Funding Liquidity Risk in a Quantitative Model of Systemic Stability

Aikman, David; Alessandri, Piergiorgio; Eklund, Bruno; Gai, Prasanna; Kapadia, Sujit; Martin, Elizabeth; Mora, Nada; Sterne, Gabriel; Willison, Matthew

doi:10.2139/ssrn.1344287

Cited by 95 publications

(84 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In many cases, these links are simulated for different scenarios. For instance, the Bank of England uses risk transmission maps and feedback techniques to analyze financial crises (Bank of England, 2008;Aikman et al, 2009). Another such approach applies network theory to links in financial markets.…”

Section: Related Literaturementioning

confidence: 99%

Comparing Different Early Warning Systems: Results from a Horse Race Competition Among Members of the Macro-Prudential Research Network

et al. 2015

View full text Add to dashboard Cite

Over the recent decades researchers in academia and central banks have developed early warning systems (EWS) designed to warn policy makers of potential future economic and financial crises. These EWS are based on diverse approaches and empirical models. In this paper we compare the performance of nine distinct models for predicting banking crises resulting from the work of the Macroprudential Research Network (MaRs) initiated by the European System of Central Banks. In order to ensure comparability, all models use the same database of crises created by MaRs and comparable sets of potential early warning indicators. We evaluate the models' relative usefulness by comparing the ratios of false alarms and missed crises and discuss implications for pratical use and future research. We find that multivariate models, in their many appearances, have great potential added value over simple signalling models. One of the main policy recommendations coming from this exercise is that policy makers can benefit from taking a broad methodological approach when they develop models to set macro-prudential instruments.The obligatory copyright note: We certify that we have the right to deposit the contribution with MPRA.

show abstract

Section: Related Literaturementioning

confidence: 99%

Comparing Different Early Warning Systems: Results from a Horse Race Competition Among Members of the Macro-Prudential Research Network

et al. 2015

View full text Add to dashboard Cite

show abstract

“…There is branch of research in central banks which includes "network models" within a wider simulation framework, as in Boss et al (2006), Aikman et al (2009) Gauthier et al (2010b), Gauthier et al (2010a).…”

Section: Network Models and Systemic Riskmentioning

confidence: 99%

An empirical study of the Mexican banking system’s network and its implications for systemic risk

Martínez-Jaramillo

Alexandrova-Kabadjova

Bravo-Benítez

et al. 2014

Journal of Economic Dynamics and Control

186

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract: With the purpose of measuring and monitoring systemic risk, some topological properties of the interbank exposures and the payments system networks are studied. We propose non-topological measures which are useful to describe the individual behavior of banks in both networks. The evolution of such networks is also studied and some important conclusions from the systemic risks perspective are drawn. A unified measure of interconnectedness is also created. The main findings of this study are: the payments system network is strongly connected in contrast to the interbank exposures network; the type of exposures and payment size reveal different roles played by banks; behavior of banks in the exposures network changed considerably after Lehmans failure; interconnectedness of a bank, estimated by the unified measure, is not necessarily related with its assets size. Keywords: Systemic risk, financial networks, payment systems. JEL Classification: C01, C02, C44, C63, G21. Terms of use: Documents inResumen: Con el propósito de medir y monitorear el riesgo sistémico, se estudian algunas propiedades topológicas de las redes de exposiciones interbancarias y del sistema de pagos. Proponemos medidas no topológicas que sonútiles para describir el comportamiento individual de los bancos en ambas redes. La evolución de dichas redes también es estudiada y se extraen algunas conclusiones importantes desde la perspectiva del riesgo sistémico. También se crea una medida unificada de interconectividad. Los resultados principales de este estudio son: la red del sistema de pagos está fuertemente conectada en contraste con la red de exposiciones interbancarias; el tipo de exposiciones y el tamaño de los pagos revelan diferentes roles desempeñados por los bancos; el comportamiento de los bancos en la red de exposiciones cambió considerablemente después de la caída de Lehman; la interconectividad de un banco, estimada con la medida unificada, no necesariamente está relacionada con el tamaño de sus activos. Palabras Clave: Riesgo sistémico, redes financieras, sistemas de pagos.

show abstract

“…Assessment Model for Systemic Institutions, or RAMSI (Aikman et al 2009). In all of these cases, the initial trigger was relatively small in magnitude and local (for example, the Russian default in 1998 and news associated with mergers and acquisitions in 1987), but the crisis spread rapidly and globally to other markets.…”

Section: Introductionmentioning

confidence: 99%

Financial Amplification Mechanisms and the Federal Reserve's Supply of Liquidity During the Crisis

Sarkar

Shrader

2010

SSRN Journal

View full text Add to dashboard Cite

Funding Liquidity Risk in a Quantitative Model of Systemic Stability

Cited by 95 publications

References 5 publications

Comparing Different Early Warning Systems: Results from a Horse Race Competition Among Members of the Macro-Prudential Research Network

Comparing Different Early Warning Systems: Results from a Horse Race Competition Among Members of the Macro-Prudential Research Network

An empirical study of the Mexican banking system’s network and its implications for systemic risk

Financial Amplification Mechanisms and the Federal Reserve's Supply of Liquidity During the Crisis

Contact Info

Product

Resources

About