practically free of SR. The SRT can be seen as an insurance for the public against costs arising from cascading failure. ABM predictions are shown to be in remarkable agreement with the empirical data and can be used to understand the relation of credit risk and SR.     

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.     

金融体系杠杆形成机制和管控建议

2008年国际金融危机的一个深刻教训是金融杠杆的过犹不及。本文在金融杠杆概 念及相关文献综述的基础上,对我国金融部门杠杆率进行了多角度的测算,并分析金融过度杠 杆化的形成机制,梳理当前已采取的金融去杠杆措施,总结值得关注的问题,为下一步管控金 融杠杆、稳住宏观杠杆提供参考。     

Measuring systemic importance of financial institutions: An extreme value theory approach

This paper proposes a set of market-based measures on the systemic importance of a financial institution or a group of financial institutions, each designed to capture different aspects of systemic importance of financial institutions. Multivariate extreme value theory approach is used to estimate these measures. Using six big Canadian banks as the proxy for Canadian banking sector, we apply these measures to identify systemically important banks in Canadian banking sector and major risk contributors from international financial institutions to Canadian banking sector. The empirical evidence reveals that (i) the top three banks, RBC Financial Group, TD Bank Financial Group, and Scotiabank, are more systemically important than other banks, while we also find that the size of a financial institution should not be considered as a proxy of systemic importance; (ii) compared to the European and Asian banks, the crashes of the U.S. banks, on average, are the most damaging to Canadian banking sector, while the risk contribution to the Canadian banking sector from Asian banks is quite lower than that from banks in the U.S. and euro area; (iii) the risk contribution to Canadian banking sector exhibits “home bias”, that is, cross-country risk contribution tends to be smaller than domestic risk contribution.     

储蓄率与杠杆率:一个U型关系

近年来,中国呈现典型的“高储蓄—高杠杆”特征,高储蓄率也被认为是中国杠杆率偏高的主要原因之一。能否通过降低储蓄率的方式来去杠杆成为了广泛讨论的问题。为此,本文构建了一个含有融资约束的动态宏观模型,研究了储蓄率对杠杆率的影响机理。并且,基于41个代表性经济体1966-2017年的面板数据,对储蓄率与杠杆率之间的关系进行了实证分析,主要有两点研究发现:(1)虽然高储蓄率会导致高杠杆率,但是储蓄率与杠杆率不是简单的正相关关系,而是呈现显著的U型关系。结合测算的U型曲线拐点值与中国实际情况,预计储蓄率下降在降低杠杆率方面的作用效果有限。(2)高杠杆下,较高的储蓄率可以有效降低发生金融危机的概率,而储蓄率下降则会加大发生金融危机的概率。基于此,本文认为中国不能通过降低储蓄率的方式来降低杠杆率,反而需要对近年来储蓄率下滑的现象予以高度重视,从而更好地守住不发生系统性金融风险的底线。     

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.     

European systemic credit risk transmission using Bayesian networks

The analysis of systemic credit risk is one of the most important concerns within the financial system. Its complexity lies in adequately measuring how the transmission of systemic default spreads through assets or financial markets. The transmission structure of systemic credit risk across several European sectoral CDS is studied by dynamic Bayesian networks. The new approach allows for a more advanced analysis of systemic risk transmission, including long-term and more complex relationships. The modelling reveals as relevant only relationships between the original series and one- and two-lagged series. Network structure learning displays a robust and stationary underlying risk transmission structure, pointing to a consolidated transmission mechanism of systemic credit risk between CDSs. Between 5 % and 40 % of sectoral CDS series variances are explained by the network relationships. The modelling allows us to ascertain which relationships between the CDS series show positive (amplifier) and negative (reducer) effects of systemic risk transmission.     

Systemic risk in an interconnected banking system with endogenous asset markets

We analyze the emergence of systemic risk in a network model of interconnected bank balance sheets. The model incorporates multiple sources of systemic risk, including size of financial institutions, direct exposure from interbank lendings, and asset fire sales. We suggest a new macroprudential risk management approach building on a system wide value at risk (SVaR). Under the SVaR metric, the contribution of individual banks to systemic risk is well defined and can be approximated by a Shapley value-type measure. We show that, in a SVaR regime, a fair systemic risk charge which is proportional to a bank's individual contribution to systemic risk diverges from the optimal macroprudential capitalization of the banks from a planner's perspective. The results have implications for the design of macroprudential capital surcharges.     

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).     

宏观审慎政策的理论与实践进展

金融危机爆发后,宏观审慎政策成为金融监管与宏观经济调控模式改革的核心。尽管关于宏观审慎政策框架中很多问题的研究还远未达成共识,但无论在理论还是实践层面均已经积累了大量的研究成果与实践经验有待深入总结。依照宏观审慎政策理论与实践发展的逻辑脉络,本文一方面将对宏观审慎政策在其目标、工具、有效性、作用机制等方面的已有研究进行梳理和总结;另一方面,也将对国内外宏观审慎政策的实践进展进行简要综述。同时,结合构建我国宏观审慎政策框架的目标,本文将在综述的基础上,提出对我国宏观审慎政策的理解及未来宏观审慎政策理论与实践上有待深入探索的主题。