Liquidity Risk, Cash-Flow Constraints and Systemic Feedbacks

Kapadia, Sujit; Drehmann, Mathias; Elliott, John A.; Sterne, Gabriel

doi:10.2139/ssrn.2093439

Cited by 25 publications

(29 citation statements)

References 23 publications

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“…Examples include Kapadia, Drehmann, Elliott, and Sterne (2009) and Brunnermeier and Pedersen (2009).…”

Section: Illiquidity Measuresmentioning

confidence: 99%

“…Others have focused on more specific mechanisms, including imbalances (Caballero, 2009), correlated exposures (Acharya, Pedersen, Philippon, and Richardson, 2010), spillovers to the real economy (Group of Ten, 2001), information disruptions (Mishkin, 2007), feedback behavior (Kapadia, Drehmann, Elliott, and Sterne, 2009), asset bubbles (Rosengren, 2010), contagion (Moussa, 2011), and negative externalities (Financial Stability Board, 2009). …”

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confidence: 99%

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A Survey of Systemic Risk Analytics

Bisias

Flood²,

et al. 2012

SSRN Journal

324

249

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The Office of Financial Research (OFR) Working Paper Series allows staff and their co-authors to disseminate preliminary research findings in a format intended to generate discussion and critical comments. Papers in the OFR Working Paper Series are works in progress and subject to revision. We provide a survey of 31 quantitative measures of systemic risk in the economics and finance literature, chosen to span key themes and issues in systemic risk measurement and management. We motivate these measures from the supervisory, research, and data perspectives in the main text, and present concise definitions of each risk measure-including required inputs, expected outputs, and data requirements-in an extensive appendix. To encourage experimentation and innovation among as broad an audience as possible, we have developed open-source Matlab code for most of the analytics surveyed, which can be accessed through the Office of Financial Research (OFR) at http://www.treasury.gov/ofr.

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“…Examples include Kapadia, Drehmann, Elliott, and Sterne (2009) and Brunnermeier and Pedersen (2009).…”

Section: Illiquidity Measuresmentioning

confidence: 99%

mentioning

confidence: 99%

A Survey of Systemic Risk Analytics

Bisias

Flood²,

et al. 2012

SSRN Journal

324

249

View full text Add to dashboard Cite

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“…It can create or deepen liquidity problems of banks which were dependent on these loans. So liquidity hoarding may improve one bank´s liquidity position but at the expense of other banks (Kapadia et al, 2012;Acharya and Merrouche, 2013).…”

Section: Bank Liquidity and Interbank Marketsmentioning

confidence: 99%

To Lend or to Borrow on the Interbank Market: What Matters for Commercial Banks in the Visegrad Countries

Vodová¹

2015

Prague Economic Papers

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Abstract:The aim of this paper is to fi nd out determinants which aff ect the commercial banks´ decision to lend on the interbank market in the Visegrad countries. The data cover the period from 2000 to 2011. The net interbank position of individual banking sectors signifi cantly diff ers. Results of the probit model showed that banks´ decision to lend in interbank market is determined both by bank-specifi c and macroeconomic factors. Bank liquidity, capital adequacy and quality of the loan portfolio are important bank-specifi c factors. Growth rate of the gross domestic products, unemployment rate, fi nancial crisis and level of interest rates matter among macroeconomic factors. Although the Visegrad countries have a lot in common, diff erent factors determined the banks´ decision in individual countries. Moreover, the direction of infl uence of some factors may also diff er.

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“…Interbank loans have a range of maturities, from overnight to a matter of years, and may often be renewed, or rolled over, at the point of maturity. A pronounced feature of the 2007/2008 crisis was that, as the system deteriorated, banks stopped lending to each other at all but the shortest maturities (7,29). The bankruptcy of Lehman Brothers in September 2008 transmitted distress further across the financial network, and signaled that there was no guarantee of government support for institutions in distress.…”

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confidence: 99%

Size and complexity in model financial systems

Arinaminpathy

Kapadia

May

2012

Proc. Natl. Acad. Sci. U.S.A.

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110

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The global financial crisis has precipitated an increasing appreciation of the need for a systemic perspective toward financial stability. For example: What role do large banks play in systemic risk? How should capital adequacy standards recognize this role? How is stability shaped by concentration and diversification in the financial system? We explore these questions using a deliberately simplified, dynamic model of a banking system that combines three different channels for direct transmission of contagion from one bank to another: liquidity hoarding, asset price contagion, and the propagation of defaults via counterparty credit risk. Importantly, we also introduce a mechanism for capturing how swings in "confidence" in the system may contribute to instability. Our results highlight that the importance of relatively large, well-connected banks in system stability scales more than proportionately with their size: the impact of their collapse arises not only from their connectivity, but also from their effect on confidence in the system. Imposing tougher capital requirements on larger banks than smaller ones can thus enhance the resilience of the system. Moreover, these effects are more pronounced in more concentrated systems, and continue to apply, even when allowing for potential diversification benefits that may be realized by larger banks. We discuss some tentative implications for policy, as well as conceptual analogies in ecosystem stability and in the control of infectious diseases.A lthough global financial systems have seen considerable growth in size, concentration, and complexity over the past few decades (1), our understanding of the dynamic behavior of such systems has not necessarily kept pace. Indeed, the current financial crisis has presented a stark demonstration of the potential for modern financial systems to amplify and disseminate financial distress on a global scale. From a regulatory perspective, these events have prompted fresh interest in understanding financial stability from a system level. In particular, although precrisis regulation (as typified by the Basel II accords) sought to minimize the risk of failure of individual banks irrespective of systemic importance, new regulation will seek to target the systemic consequences of bank collapse as well. To quote Haldane and May (2), "What matters is not a bank's closeness to the edge of the cliff; it is the extent of the fall."In this context, a clear feature of interest is the presence of large, highly connected banks. These banks have conceptual parallels in biology: simple models have been influential in underlining the importance of "superspreaders" in the spread and control of infectious diseases (3, 4), and "keystone" species are thought to serve a valuable role in ecosystem stability (5, 6). Here we develop dynamic models to apply and extend these lessons to financial systems. Our approach is theoretical, and our models necessarily oversimplified. Nonetheless, by considering transmission mechanisms specific to modern financial sy...

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Liquidity Risk, Cash-Flow Constraints and Systemic Feedbacks

Cited by 25 publications

References 23 publications

A Survey of Systemic Risk Analytics

A Survey of Systemic Risk Analytics

To Lend or to Borrow on the Interbank Market: What Matters for Commercial Banks in the Visegrad Countries

Size and complexity in model financial systems

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