Interbank Network Research Articles

Do banks change their liquidity ratios based on network characteristics?

By applying interbank network simulation, this paper investigates the impact of interbank network topology on bank liquidity ratios. Whereas regulators have put more emphasis on liquidity requirements since the global financial crisis of 2007–2008, how differently shaped interbank networks affect individual bank liquidity behavior remains an open issue. We look at how banks' interconnectedness within interbank loan and deposit networks affects their decisions to hold more or less liquidity during normal times and distress times. Our sample consists of commercial, investment, and real estate and mortgage banks in 28 European countries and allows us to differentiate large and small networks. Our results show that accounting for bank connections within a network is important to understand how banks set their liquidity ratios. Our findings have critical implications for the implementation of Basel III liquidity requirements and bank supervision more generally.

Stress Testing the Unknown - The Impact of Network Reconstruction on Systemic Risk Estimates

Banks connect through a complex network of interbank credit exposures that determine contagion and hence the systemic stability of the network. Yet, the bilateral linkages of these institutions and thus the true structure of the network are typically unobservable, with leading reconstruction methods, such as maximum entropy or minimum density, potentially underestimating the true contagion risk of the network. Based on publicly available data from large European institutions, this paper analyses different network reconstruction techniques and the contagion risk impact of different network structures in a stress testing context. My findings suggest that uncertainty about the true interbank network leads to substantially varying risk assessments, where a Bayesian reconstruction approach can be used to identify contagion risk boundaries. In addition, network structure metrics that explain the variation in risk assessments are identified.

Interbank Networks in the Shadows of the Federal Reserve Act

Central banks provide public liquidity to traditional (regulated) banks with the intention of stabilizing the financial system. Shadow banks are not regulated, yet they indirectly access such liquidity through the interbank system. We build a model that shows how public liquidity provision may change the linkages between traditional and shadow banks, increasing systemic risk through three channels: reducing aggregate liquidity, expanding fragile short-term borrowing, and crowding out of private cross-bank insurance. We show that the creation of the Federal Reserve System and the provision of public liquidity changed the structure and nature of the U.S. interbank network in ways that are consistent with the model and its implications. We provide empirical evidence by constructing unique data on balance sheets and detailed disaggregated information on payments and funding connections in Virginia.

Interbank Networks in the Shadows of the Federal Reserve Act

Interbank Networks in the Shadows of the Federal Reserve Act

The Network Structure of the Malawi Interbank Market: Implications for Liquidity Distribution and Contagion around the Banking System

The study aimed to understand the network structure of the Malawi interbank market, a relatively small but active market. To do this, we constructed a network of banks using aggregated interbank loan amounts. We then analyzed the topological characteristics of the interbank market network structure and discussed the implications of such characteristics in terms of liquidity distribution and contagion in the Malawi banking system. We establish that the Malawi’s interbank network is fairly dense with a significantly high clustering and a small average path length. This implies that liquidity is able to flow in a fairly efficient manner within the network. Due to the relatively high connectivity of the network, entry or exit of a bank, on average, is likely to have little impact on the ability of other banks to lend and borrow from each other. The high connectivity further implies that banks are able to monitor each other’s behaviour. This may result into liquidity hoarding and may force some banks to get liquidity at a higher cost than the one prevailing on the market. The relatively high clustering and a small average path length further implies that the interbank participants are more vulnerable to contagion than in random networks. We further argue that because of the strong connectivity, the network may not be resilient to an operational shock affecting one or more of the banks. In this case, the impact of an operational shock may be felt not just on the connectivity of the network but rather on the availability of liquidity within the banking system.

Mapping bank securities across euro area sectors: comparing funding and exposure networks

We present new evidence on the structure of euro area securities markets using a multilayer network approach. Layers are broken down by key instruments and maturities as well as the secured nature of the transaction. This paper utilizes a unique dataset of banking sector crossholdings of securities to map these exposures among banks and economic and financial sectors. We can compare and contrast funding and exposure networks among banks themselves and of banks, non-banks and the wider economy. The analytical approach presented here is highly relevant for the design of appropriate prudential measures, since it supports the identification of counterparty risk, concentration risk and funding risk within the interbank network and the wider macro-financial network. JEL Classification: D85, E44, G21, L14

Optimal Bailouts and the Doom Loop with a Financial Network

Banks usually hold large amounts of domestic public debt which makes them vulnerable to their own sovereign’s default risk. At the same time, governments often resort to costly public bailouts when their domestic banking sector is in trouble. We investigate how the interbank network structure and the distribution of sovereign debt holdings jointly affect the optimal bailout policy in the presence of this doom loop. Rescuing banks with high domestic sovereign exposure is optimal if these banks are sufficiently central in the network, even though that requires larger bailout expenditures than rescuing low-exposure banks. Our findings imply that highly central banks can use exposure to their own government as a strategic tool to increase the likelihood of being bailed out. Our model thus illustrates how the doom loop exacerbates the too interconnected to fail problem in banking. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Interbank Risk Assessment – A Simulation Approach

We introduce a novel simulation-based network approach, which provides full-edged distributions of potential interbank losses. Based on those distributions we propose measures for (i) systemic importance of single banks, (ii) vulnerability of single banks, and (iii) vulnerability of the whole sector. The framework can be used for the calibration of macro-prudential capital charges, the assessment of systemic risks in the banking sector, and for the calculation of banks' interbank loss distributions in general. Our application to German regulatory data from End-2016 shows that the German interbank network was at that time in general resilient to the default of large banks, i.e. did not exhibit substantial contagion risk. Even though up to four contagion defaults could occur due to an exogenous shock, the system-wide 99.9% VaR barely exceeds 1.5% of banks' CET 1 capital. For single institutions, however, we found indications for elevated vulnerabilities and hence the need for a close supervision.

The Interbank Market Puzzle

This study documents significant differences in the interbank market lending and borrowing levels across countries. We argue that the existing differences in interbank market usage can be explained by the trust of the market participants in the stability of the country’s banking sector and counterparties, proxied by the history of banking crises and failures. Specifically, banks originating from a country that has lower level of trust tend to have lower interbank borrowing. Using a proprietary dataset on bilateral exposures, we investigate the Euro Area interbank network and find the effect of trust relies on the network structure of interbank markets. Core banks acting as interbank intermediaries in the network are more significantly influenced by trust in obtaining interbank funding, while being more exposed in a community can mitigate the negative effect of low trust. Country-level institutional factors might partially substitute for the limited trust and enhance interbank activity. JEL Classification: G01, G21, G28, D85

Optimal Network Compression

This paper introduces a formulation of the optimal network compression problem for financial systems. This general formulation is presented for different levels of network compression or rerouting allowed from the initial inter-bank network. We prove that this problem is, generically, NP-hard. We focus on objective functions generated by systemic risk measures under systematic shocks to the financial network. We conclude by studying the optimal compression problem for specific networks; this permits us to study the so-called robust fragility of certain network topologies more generally as well as the potential benefits and costs of network compression.

The Founding of the Federal Reserve, the Great Depression, and the Evolution of the U.S. Interbank Network

Financial network structure is an important determinant of systemic risk. This article examines how the U.S. interbank network evolved over a long and important period that included two key events: the founding of the Federal Reserve and the Great Depression. Banks established connections to correspondents that joined the Federal Reserve in cities with Fed offices, initially reducing overall network concentration. The network became even more focused on Fed cities during the Depression, as survival rates were higher for banks with more existing connections to Fed cities, and as survivors established new connections to those cities over time.

Financial contagion in inter-bank networks with overlapping portfolios

By considering overlapping portfolios among financial institutions, we construct a financial contagion model for inter-bank networks with two channels of contagion: counter-party risk and common asset holdings risk. Based on the model, we verify the contribution of overlapping portfolios to systemic risk contagion and further analyse how the degree of diversification and initial shock affect the probability, extent and loss degree of contagion in different network structures. The results show that as the degree of diversification increases, the probability, extent and loss degree show overall inverted U-shaped tendencies. Different from the existing research that focuses only on a single channel of risk contagion, we find that the risk contagion is significant because of the combined effect of counter-party risk and common asset holdings risk, even though there is little portfolio overlap. Additionally, we study the core–periphery network to investigate the particularity of systematically important financial institutions and the feedback effect in financial networks when banks proactively reduce the exposure of depreciating assets.

(In)Efficient Interbank Networks

AbstractWe study the efficiency properties of the formation of an interbank network. Banks face a trade‐off by establishing connections in the interbank market. On the one hand, banks improve the diversification of their liquidity risk and therefore can obtain a higher expected payoff. On the other hand, banks not sufficiently capitalized have risk‐shifting incentives that expose them to the risk of bankruptcy. Connecting to such risky banks negatively affects expected payoff. We show that both the optimal and the decentralized networks are characterized by a core‐periphery structure. The core is made of the safe banks, whereas the periphery is populated by the risky banks. Nevertheless, the two network structures coincide only if counterparty risk is sufficiently low. Otherwise, the decentralized network is underconnected as compared to the optimal one. Finally, we analyze mechanisms that can avoid the formation of inefficient interbank networks.

Do banking groups shape the network structure? Evidence from Turkish interbank market

Using a unique exposure data on Turkish banking system (disaggregated according to bank ownership structure and instrument level), we study the effects of ownership structure on the interbank network structure. During the sample period of 2003–2017, we observe that foreign and state deposit banks are the dominant institutions shaping the structure of the network under different contracts. Foreign banks, in particular, have a higher coreness vector in derivative exposures through their comparative advantage in offsetting derivative transactions. Moreover, our findings suggest that when foreign investors acquire domestic banks, the network structures of the acquired bank change considerably. We also present evidence that local and Basel III regulations play a significant role in the formation of the network structure through liquidity channel. We found highly liquid large banks and well-capitalized non-large banks have become more centralized in the interbank security market. The central bank's efforts to restore liquidity in the money markets during and after the global financial crisis seem to have increased the central role of foreign deposit banks in the overnight lending market against state and large private deposit banks.

The interbank payment network and financial system stability

Purpose The financial turbulence resulting from the global financial crisis sparked the interest in improving understanding of financial risks. The transmission of financial institution failures can be determined from the prevailing network structures between banks. The purpose of this study is to identify relationship between payment system network characteristics and financial system condition. Design/methodology/approach The characteristics of the interbank network structure in the payment system are identified using a graph theory and the relationship between the network characteristics of interbank transactions in the payment system and financial system stability is examined using a vector auto regression model. Findings This study shows that the connectedness of large-value payment transaction is more segmented compared to that of retail value payments. A significant relationship is observed between the characteristics of the network and the large-value payment transactions. Research limitations/implications This study found the connectedness of large-value transactions is more segmented when compared to retail-value transactions. It also shows a causal effect of the network characteristic on the financial system stability. Originality/value Unlike existing studies, this study considers both the connectedness in large-value transactions and retail-value transactions.

A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market

We propose a dynamic network model where two mechanisms control the probability of a link between two nodes: (i) the existence or absence of this link in the past, and (ii) node-specific latent variables (dynamic fitnesses) describing the propensity of each node to create links. Assuming a Markov dynamics for both mechanisms, we propose an Expectation-Maximization algorithm for model estimation and inference of the latent variables. The estimated parameters and fitnesses can be used to forecast the presence of a link in the future. We apply our methodology to the e-MID interbank network for which the two linkage mechanisms are associated with two different trading behaviors in the process of network formation, namely preferential trading and trading driven by node-specific characteristics. The empirical results allow to recognize preferential lending in the interbank market and indicate how a method that does not account for time-varying network topologies tends to overestimate preferential linkage.

Financial networks and systemic risk in China's banking system

The paper investigates the contagion effects and systemic risk in China's commercial banks system based on the balance sheet data. First, we quantify contagiousness and vulnerability for China's banking system without considering the detailed topology of interbank networks. Second, we estimate the detailed bilateral exposures matrix of the interbank network to examine the snowball effects of financial contagion. The simulation results from two alternative approaches are consistent. Both suggest that the contagious risk arising from an assumed bank failure is trivial, whereas the amplification effects of the losses due to the financial interlinkage are non-trivial.

Filtering for risk assessment of interbank network

Our paper contributes to the recent macroprudential policy addressing the resilience of financial systems in terms of their interconnectedness. We argue that beneath an interbank market, there is a fundamental latent network that affects the liquidity distributions among banks. To investigate the interbank market, we propose a framework that identifies such latent network using a statistical learning procedure. The framework reverse engineers overnight signals observed as banks conduct their reserve management on a daily basis. Our simulation-based results show that possible disruptions in funds supply are highly affected by the interconnectedness of the latent network. Hence, the proposed framework serves as an early warning system for regulators to monitor the overnight market and to detect ex-ante possible disruptions based on the inherent network characteristics.

Financial contagion in a core-periphery interbank network

ABSTRACTThis paper studies financial contagion in a core-periphery interbank network where core banks are large in balance sheet size while periphery banks are smaller and link only with the core banks. Core banks are all bilaterally linked and intermediate liquidity for periphery banks. We establish analytic conditions under which financial contagion propagates in the core-periphery network and examine the extent to which heterogeneity associated with size and number of banks affects these conditions. We show that the failure of core banks does not necessarily imply contagious failure of periphery banks; the core-periphery network structure exhibits a ‘robust-yet-fragile’ tendency with increased size of core banks; and the resilience of the network to contagion depends on the number of core banks, the number of periphery banks, and the level of interbank liquidity intermediated between the core banks. We also find that, under certain conditions, the core-periphery network is more resilient than the complete network with increased size of core banks.

The topology of indirect correlation networks formed by common assets

Evidence is provided that networks resulted from interbank loans have some common topological properties. As shown in this paper, indirect correlation networks formed by common assets have similar properties with interbank networks. On the basis of the systemic indirect correlation, the effects of investment behaviors, endogenous correlations among assets and fire sales of common assets are primarily tested in this paper. Then the indirect correlation network of banks is constructed and the planar maximally filtered graph is used to filter redundant information. The small world phenomenon, scale-free phenomenon and communities are found by analyzing indirect correlation networks. All the topological properties are also found on the real financial market according to the dataset from China. This observation provides a new perspective for regulators to promote the stability of banking system.