The formation of financial networks

Modern banking systems are highly interconnected. Despite various benefits, linkages between banks carry the risk of contagion. In this article, I investigate whether banks can commit ex ante to mutually insure each other, when there is contagion risk in the financial system. I model banks' decisions to share this risk through bilateral agreements. A financial network that allows losses to be shared among various counterparties arises endogenously. I characterize the probability of systemic risk, defined as the event that contagion occurs conditional on one bank failing, in equilibrium interbank networks. I show that there exist equilibria in which contagion does not occur.     

Assessing systemic risk using interbank exposures in the global banking system

This paper contributes to the literature on systemic risk by examining the network structure of bilateral exposures in the global banking system. The global interbank market constitutes a major part of the global banking system. The market has a hierarchical network structure, composed of the national or jurisdictional area's local markets and the cross-border interbank market. First, we estimate the bilateral exposures matrix using aggregate financial data on loans and deposits from Bankscope and analyze the interconnectedness in the market using network centrality measures. Subsequently, for the model analysis, we apply the Eisenberg–Noe framework to a multi-period setting. In this framework, bank defaults are classified into stand-alone defaults and contagious defaults. The banks in our sample (i.e., the top 202 banks with more than $50 billion in total assets) comprise a major part of this global banking system. The main findings are as follows: The theoretical network analysis using network centrality measures showed that most of the banks designated as global systemically important banks (G-SIBs) play a central role in the global interbank market. The theoretical default analysis showed a few contagious defaults triggered by the basic defaults during and after the global financial crisis. Our stress test proved that many G-SIBs theoretically caused 1–6 contagious defaults. Our methodology would assist in the development of a monitoring system by the respective supervisory authorities as well as in the implementation of bank-internal stress tests of default contagion.     

基于共同冲击和异质风险叠加传导的风险传染研究——来自中国上市银行网络的传染模拟

本文将银行系统遭遇外部共同冲击作为研究起点,建立了一个共同冲击和异质风险交互传导与放大的简化模型,冲击的传导包括“原始冲击”、“增量冲击”和“违约冲击”三个风险传染阶段。基于2018年我国15家上市银行的股票收益率和年报数据、2006年至2018年的银行评级数据,本文构建了贝叶斯分层图模型和银行间拆借矩阵,并利用蒙特卡洛模拟测度不同触发银行所引发的系统性风险损失、单个银行的系统性风险杠杆能力(文中定义为“传染乘数”指标)以及政府监管介入的效果。模拟结果显示:共同冲击损失远大于异质风险损失;规模和网络关联性是决定传染乘数的重要因素,且当规模因素不突出时,网络关联性对传染乘数的决定作用相对更强,极容易出现小规模、高关联性银行具有较高的传染乘数;当银行风险资产损失率在10%至25%之间时,造成系统性风险损失的杠杆能力普遍增强;政府监管介入能较好地降低系统性风险。本研究的相关结论为系统性风险的监管设计提供经验证据和参考。     

Modelling Deposit Insurance Scheme Losses in a Basel 2 Framework

This paper extends the existing literature on deposit insurance by proposing a new approach for the estimation of the loss distribution of a Deposit Insurance Scheme (DIS) that is based on the Basel 2 regulatory framework. In particular, we generate the distribution of banks’ losses following the Basel 2 theoretical approach and focus on the part of this distribution that is not covered by capital (tail risk). We also refine our approach by considering two major sources of systemic risks: the correlation between banks’ assets and interbank lending contagion. The application of our model to 2007 data for a sample of Italian banks shows that the target size of the Italian deposit insurance system covers up to 98.96% of its potential losses. Furthermore, it emerges that the introduction of bank contagion via the interbank lending market could lead to the collapse of the entire Italian banking system. Our analysis points out that the existing Italian deposit insurance system can be assessed as adequate only in normal times and not in bad market conditions with substantial contagion between banks. Overall, we argue that policy makers should explicitly consider the following when estimating DIS loss distributions: first, the regulatory framework within which banks operate such as (Basel 2) capital requirements; and, second, potential sources of systemic risk such as the correlation between banks’ assets and the risk of interbank contagion.     

Interbank contagion and resolution procedures: inspecting the mechanism

This paper develops a network model of a stylized banking system in which banks are connected to one another through interbank claims, which allows us to study the diffusion of default avalanches triggered by an exogenous shock under a number of different assumptions on the degree of interconnectedness, level of capitalization, liquidity buffers, the size of the interbank market and fire-sales. We expand upon the existing literature by comparing two alternative resolution mechanisms: (i) liquidations triggered by either illiquidity or insolvency-related distress implying asset sales and compensation of creditors; and (ii) a bail-in mechanism avoiding bank closure by forcing a recapitalization provided by bank creditors. Our model speaks to how contagion dynamics unravel via illiquidity-driven defaults in the first case and higher-order losses in the latter one. Within this framework, we show how the liquidity risk externality can be resolved, and we put forward a macro-criterion to assess the adequacy of the liquidity ratio introduced with Basel III.     

Assessing financial contagion in the interbank market: Maximum entropy versus observed interbank lending patterns

Interbank markets allow banks to cope with specific liquidity shocks. At the same time, they may represent a channel for contagion as a bank default may spread to other banks through interbank linkages. This paper analyses how contagion propagates within the Italian interbank market using a unique data set including actual bilateral exposures. Based on the availability of information on actual bilateral exposures for all Italian banks, the results obtained by assuming the maximum entropy are compared with those reflecting the observed structure of interbank claims. The comparison indicates that, under certain circumstances, depending on the structure of the interbank linkages, the recovery rates of interbank exposures and banks’ capitalisation, the maximum entropy approach overrates the scope for contagion.     

Modelling the emergence of the interbank networks

Interbank contagion has become a buzzword in the aftermath of the financial crisis that led to a series of shocks to the interbank market and to periods of pronounced market disruptions. However, little is known about how interbank networks are formed and about their sensitivity to changes in key bank parameters (for example, induced by common exogenous shocks or by regulatory initiatives). This paper aims to shed light on these issues by modelling endogenously the formation of interbank networks, which in turn allows for checking the sensitivity of interbank network structures and hence, their underlying contagion risk to changes in market-driven parameters as well as to changes in regulatory measures such as large exposures limits. The sequential network formation mechanism presented in the paper is based on a portfolio optimization model, whereby banks allocate their interbank exposures while balancing the return and risk of counterparty default risk and the placements are accepted taking into account funding diversification benefits. The model offers some interesting insights into how key parameters may affect interbank network structures and can be a valuable tool for analysing the impact of various regulatory policy measures relating to banks’ incentives to operate in the interbank market.     

Contagion in the interbank market and its determinants

Carrying out interbank contagion simulations for the German banking sector for the period from the first quarter of 2008 to the second quarter of 2011, we obtain the following results: (i) The system becomes less vulnerable to direct interbank contagion over time. (ii) The loss distribution for each point in time can be condensed into one indicator, the expected number of failures, without much loss of information. (iii) Important determinants of this indicator are the banks’ capital, their interbank lending in the system, the loss given default and how equal banks spread their claims among other banks.     

Using extreme value theory to estimate the likelihood of banking sector failure

Abstract

The growing interest in management of credit risk and estimation of default probabilities has given rise to a range of more or less elaborate credit risk models. While these models work well for non-financial firms they are usually not very successful in capturing the financial strength of banks. As an answer to this, Hall and Miles suggest a simple approach of estimating bank failure probabilities based solely on their stock prices. This paper suggests an extension to the Hall and Miles model using extreme value theory and applies the extended model to the Swedish banking sector around the banking crisis of the early 1990s. The extended model captures very well the increased likelihood of a systemic banking sector failure around the peak of the crisis and it produces default probabilities that are more stable, more realistic and more consistent with Moody’s and Fitch rating implied default rates than probabilities from the original Hall and Miles model.     

Interbank Credit Lines as a Channel of Contagion

This paper assesses the potential for contagion in the Swiss interbank market using new data on bilateral bank exposures as well as on credit lines. A simulation approach is applied to assess the banking system's inherent instability. Moreover, the spill-over effects of a simulated default situation in the interbank market on the liquidity and solvency of banks are measured. The main findings are, first, that there is a substantial potential for contagion. Second, the exposure as well as the credit line contagion channel are relevant for Switzerland. Third, a lender of last resort intervention could reduce spill-over effects remarkably. Finally, the structure of the interbank market has considerable impact on its resilience against spill-over effects: Centralized markets are more prone to contagion than homogenous ones. JEL classification: C81, G21. The opinions expressed herein are my own and not those of the Swiss National Bank.     

Banking systemic vulnerabilities: A tail-risk dynamic CIMDO approach

This study proposes a novel framework which combines marginal probabilities of default estimated from a structural credit risk model with the consistent information multivariate density optimization (CIMDO) methodology and the generalized dynamic factor model (GDFM) supplemented by a dynamic t-copula. The framework models banks’ default dependence explicitly and captures the time-varying non-linearities and feedback effects typical of financial markets. It measures banking systemic credit risk in the three forms categorized by the European Central Bank: (1) credit risk common to all banks; (2) credit risk in the banking system conditional on distress on a specific bank or combinations of banks; and (3) the buildup of banking system vulnerabilities over time which may unravel disorderly. In addition, the estimates of the common components of the banking sector short-term and conditional forward default measures contain early warning features, and the identification of their drivers is useful for macroprudential policy. Finally, the framework produces robust out-of-sample forecasts of the banking systemic credit risk measures. This paper advances the agenda of making macroprudential policy operational.     

Systemic Bank Risk in Brazil: A Comprehensive Simulation of Correlated Market, Credit, Sovereign and Inter-Bank Risks

In this study we present a comprehensive forward‐looking portfolio simulation methodology for assessing the correlated impacts of market risk, private sector and Sovereign credit risk, and inter‐bank default risk. In order to produce better integrated risk assessment for banks and systemic risk assessments for financial systems, we argue that reasonably detailed modeling of bank asset and liability structures, loan portfolio credit quality, and loan concentrations by sector, region and type, as well as a number of financial and economic environment risk drivers, is required. Sovereign and inter‐bank default risks are increasingly important in the current economic environment and their inclusion is an important model extension. This extended model is demonstrated through an application to both individual Brazilian banks (i.e., 28 of the largest banks) and groups of banks (i.e., the Brazilian banking system) as of December 2004. When omitting Sovereign risk, our analysis indicates that none of the banks face significant default risk over a 1‐year horizon. This low default risk stems primarily from the large amount of government securities held by Brazilian banks, but also reflects the banks' adequate capitalizations and extraordinarily high interest rate spreads. We note that none of the banks which we modeled failed during the very stressful 2007‐2008 period, consistent with our results. Our results also show that a commonly used approach of aggregating all banks into one single bank, for purposes of undertaking a systemic banking system risk assessment, results in a misestimate of both the probability and the cost of systemic banking system failures. Once Sovereign risk is considered and losses in the market value of government securities reach 10% (or higher), we find that several banks could fail during the same time period. These results demonstrate the well known risk of concentrated lending to a borrower, or type of borrower, which has a non‐zero probability of default (e.g., the Government of Brazil). Our analysis also indicates that, in the event of a Sovereign default, the Government of Brazil would face constrained debt management alternatives. To the best of our knowledge no one else has put forward a systematic methodology for assessing bank asset, liability, loan portfolio structure and correlated market and credit (private sector, Sovereign, and inter‐bank) default risk for banks and banking systems. We conclude that such forward‐looking risk assessment methodologies for assessing multiple correlated risks, combined with the targeted collection of specific types of data on bank portfolios, have the potential to better quantify overall bank and banking system risk levels, which can assist bank management, bank regulators, Sovereigns, rating agencies, and investors to make better informed and proactive risk management and investment decisions.     

商业银行流动性危机传染机理研究

银行危机传染往往给一个国家或地区的经济带来巨大的损失.不完全的银行间拆借市场中隐含了更大的银行危机传染的可能性;银行间的长期资产越多,银行间拆借的短期利率和银行间存款的长期利率越高,银行间拆借市场就越稳定,在遭受流动性冲击时,这一市场发生银行危机传染的可能性就越小.适量的银行存款对传染效应具有阻碍作用.为防范系统性风险,中国商业银行应逐步建立完备的银行间存款市场,减少政府干预,让市场约束力来强化商业银行的风险管理意识.     

银行理财产品与金融稳定--基于银行间风险传染的仿真分析

理财产品业绩受市场波动影响加大,有可能与原有银行间风险传染机制共振、放大银行系统风险。基于此视角,本文将银行理财产品嵌入银行间风险传染模型,研究银行理财产品对银行间风险传染的影响。结果发现:(1)在模型假定的条件下,考虑理财产品后,风险传染引发的平均损失增加28.76%。(2)如果考虑破产银行对理财产品的信息传染,平均损失进一步增加17.5%。(3)在投资者敏感性、资产非流动性较高时,银行对理财产品进行救助可以有效抑制风险传染;但冲击较大时,救助则会造成更大范围的风险传染。     

The credit quality channel: Modeling contagion in the interbank market

We propose an algorithm to model contagion in the interbank market via what we term the “credit quality channel”. In existing models on contagion via interbank credit, external shocks to banks often spread to other banks only in case of a default. In contrast, shocks are transmitted also via asset devaluations and deteriorations in the credit quality in our algorithm. First, the probability of default (PD) of those banks directly affected by some shock increases. This increases the expected loss of the credit portfolios of the initially affected banks’ counterparties, thereby reducing the counterparties’ regulatory capital ratio. From a logistic regression we estimate the increase in the counterparties’ PD due to a reduced capital ratio. Their increased PDs in turn affect the counterparties’ counterparties, and so on. This coherent and flexible framework is applied to the bilateral interbank credit exposure of the entire German banking system in order to examine policy questions. For that purpose, we propose to measure the potential cost of contagion of a given shock scenario by the aggregated regulatory capital loss computed in our algorithm.     

资产透明度、监管套利与银行系统性风险

资产不透明的金融机构过度依赖批发性融资进行监管套利不利于系统性风险的防控。在此背景下,本文首先在经典银行道德风险模型的基础上引入关联性,从资产透明度和监管套利的视角分析银行系统性风险累积的内在机理。而后利用2007-2018年中国上市银行微观数据,构建资产透明度指标和系统性风险指标(SRISK、MES),对理论推论进行实证检验。主要结论有:(1)资产不透明、监管套利会提高银行的系统性风险。(2)监管套利弱化了资产透明度和资本监管机制对银行系统性风险承担的约束作用,资产透明度与资本监管机制在约束系统性风险承担中的协调作用不明显。(3)以大银行为主的债权银行受监管套利的影响相较于受资产透明度的影响更明显。在此基础上,我们对完善金融风险防范体系以及监管机制提出了若干建议。     

Reputational contagion and optimal regulatory forbearance

Existing studies suggest that systemic crises may arise because banks either hold correlated assets, or are connected by interbank lending. This paper shows that common regulation is also a conduit for interbank contagion. One bank's failure may undermine confidence in the banking regulator's competence, and, hence, in other banks chartered by the same regulator. As a result, depositors withdraw funds from otherwise unconnected banks. The optimal regulatory response to this behavior can be privately to exhibit forbearance to a failing bank. We show that regulatory transparency improves confidence ex ante but impedes regulators' ability to stem panics ex post.     

Completeness,interconnectedness and distribution of interbank exposures—a parameterized analysis of the stability of financial networks

This paper assesses the impact of a certain structure of interbank exposures on the stability of a stylized financial system. Given a certain balance sheet structure of financial institutions, a large number of valid matrices of interbank exposures is created by a random generator. Assuming a certain loss given default, domino effects are simulated. The main results are, first, that financial stability depends not only on the completeness and interconnectedness of the network, but also on the distribution of interbank exposures within the system (measured by entropy). Second, looking at random graphs, the sign of the correlation between the degree of equality of the distribution of claims and financial stability depends on the connectivity of the financial system as well as on additional parameters that affect the vulnerability of the system to interbank contagion. Third, the more concentrated the assets are within a money center model, the less stable it is. Fourth, a money center model with asset concentration among core banks is less stable than a random graph with banks of homogeneous size.     

BANK FAILURE AND CONTAGION EFFECTS: EVIDENCE FROM HONG KONG

In this paper the influence of three Hong Kong bank failures on stock prices of the colony's banking industry is examined. As deposit insurance is nonexistent in Hong Kong, the world's fourth-largest financial center, an interesting environment is provided for testing contagion effects of bank failure on other healthy financial institutions. By examining contagion effects in an environment void of explicit deposit insurance, this study should provide interesting insights into the resiliency of modern-day financial markets. In turn, insights should also be provided into debates concerning the role and reform of deposit insurance and the rationale for regulation of the financial services industry in general. The results indicate that unexpected bank failure causes significant negative stock price reactions within the banking industry; yet, some banks are less affected than others.     

Why do contagion effects vary among bank failures?

Many of the previous studies on contagion effects in the banking industry focused on the failure of a large bank to determine whether the adverse effects spread to other banks. Yet, little is known whether other publicized bank failures cause contagion effects, and why the effects may vary among bank failures. Given the changes in the banking environment over time, contagion effects could be conditioned on the characteristics of the failing bank and of the banking environment at that time. We assess 99 publicized bank failures over the 1980–1996 period, and find that contagion effects exist in general for the surviving rivals of the failed bank. The degree of contagion effects varies over time (among bank failures), and is stronger when the failed bank is a multibank holding company, when the failed bank is publicly held, when the failed bank is relatively large, when the rivals are relatively small, and when the rivals have relatively low capital levels. The contagion effects are less pronounced in the period following the passage of FIRREA. Furthermore, the total risk-shifts of surviving rival banks in response to the announcement of a failed bank are inversely related to their capital level, and total risk-shifts of rival banks are less pronounced for failures occurring just after the passage of FIRREA. The results suggest that a bank’s exposure to possible contagion effects due to a bank failure can be partially controlled by a bank’s managerial policies and by regulatory policies.