Network structure,portfolio diversification and systemic risk

We investigate the effect of portfolio diversification on banking systemic risk, where the network effect is incorporated. We analyze three kinds of interbank networks, namely, random networks, small-world networks and scale-free networks. We show that the effect of portfolio diversification on banking systemic risk depends on interbank network structures and shock types. First, systemic risk increases first and then reduces with the increase of the level of portfolio diversification in the case of the individual shock. Second, in the case of the systemic shock, systemic risk reduces with the increases of the level of portfolio diversification. Third, banking systems with scale-free network structures are the most stable, and those with small-world network structures are the most vulnerable.     

Does diversification promote systemic risk?

We measure systemic risk when faced with simulated shocks through the systemic model of banking originated losses. The formation mechanism of systemic risk is explored from the perspective of investment diversification and asset similarity. The results indicate that contagion risks formed by the over similarity of investment assets are the main cause of systemic risk. The similarity generally promotes contagion risks, however, it shows a double-faced effect for state-owned commercial banks that disperse shocks from counterparties through their too-big-to-fail advantages. The similarity is determined by diversification, which initially promotes similarity and disperses it after a threshold. The diversification acts on the contagion process of systemic risk by the mediation of the similarity. Therefore, diversification generally has a nonlinear impact on systemic risk. The results provide regulatory implications for the systemic stability of the banking system.     

Topological properties of reconstructed credit networks and banking systemic risk

Financial bipartite networks provide channels for contagion risks and their topological properties determine financial stability. We enrich the bipartite network reconstruction methods proposed by Ramadiah et al. (2020) and extend them to the Chinese banking system. By comparing the reproducibility of the real credit market and the corresponding systemic risk, the impact of topological properties for different reconstructed bipartite networks on financial stability is analyzed. The empirical evidence shows that network reconstruction methods based on maximum entropy ensembles capture more properties in the real credit network. It also highlights that the different systemic risk level is mainly contributed by the topological properties based on common exposures. These analyses for topological properties provide regulatory insights for systemic risk prevention. It shows that reducing credit similarity across banks while increasing credit diversification in different sectors helps to control systemic risk. The results imply the possibility of increasing financial stability through the macro-regulation of the credit market structure.     

Systemic risk governance in a dynamical model of a banking system with stochastic assets and liabilities

We consider the problem of governing systemic risk in an assets–liabilities dynamical model of a banking system. In the model considered, each bank is represented by its assets and liabilities. The net worth of a bank is the difference between its assets and liabilities and bank is solvent when its net worth is greater than or equal to zero; otherwise, the bank has failed. The banking system dynamics is defined by an initial value problem for a system of stochastic differential equations whose independent variable is time and whose dependent variables are the assets and liabilities of the banks. The banking system model presented generalizes those discussed in Fouque and Sun (in: Fouque, Langsam (eds) Handbook of systemic risk, Cambridge University Press, Cambridge, pp 444–452, 2013) and Fatone and Mariani (J Glob Optim 75(3):851–883, 2019) and describes a homogeneous population of banks. The main features of the model are a cooperation mechanism among banks and the possibility of the (direct) intervention of the monetary authority in the banking system dynamics. By “systemic risk” or “systemic event” in a bounded time interval, we mean that in that time interval at least a given fraction of banks have failed. The probability of systemic risk in a bounded time interval is evaluated via statistical simulation. Systemic risk governance aims to maintain the probability of systemic risk in a bounded time interval between two given thresholds. The monetary authority is responsible for systemic risk governance. The governance consists in the choice of assets and liabilities of a kind of “ideal bank” as functions of time and in the choice of the rules for the cooperation mechanism among banks. These rules are obtained by solving an optimal control problem for the pseudo mean field approximation of the banking system model. Governance induces banks in the system to behave like the “ideal bank”. Shocks acting on the banks’ assets or liabilities are simulated. Numerical examples of systemic risk governance in the presence and absence of shocks acting on the banking system are studied.

     

Federal Home Loan Bank advances and bank risk

The Federal Home Loan Bank system (FHLB) has evolved into a major source of liquidity for the banking system with the demonstrated ability to borrow over a trillion dollars in world financial markets based on an implied U. S. Treasury guarantee. The FHLB loans the borrowed funds to commercial banks at reduced rates that are not adjusted for the risk of an individual bank. Moral hazard could cause member banks using FHLB loans to increase financial leverage and exposure to high risk assets. Conversely, the FHLB offers banks additional liquidity and specialized debt instruments that help them manage interest rate risk. We use dynamic panel generalized method of moments estimation to test the relation between FHLB advances and bank risk. We find that if banks have relatively normal default probabilities, advances are not associated with increased bank risk but, instead, advances are related to decreased interest rate risk. However, when bank default probabilities are high, our evidence suggests advances and higher bank risk are related.     

Robustness of banking networks to idiosyncratic and systemic shocks: a network-based approach

We propose a network-based structural model of credit risk to demonstrate how idiosyncratic and systemic shocks propagate across the banking system and evaluate the costs. The banking system is built as a network of heterogeneous banks which are connected with one another. In such a system, single credit events propagate through the interbank market from debtors to creditors and across the system. The shock is imposed as an unexpected event. We demonstrate that while idiosyncratic shocks cannot substantially disturb the banking system, a systemic shock of even a moderate magnitude can be highly detrimental. Such shock includes a huge contagious potential. We demonstrate that the costs of the shock are largely determined by the extent of contagion and range from negligible to catastrophic. The results imply that a severe crisis has to be initiated by a systemic shock of at least moderate magnitude. Capital ratio and the bank size are two additional factors of the banking system stability. Finally, credit risk analysis is sensitive to the network topology and exhibits a profound nonlinear characteristic.     

Networks and market-based measures of systemic risk: the European banking system in the aftermath of the financial crisis

This article investigates the behaviour of the European banking system during the financial crises that occurred in the last decades. Among the various approaches for measuring systemic risk, we consider network analysis, which describes the linkages among financial institutions and their whole structure. We construct a time-varying network of the European banking system. Banks are linked to form a global interconnected system and they mutually influence one another in terms of risk. We model their reciprocal influence via a weighted and directed network, in which weights are related to risk measures that are based on equity returns. Then, we apply two network indicators to investigate the prominence of a bank in spreading and receiving risk from the others. The results enable us to capture many features of the banking system while identifying the global systemically important banks. Moreover, the results of the analysis over time show how interconnections change over periods that are characterized by various economic scenarios.

     

Financial fragility and distress propagation in a network of regions

We investigate how the financial fragility in the real economy is affected by the average level of interdependence among agents across different regions of the economy. To this end, we develop a parsimonious agent-based model of firms and banks organized in geographic regions. The model is built on the framework of an existing class of models for business fluctuations. The goal of our exercise is to clarify the effect on systemic failures of the interplay between network interconnectedness and financial acceleration. In particular, we investigate the probability of individual and systemic failures with varying levels of interconnectedness. We find that, in the absence of financial acceleration, connectivity makes the system more resilient. In contrast, in the presence of financial acceleration, the probability of both individual and systemic failures are minimized at intermediate level of diversification.     

中国影子银行部门系统性风险的形成、影响与应对

本文分析了影子银行风险传染机制及其影响,在违约风险基于会计账户传染的马尔科夫过程假设下,运用投入产出法构建影子银行系统性风险测度模型,以2007-2012年中国影子银行业务数据进行检验,结果显示：信托公司部门是主要的风险源,银行部门是系统性风险最主要的承担者,观测期内影子银行部门系统性风险整体呈现上升趋势。防控系统性风险应从影子银行业务风险隔离机制、资本与杠杆率监管、信息透明度、宏观审慎框架和风险应急机制等建设着手。     

What drives credit risk in the Indian banking industry? An empirical investigation

Using a two-step system GMM approach on a unique bank-level dataset for the period 1998/99–2013/14, this paper tries to explore the key determinants of credit risk in the Indian banking industry. The main premise of this paper is that, along with regulatory and institutional factors, both macroeconomic and bank-specific variables influence the formation of credit risk in a banking system, and their influences vary across ownership groups. The empirical findings suggest that lower profitability, more diversification in the banking business, the large size of banks and a higher concentration of banks in lending increase the probability of defaults in India. We find a significant degree of persistence in credit risk, and the observed persistence is higher in the gross non-performing loans (NPLs) specification relative to what has been observed in the net NPLs specification. In the case of public sector banks, NPLs are more sensitive to internal bank-specific factors, while for private and foreign banks, macroeconomic and industry-related factors play a significant role in determining credit risk. Our results are robust for different panel data estimation models and sub-samples of ownership groups. The findings of this paper provide important insights into the formation of default risk in the banking system of an emerging market economy.     

Understanding the consequences of diversification on financial stability

In this paper, we study the consequences of diversification on financial stability and social welfare using an agent based model that couples the real economy and a financial system. We validate the model against its ability to reproduce several stylized facts reported in real economies. We find that the risk of an isolated bank failure (i.e. idiosyncratic risk) is decreasing with diversification. In contrast, the probability of joint failures (i.e. systemic risk) is increasing with diversification which results in more downturns in the real sector. Additionally, we find that the system displays a “robust yet fragile” behaviour particularly for low diversification. Moreover, we study the impact of introducing preferential attachment into the lending relationships between banks and firms. Finally, we show that a regulatory policy that promotes bank–firm credit transactions that reduce similarity between banks can improve financial stability whilst permitting diversification.

     

Investor protection,regulation and bank risk-taking behavior

This paper examines whether the influence of investor protection on banks’ risk is channeled through banking regulation, and vice-versa, using panel data from a sample of 567 European and US banks for the 2004–2015 period. As banking regulatory factors, we consider capital stringency, activity restrictions and private monitoring, whereas as investor protection factors, we consider the level of shareholder and creditor protection. We find that banking regulation moderates the positive direct influence of investor protection on banks’ risk, while investor protection reinforces the negative direct influence of banking regulation on risk. Moreover, we show that the negative effect of national regulations on banks’ risk is more pronounced during systemic crisis years. Finally, taking into account market competition, we argue that private monitoring only has a direct effect on banks’ risk, whereas the effects of capital stringency and activity restriction are channeled through market competition.     

Systemic risk mitigation in financial networks

We propose a multi-period clearing framework, where the level of systemic risk is mitigated through the provision of liquidity assistance. The interbank liability network evolves stochastically over time, and assets of defaulted banks are sold to qualified banks within the network through a first-price sealed-bid auction. We find that policies targeting systemically important banks are more effective in core-periphery network structures, whereas those maximizing the total liquidity in the system are preferred in random network configurations. We assess sensitivity of systemic risk to variations in interbank liabilities as well as to their correlation structure.     

Systemic risk in banking networks: Advantages of “tiered” banking systems

This paper studies the risk and potential impact of system-wide defaults in a tiered banking network, where a small group of head institutions has many credit linkages with other banks, while the majority of banks have only a few links. A network is random and displays a given distribution of the number of banks׳ linkages, known as degree. We model tiering by a negative correlation between degrees of neighboring banks and by a scale-free degree distribution. The main findings of the paper highlight the advantages of tiering. Both the risk of systemic crisis and the potential scope of the crisis are lower in systems with negative correlation of bank degrees than in other types of systems. Similarly, in scale-free networks, the resilience of the system to shocks is increasing with the level of tiering.     

Bank systemic risk and CEO overconfidence

This study examines the relationship between CEO overconfidence and banking systemic risk. We employ the CoVaR (Conditional Value-at-Risk) approach to measure a bank's contribution to systemic risk and compute its MES (Marginal Expected Shortfall) and SRISK (Systemic Risk index) to measure the exposure to banking systemic risk. We use a stock options based measure for CEO overconfidence and explore how managerial overconfidence could be associated with banking systemic risk. Using data for U.S. banks from 1995–2014, we find evidence that banks with overconfident CEOs have a higher contribution and exposure to systemic risk than banks with non-overconfident CEOs. We also show that the impact of CEO overconfidence contributed significantly more to systemic risk during the financial crisis of 2008–2009.     

The default contagion of contingent convertible bonds in financial network

This paper investigates the impact of contingent convertible (CoCo) bonds on systemic risk using Eisenberg-Noe’s financial network method, in which the network is linked by debt relationships. As an efficient method for addressing the problem of “too big to fail,” CoCo bonds have received widespread attention, particularly because the trigger for CoCo bonds is a systemic risk event. Thus, the impact of CoCo bonds on systemic risk needs to be addressed. To solve this problem, we adopt default contagion and loss amplification due to network linkage to measure systemic risk, from which we can ascertain the potential impact on it of CoCo bonds. The results show that CoCo bonds enhance the spillover effect of the issuer’s default; meanwhile, sufficient CoCo bonds partly offset the impact of default contagion from other banks. Furthermore, CoCo bonds enhance the amplification effect of loss due to network linkage, but the amplification effect diminishes after the bankruptcy cost is considered. Finally, the numerical test provides some insight into how the issuance of writedown (WD) bonds influences commercial banks in China. Our study not only offers suggestions to the regulators of CoCo bonds but also contributes to related studies.     

Deposit structure,market discipline,and ownership type: Evidence from Indonesia

In this paper, we extend the literature on the discipline imposed by depositors on banks by disentangling the impact of macro risk and micro risk. We also take advantage of a unique dataset in which depositors are split into different categories of deposit size in different types of banks (bank ownership structure). We consider the Banking Stability Index, which is used by the Indonesia Deposit Insurance Corporation as a dashboard to monitor banking stability at the country level as well as individual stability measures such as the Z-score. Using monthly data from 2005 to 2013, our findings show that both macro and micro levels of risk are considered by depositors to discipline banks. Large uninsured depositors are more effective at disciplining banks, highlighting the credibility of the insurance system that is in place. Bank ownership type also matters in explaining the difference in market discipline by depositors.     

Risk contagion in the banking network: New evidence from China

Based on data from 111 Chinese banks over the 2013–2016 period, this paper estimates the interbank bilateral lending matrix using the maximum entropy method. The estimated matrix is used to simulate the effects of credit and liquidity shocks on China’s banking network. Simulation results show that, under the extreme pressure scenario, the contagion arising from a liquidity shock is significantly stronger than the effect of a credit shock, indicating the importance of liquidity in the banking system. The contagion effect arising from a credit shock does not vary much over the sample period. However, the contagion effect arising from a liquidity shock decreases significantly, which could be attributed to contraction in interbank business due to stricter interbank business supervision. The simulation results also identify the most important and most vulnerable nodes of the banking system. An increase in the level of capital level can enhance the ability of banks to withstand credit and liquidity shocks. Our analysis also suggests that risk contagion faced by China’s banks varies across banking network structures.     

Income diversification and bank risk in Asia Pacific

This paper investigates the effect of income diversification on bank risk for a large sample of commercial banks in 14 Asia Pacific economies over the period 2011–2016. Using a dynamic panel data model with a system generalized methodof moments estimator, we find that banks with a higher level of income diversification are less risky in general. We further consider both developed and emerging economies according to the International Monetary Fund's classification of the level of economic development. Specifically, for emerging economies, the results indicate that banks with a higher level of income diversification face less risk. However, the diversification of commercial bank income has no significant impact on bank risk in developed Asia Pacific economies.     

Shadow Banking,Chinese Style

Shadow banks are broadly defined as entities which conduct credit intermediation outside the formal banking system. Poorly regulated, engaging in opaque forms of intermediation, deeply interconnected with the official banking system, and operating with implicit government guarantees, they pose a major source of systemic risk. Yet shadow banks provide an important service by channeling credit to excluded investors, and can complement the formal banking sector. What explains the rapid proliferation of shadow banks in China? How large are they and what forms do they take? What types of risks do they pose to the financial system? And how best can China utilise the services of shadow banks while at the same time ensuring that they do not create systemic risks for the financial system?