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Exploring Agent-Based Methods for the Analysis of Payment Systems: A Crisis Model for StarLogo TNG

  • Luca Arciero

    ()

  • Claudia Biancotti

    ()

  • Leandro D'Aurizio

    ()

  • Claudio Impenna

    ()

This paper presents an exploratory agent-based model of a real time gross settlement (RTGS) payment system. Banks are represented as agents who exchange payment requests, which are then settled according to a set of simple rules. The model features the main elements of a real-life system, including a central bank acting as liquidity provider, and a simplified money market. A simulation exercise using synthetic data of BI-REL (the Italian RTGS) predicts the macroscopic impact of a disruptive event on the flow of interbank payments. In our reduced-scale system, three hypothetical distinct phases emerge after the disruptive event: 1) a liquidity sink effect is generated and the participants\' liquidity expectations turn out to be excessive; 2) an illusory thickening of the money market follows, along with increased payment delays; and, finally 3) defaulted obligations dramatically rise. The banks cannot staunch the losses accruing on defaults, even after they become fully aware of the critical event, and a scenario emerges in which it might be necessary for the central bank to step in as liquidity provider.

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File URL: http://jasss.soc.surrey.ac.uk/12/1/2/2.pdf
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Article provided by Journal of Artificial Societies and Social Simulation in its journal Journal of Artificial Societies and Social Simulation.

Volume (Year): 12 (2009)
Issue (Month): 1 ()
Pages: 2

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Handle: RePEc:jas:jasssj:2008-12-2
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  1. Michael Boss & Helmut Elsinger & Martin Summer & Stefan Thurner, 2004. "Network topology of the interbank market," Quantitative Finance, Taylor & Francis Journals, vol. 4(6), pages 677-684.
  2. 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.
  3. 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.
  4. Sheri Markose & Amadeo Alentorn & Stephen Millard & Jing Yang, 2011. "Designing large value payment systems: An agent-based approach," Economics Discussion Papers 700, University of Essex, Department of Economics.
  5. 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.
  6. Nigel Gilbert & Pietro Terna, 2000. "How to build and use agent-based models in social science," Mind and Society: Cognitive Studies in Economics and Social Sciences, Fondazione Rosselli, vol. 1(1), pages 57-72, March.
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