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.     

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.     

The impact of credit supply shocks and a new Financial Conditions Index based on a FAVAR approach

This paper investigates the impact of credit supply shocks on the macroeconomy and estimates a new financial conditions index. We calculated two credit supply factors using a time-varying parameter FAVAR model. The first factor is identified as the willingness to lend, while the second factor is the lending capacity. The impact of these two types of shocks and their changes over time is examined using Hungarian data. The two types of lending shocks affect macro variables rather differently: a positive lending capacity shock (in a banking system mostly owned by non-residents) influences GDP through a decrease in country risk and the easing of monetary policy, while willingness to lend primarily increases lending activity. The two financial shocks also differ in terms of their evolution over time: deviations from the average in the impact of a willingness to lend shock usually occur for short periods of time and are of a small degree between the various quarters. However, in the case of lending capacity, certain trends can be observed: before the crisis, the stability of the banking system played an increasing role in country risk, whereas after 2008 it appears that monetary policy paid increasing attention to financial stability. Finally, a new type of financial conditions index is quantified based on our estimates, which measures the impact of the banking system’s lending activity on GDP growth.     

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.     

The multi-country transmission of sovereign and banking risk: a spatial vector autoregressive approach

ABSTRACT

This paper develops a spatial vector autoregressive (SpVAR) model to investigate the transmission of sovereign, banking and corporate default risks among 11 Eurozone countries for the period January 2008–December 2013. The results show that a significant proportion of default risk variation is explained by foreign shocks. However, the cross-border sovereign–bank nexus is statistically significant, but economically moderate. Among the three sectors, shocks to the banking sector play the most critical role. On average, for the 11 countries, a foreign banking shock can explain 7%, 23% and 18% of the forecast error variance of changes in sovereign, banking and corporate credit default swap spreads respectively.     

The role of banking regulation in an economy under credit risk and liquidity shock

This paper develops a Dynamic Stochastic General Equilibrium model which includes a financial sector to analyze the effects of liquidity shock and credit risk in the Brazilian economy. Banks use equity capital and deposits from agents to finance investments of the productive sector. The sources of financial frictions are default rate and liquidity shock, due to deposits withdrawn in advance. The banking supervisor injects liquidity in the deposit market. Using data for the Brazilian economy in the period from 1995 to 2009, the structural parameters are estimated by Bayesian methods. Impulse response functions are computed to describe the dynamic effects of exogenous shocks. The major results show that credit risk is pro-cyclical and default risk depends on structural features. The banking regulator is able to set up a policy to promote financial stability and efficiently reduce fluctuations in the output.     

Contagion risk in the Czech financial system: A network analysis and simulation approach

This paper examines the potential for contagion within the Czech banking system via the channel of interbank exposures of domestic banks, enriched by a liquidity channel and an asset price channel, over the period March 2007 to June 2012. A computational model is used to assess the resilience of the Czech banking system to interbank contagion, taking into account the size and structure of interbank exposures as well as balance sheet and regulatory characteristics of individual banks in the network. The simulation results suggest that the potential for contagion due to credit losses on interbank exposures was rather limited. Even after the introduction of a liquidity condition into the simulations, the average contagion was below 3.8% of the remaining banking sector assets, with the exception of the period from December 2007 to September 2008. Activation of the asset price channel further increases the losses due to interbank contagion, showing that the liquidity of government bonds would be essential for the stability of Czech banks in stress situations. Finally, the simulation results for both idiosyncratic and multiple bank failure shocks suggest that the potential for contagion in the Czech banking system has decreased since the onset of the global financial crisis.     

Portfolio diversification and systemic risk in interbank networks

This paper contributes to a growing literature on the ambiguous effects of risk diversification. In our model, banks hold claims on each other’s liabilities that are marked-to-market on the individual financial leverage of the obligor. The probability of systemic default is determined using a passage-problem approach in a network context and banks are able to internalize the network externalities of contagion through their holdings. Banks do not internalize the social costs to the real economy of a systemic default of the banking system. We investigate the optimal diversification strategy of banks in the face of opposite and persistent economic trends that are ex-ante unknown to banks. We find that the optimal level of risk diversification may be interior or extremal depending on banks exposure the external assets and that a tension arises whereby individual incentives favor a banking system that is over-diversified with respect to the level of diversification that is desirable in the social optimum.     

How important can bank lending shocks be for economic fluctuations?

We analyze the quantitative importance of bank lending shocks on real activity fluctuations in Norway and the UK, using structural VARs estimated on quarterly data from 1988 to 2010. We find that an adverse bank lending shock causes output to contract, and that such shocks can account for a substantial share of output volatility. This suggests that financial intermediation is an important source of shocks. The empirical analysis comprises the Norwegian banking crisis (1988–1992) and the recent period of banking failures in the UK. However, the results are also non-trivial when omitting periods of systemic banking distress from the sample.     

Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors

This paper presents a dynamic portfolio credit model following the regulatory framework, using macroeconomic and latent risk factors to predict the aggregate loan portfolio loss in a banking system. The latent risk factors have three levels: global across the entire banking system, parent-sectoral for the intermediate loan sectors and sector-specific for the individual loan sectors. The aggregate credit loss distribution of the banking system over a risk horizon is generated by Monte Carlo simulation, and a quantile estimator is used to produce the aggregate risk measure and economic capital. The risk contributions of the individual sectors and risk factors are measured by combining the Hoeffding decomposition with the Euler capital allocation rule. For the U.S. banking system, we find that the real GDP growth rate, the global and sector-wide frailty risk factors and their spillovers significantly affect loan defaults, and the impacts of the frailty factors are not only economy-wide but also sector-specific. We also find that the frailty risk factors make more significant risk contributions to the aggregate portfolio risk than the macroeconomic factors, while the macroeconomic factors help to improve the accuracy and efficiency of the credit risk forecasts.     

Identifying credit demand,financial intermediation,and supply of funds shocks: A structural VAR approach

In this paper, we identify three exogenous shocks to credit market: demand for credit, supply of funds into the financial system, and the willingness to lend of financial institutions (financial intermediation), and also, determine the contribution of these shocks to fluctuations in the credit market and overall economic activity. We estimate a structural vector autoregression model where the three credit shocks are identified with a set of sign restrictions motivated by a simple partial equilibrium model of financial intermediation. We find that the credit demand shock explains significantly the variations in the long-term loan rate proxied by the Moody’s Baa corporate bond yield, while the supply of funds shock contributes to most of the fluctuations in the short-term commercial paper rate. The financial intermediation shock drives most of the fluctuations in the quantity of loans as well as the spread between the Baa and commercial paper rates. Of the credit shocks, we find that the financial intermediation shock has the largest impact on real economic activity. In fact, our analysis implies that the sharp decline in output during the 2007–2009 financial crisis is largely attributable to the financial intermediation shock, along with shocks originating outside of the financial system.     

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.     

Emergence of a core-periphery structure in a simple dynamic model of the interbank market

This paper studies a simple dynamic model of interbank credit relationships. Starting from a given balance sheet structure of a banking system with a realistic distribution of bank sizes, the necessity of establishing interbank credit connections emerges from idiosyncratic liquidity shocks. Banks initially choose potential trading partners randomly, but over time form preferential relationships via an elementary reinforcement learning algorithm. As it turns out, the dynamic evolution of this system displays a formation of a core-periphery structure with mainly the largest banks assuming the roles of money center banks mediating between the liquidity needs of many smaller banks. Statistical analysis shows that this evolving interbank market shares the majority of the salient characteristics of interbank credit relationship that have been put forth in recent literature. Preferential interest rates for borrowers with strong attachment to a lender may prevent the system from becoming extortionary and guarantee the survival of the small peripherical banks.     

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.     

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.

     

BANK CAPITAL REQUIREMENTS, BUSINESS CYCLE FLUCTUATIONS AND THE BASEL ACCORDS: A SYNTHESIS

Abstract.  In order to survey the mechanisms through which the introduction of Basel II bank capital requirements is likely to accentuate the procyclical tendencies of banking, this paper brings together the theoretical literature on the bank capital channel of propagation of exogenous shocks and the literature on the regulatory framework of capital requirements under the Basel Accords. We conclude that the theoretical models that revisit the bank capital channel under the new accord generally support the Basel II procyclicality hypothesis and that the magnitude of the procyclical effects essentially depends on (i) the composition of banks' asset portfolios, (ii) the approach adopted by banks to compute their minimum capital requirements, (iii) the nature of the rating system used by banks, (iv) the view adopted concerning how credit risk evolves through time, (v) the capital buffers over the regulatory minimum held by the banking institutions, (vi) the improvements in credit risk management and (vii) the supervisor and market intervention under Basel II. The recent events and instability in financial markets all over the world have led the procyclicality issue to enter the agendas of several political international  fora  and some measures to mitigate procyclicality are being put forward. The bank capital channel literature should now play an important role in evaluating their effectiveness.     

Determinants of bank interest margins in Russia: Does bank ownership matter?

This paper analyzes interest margin determinants in the Russian banking sector with a particular emphasis on the bank ownership structure. Using unique bank-level data covering Russia's entire banking sector for the 1999–2007 period, we find that the impact of a number of commonly used determinants such as market structure, credit risk, liquidity risk and size of operations differs across state-controlled, domestic-private and foreign-owned banks. At the same time, the influence of operational costs and risk aversion is homogeneous across ownership groups. The results overall suggest that the form of bank ownership needs to be considered when analyzing interest margin determinants.     

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?     

The granularity of the Brazilian banking market

Bank size distributions concentrate in a few large banks – the big “grains.” This fact means idiosyncratic shocks at the bank level do not cancel out, thus affecting the business cycle. Here, we present evidence of granularity in the banking market using Brazilian data. We examine the explanatory power of the granular banking residual of the five largest banks on quarterly GDP changes from 2010 to 2019. We conservatively find that shocks to revenues of these top five banks explain nearly one-fifth of GDP fluctuations.     

Multinomial modeling methods: Predicting four decades of international banking crises

This paper examines banking crises in a large sample of countries over a forty-year period. A multinomial modeling approach is applied to panel data in order to track and capture end-to-end cyclical crisis formations, which enhances the binary focus of previous research studies. Several macroeconomic and banking sector variables are shown to be emblematic of leading indicators across the idiosyncratic stages of a banking crisis. Gross domestic product is an early warning signal across all phases, and a concomitant deterioration in consumption spending and fixed capital formation, preceded by a credit boom, signal a banking crisis to come. Currency depreciation exemplifies ensuing financial distress, reinforced by developmental constructs and regional integration. Lower real interest rates, increasing imports, and rising deposits are frequently harbingers of a recovery. Period effects underscore the dynamic evolution of common contemporaneous precursors over time. Premised on pursuing cyclical movements through multiple outcomes, our findings on forecasting performance suggest enhanced predictive power. Several multinomial logistic models generate higher predictive accuracy in contrast to probit models. Compared to machine learning methods (which encompass artificial neural networks, gradient boost, k-nearest neighbors, and random forests methods), a multinomial logistic approach outperforms during pre-crisis periods and when crisis severity is modeled, whereas gradient boost has the highest predictive accuracy across numerous versions of the multinomial model. As investors and policy makers continue to confront banking crises, leading to high economic and social costs, enhanced multinomial modeling methods make a valuable contribution to improved forecasting performance.