Interbank Assets Research Articles

Does cross-industry loan diversification reduce bank systemic risk? Evidence from listed banks in China

ABSTRACT Banking plays a crucial role as the most significant financial intermediary, and the effectiveness of its diversification strategy aimed at reducing individual bank systemic risk is a significant topic in both theory and practice. In this study, we investigate the impact of cross-industry loan diversification on bank systemic risk using data from listed banks, and reveal a significant positive correlation, indicating a clear‘diversification systemic risk’ effect. This effect remains robust across a series of robustness tests. Further research reveals the influence of cross-industry loan diversification on bank systemic risk operates primarily through the channel of interbank asset similarity. Additionally, we find the‘diversification systemic risk’ effect is particularly prominent among joint-stock banks, those with high interbank deposits，and those with high real estate loans. These findings hold important reference value for the ongoing reforms and practices in China aimed at preventing bank systemic risk.

Interbank liquidity transmission and the credit channel of monetary policy in China

This paper investigates the liquidity transmission of traditional and structural monetary policy instruments in the interbank market and their effects on bank credit growth based on 107 banks from 2005Q4 to 2020Q4 in China. We find that the credit channel of monetary policy differs across banks with heterogeneous liquidity acquisitions. The liquidity released by open market operations (OMOs) cannot stimulate credit growth, but increases the net interbank assets of primary banks and reduces those of non-primary banks. The reduction of the required reserve ratio (RRR) increases the net interbank assets of non-primary banks and stimulates non-primary banks’ credit growth. Furthermore, a higher interbank financing ratio reduces the credit channel of RRR reduction in non-primary banks. In addition, medium- and small-sized banks would increase credit growth and reduce reliance on interbank financing, as the structural monetary policy instrument of medium-term lending facilities (MLFs) plays a growing role post-reform.

How Does Exogenous Shock Change the Structure of Interbank Network?: Evidence from China under COVID-19

ABSTRACT This paper utilizes China’s interbank deposit system under COVID-19 to examine how interbank network changes with considerable uncertainty surrounding exogenous shock. We investigate the interbank network in China by specifying the core-periphery pattern to disentangle the network development and the pandemic onset. In order to model the interbank deposit system, maximum entropy and partition-based approach are employed to estimate the bilateral exposures for banks and identify the network structure, respectively. We find that the four largest global systemically important banks (G-SIBs) in the world play a critical role in bearing interbank burden under this crucial period by increasing interbank assets and decreasing interbank liability. By comparing the situations before and after the outbreak of the pandemic in stress-testing, the empirical evidence shows that the number of cores and capital of them is declined in 2020Q2; however, the topological structure of the network is increasingly similar to a typical core-periphery pattern, and the changed interbank network can better absorb the loss and interrupt the contagion of systemic risk.

Climate risk and financial stability in the network of banks and investment funds

We analyze the effects on financial stability of the interplay between climate transition risk and market conditions, such as recovery rate and asset price volatility. To this end, we extend the framework of the climate stress-test of the financial system by including an ex-ante network valuation of financial assets which accounts for asset price volatility as well as for endogenous recovery rate on interbank assets. Moreover, we also consider the dynamics of indirect contagion of banks and investment funds, which are key players in the low carbon transition, via exposures to the same asset classes. We derive some analytical results and we apply the model to a unique supervisory dataset in a range of climate policy scenarios and market conditions. In the event of a disorderly low-carbon transition, stronger market conditions allow to reach more ambitious climate policies at the same level of financial risk.

How Does Exogenous Shock Change the Structure of Interbank Network?: Evidence from China under COVID-19

This paper utilizes China’s interbank deposit system under COVID-19 to examine how interbank network changes with considerable uncertainty surrounding exogenous shock. We investigate the interbank network in China by specifying the core-periphery pattern to disentangle the network development and the pandemic onset. In order to model the interbank deposit system, maximum entropy and partition-based approach are employed to estimate the bilateral exposures for banks and identify the network structure, respectively. We find that the four largest global systemically important banks (G-SIBs) in the world play a critical role in bearing interbank burden under this crucial period by increasing interbank assets and decreasing interbank liability. By comparing the situations before and after the outbreak of the pandemic in stress-testing, the empirical evidence shows that the number of core banks and capital of banks is declined in 2020Q2; however, the topological structure of the network is increasingly similar to a typical core-periphery pattern, and the changed interbank network can better absorb the loss and interrupt the contagion of systemic risk.

What is the minimal systemic risk in financial exposure networks?

We quantify how much systemic risk can be eliminated in financial contract networks by rearranging their network topology. By using mixed integer linear programming, financial linkages are optimally organized, whereas the overall economic conditions of banks, such as capital buffers, total interbank assets and liabilities, and average risk-weighted exposure remain unchanged. We apply the new optimization procedure to 10 snapshots of the Austrian interbank market where we focus on the largest 70 banks covering 71% of the market volume. The optimization reduces systemic risk (measured in DebtRank) by about 70%, showing the huge potential that changing the network structure has on the mitigation of financial contagion. Existing capital levels would need to be scaled up by a factor of 3.3 to obtain similar levels of DebtRank. These findings underline the importance of macro-prudential rules that focus on the structure of financial networks. The new optimization procedure allows us to benchmark actual networks to networks with minimal systemic risk. We find that simple topological measures, like link density, degree assortativity, or clustering coefficient, fail to explain the large differences in systemic risk between actual and optimal networks. We find that if the most systemically relevant banks are tightly connected, overall systemic risk is higher than if they are unconnected.

Banking Competition, Interbank Business Expansion and Bank Credit Risk

With the competition becoming more intense, scarcity of deposits makes it reasonable for commercial banks to increasingly depend on interbank liability. As consequence, a large amount of interbank debt flows to shadow banks through the channel of interbank investment and financial products with the motive of regulatory arbitrage, which increases interbank leverage. Previous studies have shown that the expansion of interbank asset and interbank debt has an impact on the effect of monetary policy and liquidity risks, but seldom discuss whether and how interbank leverage influences the credit risk of traditional loans. This paper puts forward that the essence of interbank leverage rising is the expansion of interbank sha- dow credit. Under the analysis on how interbank shadow credit affects the credit risk of traditional loans through the channel of financing structure, investment efficiency, regulatory evasion and risk-taking, we empirically examine the relationship between interbank leverage and the credit risk of traditional loans by means of OLS and IV/2SLS estimation, and find that the effect of interbank leverage on credit risk is negative as interbank leverage increases. However, when leverage reaches a certain level, the impact of interbank leverage on credit risk becomes positive. Furthermore, we analyze the heterogeneous effect that interbank leverage has on the credit risk of traditional loans when the size or type of banks is distinguished. By means of threshold regression and regression by group, we conclude that if taking no account of shadow credit caused by NCD, the rise of interbank leverage reduces the credit risk of the five biggest state-owned banks, city commercial banks and rural commercial banks but reinforces the credit risk of joint-stock banks; Nevertheless, when taking NCD into consideration, except that the impact of interbank leverage on the credit risk of the five biggest state-owned banks is negative, the rise of interbank leverage increases the credit risk of other banks, including joint-stock banks, city commercial banks and rural commercial banks. At last, we analyze that interbank shadow credit offsets the effect of monetary policy. The empirical results also show that the higher the level of inter- bank leverage expansion, the stronger the hedging effect of monetary policy. This paper contributes to the following aspects: Firstly, it expands the literature on how shadow credit expansion affects the liquidity risk to how it affects the traditional credit risk. Secondly, it proves that the inter- bank certificates of deposits have a significant incentive effect on the traditional credit risk of city/rural commercial banks. At the same time, it shows that MPA’s new policy will bring the interbank certificates of depo- sits into the assessment of the proportion of interbank liability to help to improve the quality of risk supervision, which is of practical significance to understand the interbank risk of city/rural commercial banks, and then to implement differentiated risk supervision strategies. Thirdly, based on the perspective of commercial banks’ interbank business, this paper explores the factors that inhibit the transmission of monetary policy, which provides a logical basis for understanding how regulatory arbitrage under the interbank channel impacts the regulation of monetary policy and thus improves the quality of monetary policy regulation.

Network model of credit risk contagion in the interbank market by considering bank runs and the fire sale of external assets

We construct a network model of credit risk contagion in the interbank lending market based on time series. Such network model is based on imperfect information considering that the initial credit default of the debt bank will cause the creditor bank to run on its debt bank and the debt bank’s fire sale of external assets held to repay the debt or control the leverage ratio that reduce asset prices and create spillovers. By the theoretical deduction and simulation method, we study how the contagion effects of credit risk accumulate and spread in the interbank market network. In addition, we study the evolution characteristics of credit risk contagion caused by the initial default of debt banks in the interbank market. The following are the results of the study. First, when banks sell external assets at a fixed price, the fire sale of external assets can effectively reduce the probability of credit default. However, when the price of external assets decrease with the increase of fire sales volume, banks’ fire sale of external assets will lead to more serious contagion spillover consequences than that of none of the banks’ selling strategies. Second, the panic of bank decision makers in the banking system has a nonlinear evolution characteristic of increasing and decreasing credit risk contagion. Third, the higher the proportion of banks’ liquid assets, the stronger their ability to resist credit risks. Last, the higher the proportion of banks’ interbank assets, the stronger the contagion effect of credit risk on the entire banking system.

A Double-Layer Network and the Contagion Mechanism of China's Financial Systemic Risk

We studied the dynamic mechanism of systemic risk contagion in financial systems with a double-layer network and analysed the factors influencing systemic risk. We used the maximum entropy method to estimate interbank loan data and combined cross-shareholding data among financial institutions to construct a double-layer network structure of China’s financial system, consisting of an interbank lending and a cross-shareholding network. Through simulation, we analysed the nonlinear evolution of the risk contagion process. Numerical results showed that contagious losses in the double-layer network are more than the sum of the losses infecting the interbank lending network and the cross-shareholding network independently. Most of the excess losses are caused by the interbank lending channel. However, if linkages in the cross-shareholding channels are strengthened, excess losses tend to increase. Furthermore, we found that certain specific factors, i.e., the loss rate of assets, the loss given default, total assets, interbank assets and interbank liabilities, have a positive impact on the losses caused by the potential bankruptcy of an institution. We also found that the number of bankruptcies could increase significantly with an increase in the asset loss rate and the loss given default. Our findings suggest certain policy recommendations for managing systemic risk.

Measuring the systemic risk of China’s banking sector: an application of differential DebtRank

This paper investigates the systemic risk of China’s banking sector via network analysis and differential DebtRank from 2007 to 2016. The interbank network of each year is constructed by means of the yearly interbank assets and liabilities of twenty-eight Chinese banks. The results show that the twenty-eight banks in China are closely connected through interbank networks. We compute the risk contribution of each bank and the expected systemic losses by using the differential DebtRank method. We find that the interconnectedness of a bank is highly significant to its systemic risk: banks with high eigenvector centrality contribute more systemic risk. Banks with high returns on assets and low liquidity also contribute more systemic risk. The overall systemic risk changes over time and reaches high levels in 2007, 2008, 2011 and 2012. In high-risk years, the risk contribution of small-scale banks significantly increases. Our results offer novel insights with reference to macroprudential supervision.

The economics of netting in financial networks

Can the netting of on-balance-sheet interbank assets and liabilities be useful in thwarting financial contagion during a systemic crisis episode? In order to answer this question, in this paper we use mean-field approximation techniques and computer simulations to comparatively assess how contagion spreads out throughout an interbank network under different settlement modes. We find that a regulator forcing banks to net their credit/debt obligations instead of allowing them to regulate their mutual exposures on a gross basis succeeds in reducing the number of defaults and in preserving the aggregate amount of bank capital. Interbank netting takes its toll on retail depositors by increasing their potential losses, however. Hence, our analysis provides support for an optimal crisis-management policy mix that combines the enforcement of bilateral netting with a blanket deposit insurance scheme. The desirability of netting increases when the system is highly connected and susceptible to large shocks, especially when strains are first detected in banks located at the core of the network.

Coordination Failures, Bank Runs and Asset Prices

We study efficiency properties of competitive economies in which banks provide liquidity insurance and interact on secondary asset markets. While all banks are subject to extrinsic risk, a bank's portfolio choice determines whether it is prone to a bank run in one of the extrinsic states. Asset prices determine the value of bank assets and thus how to structure run-proof portfolios. Except for very large sunspot probabilities, equilibria with trivial sunspots exist, where asset prices are state-dependent, bank runs do not occur and the efficient allocation obtains. Interbank asset markets are also a new source of multiplicity of equilibrium. For low sunspot probabilities, there are equilibria in which all banks are run-prone. For high sunspot probabilities, there is no equilibrium with run-prone banks but consumption can be indeterminate. If the sunspot probability is neither high nor low, equilibria may exist in which some banks are run-prone and others are run-proof.

The impact of network inhomogeneities on contagion and system stability

This work extends the contagion model introduced by Nier et al. (J Econ Dyn Control 31(6):2033–2060, 2007. http://www.bankofengland.co.uk/publications/workingpapers/wp346.pdf ) to inhomogeneous networks. We preserve the convenient description of a financial system using a sparsely parameterized random graph, but add several relevant inhomogeneities. These include well-connected banks, financial institutions with disproportionately large interbank assets, and big banks that focus on wholesale and retail customers. These extensions significantly enhance the model’s generality as they reflect realistic inhomogeneities that have a potentially decisive impact on a system’s stability. We find that large and well-connected banks have a surprisingly modest impact. However, institutions with disproportionately large interbank assets significantly increase the risk of contagion in networks. Moreover, these effects can be partly compensated by a redistribution of equity capital, even without increasing the total amount. However, the level of regulatory capital should be defined according to the interbank market position of a bank, and not the size of the bank.

Risk Contagion in Interbank Networks: An Empirical Study Based on Banking Industry in China

This paper adopts the maximum entropy method to estimate the interbank networks of banking industry in China from 2007 to 2013. Under the premise of the distinction between creditor banks and debt banks,it calculates total risk of interbank business rivals by taking network linkage strength as the weight,and then explores the effect of total risks of interbank business rivals on banks' own risk. Results show that the risks of debt banks have the significantly positive effect on the risks of creditor banks,but the risks of creditor banks do not have the significant effect on the risks of debt banks,confirming that there is risk contagion from debt banks to creditor banks in China's interbank business. Further analysis shows that,banks with high leverage,high interbank asset ratio and high interbank asset concentration are more susceptible to contagion.This paper provides evidence for risk contagion resulting from interbank business in China,and is of great reality significance to the enhancement of preventing banks against risk contagion and the avoidance of banking systematic risks.

A Counterparty Risk Study of UK Banking Systems

We study the effect of counterparty risk on the stability of a banking system using stylized banking cascade models calibrated with UK exposure and balance sheet data from regulatory reports. We observe the development of a fragile phase, at which small perturbations to banks' capital reserves can trigger a sudden system failure. We compute the critical balance sheet values for a stylized homogeneous system and show that a more realistic heterogeneous system, with different bank types and complex interbank network calibrated on UK data, also has systemic failures around similar sized shocks to banks' capital as the stylized homogeneous system. By aggregating the fraction of surviving banks to specific bank types, we show that balance sheet size and banks' position in the interbank network are not the decisive components when considering system failure due to counterparty insolvency. This implies that interbank network structure and heterogeneity do not play a critical role in the onset of the fragile phase. Instead, the onset of the system failure depends on the ratios of interbank assets to total assets and loss absorbing capital to total assets. Finally, we discuss the effects of increased exposure of specific banks and we compute minimum capital requirements to ensure a stable banking system.

Managing markets for toxic assets

A model in which banks trade toxic assets to raise funds for investment is analyzed. Toxic assets generate an adverse selection problem and, consequently, the interbank asset market provides insufficient liquidity. Investment is inefficiently low because acquiring funding requires banks to sell high-quality assets for less than their “fair” value. Equity injections reduce liquidity and may be counterproductive as a policy for increasing investment. Paradoxically, if it is directed to firms with the greatest liquidity needs, an equity injection will reduce investment further. Asset purchase programs, like the Public–Private Investment Program, often have favorable impacts on liquidity, investment and welfare.

A model of financial contagion with variable asset returns may be replaced with a simple threshold model of cascades

I show the equivalence between a model of financial contagion and the threshold model of global cascades proposed by Watts (2002). The model financial network comprises banks that hold risky external assets as well as interbank assets. It is shown that a simple threshold model can replicate the size and the frequency of financial contagion without using information about individual balance sheets.

Macroprudential capital requirements and systemic risk

Abstract When setting banks’ regulatory capital requirement based on their contribution to the overall risk of the banking system we have to consider that the risk of the banking system as well as each bank’s risk contribution changes once bank equity capital gets reallocated. We define macroprudential capital requirements as the fixed point at which each bank’s capital requirement equals its contribution to the risk of the system under the proposed capital requirements. We use a network based structural model to measure systemic risk and how it changes with bank capital and allocate risk to individual banks based on five risk allocation mechanisms used in the literature. Using a sample of Canadian banks we find that macroprudential capital allocations can differ by as much as 25% from observed capital levels, are not trivially related to bank size or individual bank default probability, increase in interbank assets, and differ substantially from a simple risk attribution analysis. We further find that across all risk allocation mechanisms macroprudential capital requirements reduce the default probabilities of individual banks as well as the probability of a systemic crisis by about 25%. Macroprudential capital requirements are robust to model risk and are positively correlated to future capital raised by banks as well as future losses in equity value. Our results suggest that financial stability can be substantially enhanced by implementing a systemic perspective on bank regulation.

The Impact of Network Inhomogeneities on Contagion and System Stability

This work extends the contagion model introduced by Nier et al. (2007) to inhomogeneous networks. We preserve the convenient description of a financial system by a sparsely parameterized random graph but add several relevant inhomogeneities, namely well-connected banks, financial institutions with disproportionately large interbank assets, and big banks focusing on wholesale and retail customers. These extensions significantly enhance the model's generality as they reflect inhomogeneities as found in reality with a potentially decisive impact on system stability. Whereas well-connected banks and big retail banks have only a surprisingly modest impact, we find a significantly enhanced contagion risk in networks containing institutions with disproportionately large interbank assets. Moreover, we show that these effects can be partly compensated by a suitable regulatory response which demands additional net worth buffers for banks with above average volume of interbank assets. The stabilising effect is most notably achieved by a pure redistribution of equity capital without increasing its total amount.

Financial Contagion on Power Law Networks

We use networks with power law degree distributions to build stylistic models of interbank financial interactions, and employ computer simulations to study progression of financial contagion through these networks. We find that power law networks are more resilient than Erdos-Renyi networks to random financial shocks. Power law networks are more vulnerable to targeted shocks than to random shocks. We also study the effect of average node degree, interbank asset ratio, and capital buffer ratio on the extent of financial contagion.