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An agent-based model of payment systems

Author

Listed:
  • Galbiati, Marco

    () (Bank of England)

  • Soramaki, Kimmo

    () (Helsinki University of Technology)

Abstract

This paper lays out and simulates a multi-agent, multi-period model of an RTGS payment system. At the beginning of the day, banks choose how much costly liquidity to allocate to the settlement process. Then, they use it to execute an exogenous, random stream of payment orders. If a bank's liquidity stock is depleted, payments are queued until new liquidity arrives from other banks, imposing costs on the delaying bank. The paper studies the equilibrium level of liquidity posted in the system, performing some comparative statics and obtaining: i) a liquidity demand curve which links liquidity to delay costs and ii) insights on the efficiency of alternative system configurations.

Suggested Citation

  • Galbiati, Marco & Soramaki, Kimmo, 2008. "An agent-based model of payment systems," Bank of England working papers 352, Bank of England.
  • Handle: RePEc:boe:boeewp:0352
    as

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    References listed on IDEAS

    as
    1. Kahn, Charles M & Roberds, William, 1998. "Payment System Settlement and Bank Incentives," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 845-870.
    2. Devriese, Johan & Mitchell, Janet, 2005. "Liquidity Risk in Securities Settlement," CEPR Discussion Papers 5123, C.E.P.R. Discussion Papers.
    3. Angelini, Paolo, 1998. "An analysis of competitive externalities in gross settlement systems," Journal of Banking & Finance, Elsevier, vol. 22(1), pages 1-18, January.
    4. Simon Buckle & Erin Campbell, 2003. "Settlement bank behaviour and throughput rules in an RTGS payment system with collateralised intraday credit," Bank of England working papers 209, Bank of England.
    5. Kukushkin, Nikolai S., 2004. "Best response dynamics in finite games with additive aggregation," Games and Economic Behavior, Elsevier, vol. 48(1), pages 94-110, July.
    6. 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.
    7. Tesfatsion, Leigh, 2001. "Introduction to the special issue on agent-based computational economics," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 281-293, March.
    8. Bech, Morten L. & Garratt, Rod, 2003. "The intraday liquidity management game," Journal of Economic Theory, Elsevier, vol. 109(2), pages 198-219, April.
    9. Beyeler, Walter E. & Glass, Robert J. & Bech, Morten L. & Soramäki, Kimmo, 2007. "Congestion and cascades in payment systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 693-718.
    10. Leinonen, Harry, 2005. "Liquidity, risks and speed in payment and settlement systems : a simulation approach," Scientific Monographs, Bank of Finland, number 2005_031, December.
    11. John P. Jackson & Mark J. Manning, 2007. "Central Bank intraday collateral policy and implications for tiering in rtgs payment systems," DNB Working Papers 129, Netherlands Central Bank, Research Department.
    12. Chakravorti, Sujit, 2000. "Analysis of systemic risk in multilateral net settlement systems," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 10(1), pages 9-30, January.
    13. Dindos, Martin & Mezzetti, Claudio, 2006. "Better-reply dynamics and global convergence to Nash equilibrium in aggregative games," Games and Economic Behavior, Elsevier, vol. 54(2), pages 261-292, February.
    14. Morten L. Bech & Rodney J. Garratt, 2012. "Illiquidity in the Interbank Payment System Following Wide‐Scale Disruptions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(5), pages 903-929, August.
    15. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, January.
    16. Marco Galbiati & Simone Giansante, 2010. "Emergence of networks in large value payment systems (LVPSs)," Department of Economic Policy, Finance and Development (DEPFID) University of Siena 0110, Department of Economic Policy, Finance and Development (DEPFID), University of Siena.
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    More about this item

    Keywords

    Payment systems; liquidity; RTGS; agent-based modelling; learning; fictitious play.;

    JEL classification:

    • C79 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Other

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