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Congestion and cascades in payment systems

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  • Walter E. Beyeler
  • Robert J. Glass
  • Morten L. Bech
  • Kimmo Soramaki

Abstract

We develop a parsimonious model of the interbank payment system to study congestion and the role of liquidity markets in alleviating congestion. The model incorporates an endogenous instruction arrival process, scale-free topology of payments between banks, fixed total liquidity that limits banks' capacity to process arriving instructions, and a global market that distributes liquidity. We find that at low liquidity, the system becomes congested and payment settlement loses correlation with payment instruction arrival, becoming coupled across the network. The onset of congestion is evidently related to the relative values of three characteristic times: the time for banks' net position to return to zero, the time for banks to exhaust their liquidity endowments, and the liquidity market relaxation time. In the congested regime, settlement takes place in cascades having a characteristic size. A global liquidity market substantially diminishes congestion, requiring only a small fraction of the payment-induced liquidity flow to achieve strong beneficial effects.

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Bibliographic Info

Paper provided by Federal Reserve Bank of New York in its series Staff Reports with number 259.

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Date of creation: 2006
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Handle: RePEc:fip:fednsr:259

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Keywords: Payment systems ; Bank liquidity ; International liquidity;

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References

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  1. Soramäki, Kimmo & Bech, Morten L. & Arnold, Jeffrey & Glass, Robert J. & Beyeler, Walter E., 2007. "The topology of interbank payment flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 317-333.
  2. James J. McAndrews & Simon M. Potter, 2002. "Liquidity effects of the events of September 11, 2001," Economic Policy Review, Federal Reserve Bank of New York, issue Nov, pages 59-79.
  3. Anna Nagurney & Jose Cruz, 2004. "Dynamics of international financial networks with risk management," Quantitative Finance, Taylor & Francis Journals, vol. 4(3), pages 276-291.
  4. Bech, Morten L. & Garratt, Rod, 2003. "The intraday liquidity management game," Journal of Economic Theory, Elsevier, vol. 109(2), pages 198-219, April.
  5. Ponzi, A. & Aizawa, Y., 2000. "Evolutionary financial market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 507-523.
  6. Adrian Dragulescu & Victor M. Yakovenko, 2000. "Statistical mechanics of money," Papers cond-mat/0001432, arXiv.org, revised Aug 2000.
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Citations

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Cited by:
  1. Galbiati, Marco & Soramaki, Kimmo, 2010. "Liquidity-saving mechanisms and bank behaviour," Bank of England working papers 400, Bank of England.
  2. Olivier Armantier & Jeffrey Arnold & James McAndrews, 2008. "Changes in the timing distribution of Fedwire funds transfers," Economic Policy Review, Federal Reserve Bank of New York, issue Sep, pages 83-112.
  3. Galbiati, Marco & Soramäki, Kimmo, 2011. "An agent-based model of payment systems," Journal of Economic Dynamics and Control, Elsevier, vol. 35(6), pages 859-875, June.
  4. Perlin, Marcelo & Schanz, Jochen, 2011. "System-wide liquidity risk in the United Kingdom’s large-value payment system: an empirical analysis," Bank of England working papers 427, Bank of England.
  5. Kei Imakubo & Yutaka Soejima, 2010. "The Microstructure of Japanfs Interbank Money Market: Simulating Contagion of Intraday Flow of Funds Using BOJ-NET Payment Data," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 28, pages 151-180, November.
  6. Huberto M. Ennis & John A. Weinberg, 2007. "Interest on reserves and daylight credit," Economic Quarterly, Federal Reserve Bank of Richmond, issue Spr, pages 111-142.
  7. Maeno, Yoshiharu, 2013. "Transient fluctuation of the prosperity of firms in a network economy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3351-3359.
  8. Denbee, Edward & Norman, Ben, 2010. "The impact of payment splitting on liquidity requirements in RTGS," Bank of England working papers 404, Bank of England.
  9. Soramäki, Kimmo & Cook, Samantha, 2012. "Algorithm for identifying systemically important banks in payment systems," Economics Discussion Papers 2012-43, Kiel Institute for the World Economy.

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