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Congestion and cascades in payment systems

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

Abstract

We develop a parsimonious model of the interbank payment system. The model incorporates an endogenous instruction arrival process, a scale-free topology of payments between banks, a fixed total liquidity which 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 0, the time for a bank to exhaust its liquidity endowment, and the liquidity market relaxation time. In the congested regime settlement takes place in cascades having a characteristic length scale. A global liquidity market substantially attenuates congestion, requiring only a small fraction of the payment-induced liquidity flow to achieve strong beneficial effects.

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Bibliographic Info

Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 384 (2007)
Issue (Month): 2 ()
Pages: 693-718

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Handle: RePEc:eee:phsmap:v:384:y:2007:i:2:p:693-718

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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

Related research

Keywords: Network; Topology; Interbank; Payment; Money market; Sandpile model; Congestion;

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References

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  1. Adrian Dragulescu & Victor M. Yakovenko, 2000. "Statistical mechanics of money," Papers cond-mat/0001432, arXiv.org, revised Aug 2000.
  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. Kimmo Soramaki & Morten L. Bech & Jeffrey Arnold & Robert J. Glass & Walter Beyeler, 2006. "The topology of interbank payment flows," Staff Reports 243, Federal Reserve Bank of New York.
  5. Bech, Morten L. & Garratt, Rod, 2001. "The Intraday Liquidity Management Game," University of California at Santa Barbara, Economics Working Paper Series qt0m6035wg, Department of Economics, UC Santa Barbara.
  6. Anna Nagurney & Ke Ke & Jose Cruz & Kitty Hancock & Frank Southworth, 2002. "Dynamics of supply chains: a multilevel (logistical – informational – financial) network perspective," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 29(6), pages 795-818, November.
  7. Ponzi, A. & Aizawa, Y., 2000. "Evolutionary financial market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 507-523.
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Citations

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Cited by:
  1. Galbiati, Marco & Soramaki, Kimmo, 2008. "An agent-based model of payment systems," Bank of England working papers 352, Bank of England.
  2. Denbee, Edward & Norman, Ben, 2010. "The impact of payment splitting on liquidity requirements in RTGS," Bank of England working papers 404, Bank of England.
  3. Galbiati, Marco & Soramaki, Kimmo, 2010. "Liquidity-saving mechanisms and bank behaviour," Bank of England working papers 400, Bank of England.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.

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