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Congestion and cascades in payment systems

Author

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

Suggested Citation

  • Morten L. Bech & Walter E. Beyeler & Robert J. Glass & Kimmo Soramaki, 2006. "Congestion and cascades in payment systems," Staff Reports 259, Federal Reserve Bank of New York.
    • Handle: RePEc:fip:fednsr:259
    Note: For a published version of this report, see Walter E. Beyeler, Robert J. Glass, Morten Bech, and Kimmo Soramäki, "Congestion and Cascades in Payment Systems," Physica A: Statistical Mechanics and Its Applications 384, no. 2 (October 2007): 693-718.
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. 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.
    2. Leinonen, Harry, 2009. "Simulation analyses and stress testing of payment networks," Scientific Monographs, Bank of Finland, number 2009_042.
    3. Galbiati, Marco & Soramaki, Kimmo, 2010. "Liquidity-saving mechanisms and bank behaviour," Bank of England working papers 400, Bank of England.
    4. 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.
    5. Denbee, Edward & Norman, Ben, 2010. "The impact of payment splitting on liquidity requirements in RTGS," Bank of England working papers 404, Bank of England.
    6. Huberto M. Ennis & John A. Weinberg, 2007. "Interest on reserves and daylight credit," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 93(Spr), pages 111-142.
    7. 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 (IfW).
    8. Norman, Ben, 2010. "Financial Stability Paper No 7: Liquidity Saving in Real-Time Gross Settlement Systems - an Overview," Bank of England Financial Stability Papers 7, Bank of England.
    9. Olivier Armantier & Jeffrey Arnold & James J. McAndrews, 2008. "Changes in the timing distribution of Fedwire funds transfers," Economic Policy Review, Federal Reserve Bank of New York, vol. 14(Sep), pages 83-112.
    10. De Caux, Robert & Brede, Markus & McGroarty, Frank, 2016. "Payment prioritisation and liquidity risk in collateralised interbank payment systems," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 41(C), pages 139-150.
    11. Massimiliano Zanin & David Papo & Miguel Romance & Regino Criado & Santiago Moral, 2016. "The topology of card transaction money flows," Papers 1605.04938, arXiv.org.
    12. Marina Resta, 2016. "Enhancing Self‐Organizing Map Capabilities with Graph Clustering: An Application to Financial Markets," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(1-2), pages 21-46, January.
    13. L. C. G. Rogers & L. A. M. Veraart, 2013. "Failure and Rescue in an Interbank Network," Management Science, INFORMS, vol. 59(4), pages 882-898, April.
    14. Ball, Alan & Denbee, Edward & Manning, Mark & Wetherilt, Anne, 2011. "Financial Stability Paper No 11: Intraday Liquidity - Risk and Regulation," Bank of England Financial Stability Papers 11, Bank of England.
    15. Kei Imakubo & Yutaka Soejima, 2010. "The Microstructure of Japan's 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.

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    More about this item

    Keywords

    network; topology; interbank; payment; money market; sandpile model; congestion;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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