Systemic loops and liquidity regulation (original) (raw)
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We simulate interbank market contagion, enriching the standard transmission channel based on credit losses and capital, with new channels like funding liquidity losses, …re assets sales and active liquidity runs on infected banks, employing a testing dataset of Russian bilateral interbank exposures. Allowing active liquidity runs on infected banks is crucial to capture reality with the simulations. We use the simulations to calculate a bank's potential contribution to contagion, which serves as our measure of systemic importance. We …nd that the K-shell index, a new measure of interconnectedness, is the only robust and reliable predictor of a individual bank's potential to spread contagion, rather than size. Coreness should therefore not be confounded with size.
Bank Networks: Contagion, Systemic Risk and Prudential Policy
We present a network model of the interbank market in which optimizing risk averse banks lend to each other and invest in non-liquid assets. Market clearing takes place through a tâtonnement process which yields the equilibrium price, while traded quantities are determined by means of a matching algorithm. Contagion occurs through liquidity hoarding, interbank interlinkages and fire sale externalities. The resulting network configuration exhibits a coreperiphery structure, dis-assortative behavior and low density. Within this framework we analyze the effects of prudential policies on the stability/efficiency trade-off. Liquidity requirements unequivocally decrease systemic risk but at the cost of lower efficiency (measured by aggregate investment in non-liquid assets). Equity requirements tend to reduce risk (hence increase stability) without reducing significantly overall investment.
Banks and Their Contagion Potential: How Stable Is Banking System?
Lecture Notes in Economics and Mathematical Systems, 2013
We measure contagion potential and stability of banking system on a randomized version of the credit contagion model by Steinbacher M, Steinbacher M, Steinbacher M (2012) Credit contagion in financial markets: a network-based approach. Available via SSRN. http://papers.ssrn.com/sol3/papers.cfm?abstract id= 2068716. Cited 30 Jan 2013. We introduce two estimators of the contagion potential of banks (liquidity-loss potential and˛-criticality index (Steinbacher M, Steinbacher M, Steinbacher M (2012) Credit contagion in financial markets: a network-based approach. Available via SSRN. http://papers.ssrn.com/sol3/papers. cfm?abstract id=2068716. Cited 30 Jan 2013)) and introduce Shannon's entropy as a stability estimator. Our approach is systemic in that it enables an overall estimation of the capacity of the banking system to provide liquidity. Mechanism developed can be employed for measuring systemic risk of banking system as a whole. Schweitzer et al. [15] acknowledge that We need an approach that stresses the systemic complexity [.. . ] that can be used to revise and extend established paradigms in economic theory.
Systemic risk propagation and distress in bank networks
2017
Stability of the banking system and macro-prudential regulation are essential for healthy economic growth. In this paper we study the European bank network and its vulnerability to stressing different bank assets. The importance of macro-prudential policy is emphasized by the inherent vulnerability of the financial system, high level of leverage, interconnectivity of system’s entities, similar risk exposure of financial institutions, and susceptibility for systemic crisis propagation through the system. Current stress tests conducted by the European Banking Authority do not take in consideration the connectivity of the banks and the potential of one bank vulnerability spilling over to the rest of the system. We create a bipartite network with bank nodes on one hand and asset nodes on the other with weighted links between the two layers based on the level of different countries’ sovereign debt holdings by each bank. We propose a model for systemic risk propagation based on common ban...
Liquidity risk and contagion in interbank markets: a presentation of Allen and Gale Model
The paper analyzes liquidity risk and contagion in interbank markets. The aim of the research is to define the different structures of interbank markets and structures that allow the better allocation of liquidity and thus avoid the spread of crisis in the whole system. For this purpose, this paper examines Allen and Gale model. This model is the pioneer model in the management of liquidity risk in the interbank market. We will then analyze the mechanisms that explain the spread of liquidity risk in the banking system both at national and international level.
Interconnected Banks and Systemically Important Exposures
Journal of Economic Dynamics and Control, 2021
We study the interplay between two channels of interconnectedness in the banking system. The first one is a direct interconnectedness, via a network of interbank loans, banks' loans to other corporate and retail clients, and securities holdings. The second channel is an indirect interconnectedness, via exposures to common asset classes. To this end, we analyze a unique supervisory data set collected by the European Central Bank that covers 26 large banks in the euro area. To assess the impact of contagion, we apply a structural valuation model NEVA (Barucca et al., 2016a), in which common shocks to banks' external assets are reflected in a consistent way in the market value of banks' mutual liabilities through the network of obligations. We identify a strongly non-linear relationship between diversification of exposures, shock size, and losses due to interbank contagion. Moreover, the most systemically important sectors tend to be the households and the financial sectors of larger countries because of their size and position in the financial network. Finally, we provide policy insights into the potential impact of more diversified versus more domestic portfolio allocation strategies on the propagation of contagion, which are relevant to the policy discussion on the European Capital Market Union.
Systemic Risk and Network Formation in the Interbank Market
2011
We propose a novel mechanism to facilitate understanding of systemic risk in financial markets. The literature on systemic risk has focused on two mechanisms, common shocks and domino-like sequential default. Our approach is a formal model that provides an intellectual combination of the two by looking at how shocks propagate through a network of interconnected banks. Transmission in our model is not based on default. Instead, we provide a simple microfoundation of banks' profitability based on classic competition incentives. As competitors lending quantities change, both for closely connected ones and the whole market, banks adjust their own lending decisions as a result, generating a 'transmission' of shocks through the system. We provide a unique equilibrium characterization of a static model, and embed this model into a full dynamic model of network formation with n agents. Because we have an explicit characterization of equilibrium behavior, we have a tractable way to bring the model to the data. Indeed, our measures of systemic risk capture the propagation of shocks in a wide variety of contexts; that is, it can explain the pattern of behavior both in good times as well as in crisis. . We are very grateful to Carefin -Bocconi Centre for Applied Research in Finance for financial support. Cohen-Cole also thanks the CIBER and the US Department of Education for support. All remaining errors are our own. 1 A general perception and intuition has emerged that the interconnectedness of financial institutions is potentially as crucial as their size. Recent papers that emphasize such interconnectedness or try to explain it include Allen, Babus and Carletti (2010), Cohen-Cole, Patacchini (2010), Boyson, Stahel and, ). 2 In a creative expansion of this theory, Allen, Babus and Carletti (2010) illustrate how the accumulation of exposure to these shocks depends on the incentives for individual banks to diversify holdings. 3 Indeed, even prior to the crisis there is a wide range of research on the importance of interbank markets, including some that address the systemic risk inherent to these markets. Some examples include Freixas, Parigi and Rochet (
Modeling and Mathematical Analysis of Liquidity Risk Contagion in the Banking System
Journal of Applied Mathematics
In recent times, all world banks have been threatened by the liquidity risk problem. This phenomenon represents a devastating financial threat to banks and may lead to irrecoverable consequences in case of negligence or underestimation. In this article, we study a mathematical model that describes the contagion of liquidity risk in the banking system based on the SIR epidemic model simulation. The model consists of three ordinary differential equations illustrating the interaction between banks susceptible or affected by liquidity risk and tending towards bankruptcy. We have demonstrated the bornness and positivity of the solutions, and we have mathematically analyzed this system to demonstrate how to control the banking system’s stability. Numerical simulations have been illustrated by using real data to support the analytical results and prove the effects of different system parameters studied on the contagion of liquidity risk.
Epidemics of Liquidity Shortages in Interbank Markets
Financial contagion from liquidity shocks has being recently ascribed as a prominent driver of systemic risk in interbank lending markets. Building on standard compartment models used in epidemics, here we develop an EDB (Exposed-Distressed-Bankrupted) model for the dynamics of liquidity shocks reverberation between banks, and validate it on electronic market for interbank deposits data. We show that the interbank network was highly susceptible to liquidity contagion at the beginning of the 2007/2008 global financial crisis, and that the subsequent micro-prudential and liquidity hoarding policies adopted by banks increased the network resilience to systemic risk—yet with the undesired side effect of drying out liquidity from the market. We finally show that the individual riskiness of a bank is better captured by its network centrality than by its participation to the market, along with the currently debated concept of " too interconnected to fail " .
A Dynamic Network Model of Interbank Lending Systemic Risk and Liquidity Provisioning
SSRN Electronic Journal, 2017
We develop a dynamic model of interbank borrowing and lending activities in which banks are organized into clusters, and adjust their monetary reserve levels to meet prescribed capital requirements. Each bank has its own initial monetary reserve level and faces idiosyncratic risks characterized by an independent Brownian motion; whereas system wide, the banks form a hierarchical structure of clusters. We model the interbank transactional dynamics through a set of interacting measure-valued processes. Each individual process describes the intra-cluster borrowing/lending activities, and the interactions among the processes capture the inter-cluster financial transactions. We establish the weak limit of the interacting measure-valued processes as the number of banks in the system grows large. We then use the weak limit to develop asymptotic approximations of two proposed macro-measures, the liquidity stress index and the concentration index, both capturing the dynamics of systemic risk. We use numerical examples to illustrate the applications of the asymptotics and conduct related sensitivity analysis with respect to various indicators of financial activity.