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Exploring agent-based methods for the analysis of payment systems: a crisis model for StarLogo TNG

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  • Luca Arciero

    ()
    (Bank of Italy)

  • Claudia Biancotti

    ()
    (Bank of Italy)

  • Leandro DÂ’Aurizio

    ()
    (Bank of Italy)

  • Claudio Impenna

    ()
    (Bank of Italy)

Abstract

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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Bibliographic Info

Paper provided by Bank of Italy, Economic Research and International Relations Area in its series Temi di discussione (Economic working papers) with number 686.

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Date of creation: Aug 2008
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Handle: RePEc:bdi:wptemi:td_686_08

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Keywords: agent-based modeling; payment systems; RTGS; liquidity; crisis simulation Abstract: 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 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. The main advantage of agent - based modeling is that we can dynamically see what happens to the major variables involved. 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. The methodology presented differs from traditional payment systems simulations featuring deterministic streams of payments dealt with in a centralized manner with static behavior on the part of banks. The paper is within a recent stream of empirical research that attempts to model RTGS with agent – based techniques.;

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  1. Bech, Morten L. & Garratt, Rod, 2003. "The intraday liquidity management game," Journal of Economic Theory, Elsevier, vol. 109(2), pages 198-219, April.
  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. 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.
  4. Jing Yang & Sheri Markose & Amadeo Alentorn, 2005. "Designing large value payment systems: an agent based approach," Computing in Economics and Finance 2005 396, Society for Computational Economics.
  5. 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.
  6. 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.
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