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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
  • Claudia Biancotti
  • Leandro D'Aurizio
  • Claudio Impenna

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.

Suggested Citation

  • Luca Arciero & Claudia Biancotti & Leandro D'Aurizio & Claudio Impenna, 2009. "Exploring Agent-Based Methods for the Analysis of Payment Systems: A Crisis Model for StarLogo TNG," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-2.
    • Handle: RePEc:jas:jasssj:2008-12-2
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    1. repec:zbw:bofism:2005_031 is not listed on IDEAS
    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, vol. 8(Nov), pages 59-79.
    3. 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.
    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. Nigel Gilbert & Pietro Terna, 2000. "How to build and use agent-based models in social science," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 1(1), pages 57-72, March.
    6. Bech, Morten L. & Garratt, Rod, 2003. "The intraday liquidity management game," Journal of Economic Theory, Elsevier, vol. 109(2), pages 198-219, April.
    7. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871.
    8. Angelo Baglioni & Andrea Monticini, 2008. "The Intraday Price of Money: Evidence from the e‐MID Interbank Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(7), pages 1533-1540, October.
    9. Furfine, Craig H, 2001. "Banks as Monitors of Other Banks: Evidence from the Overnight Federal Funds Market," The Journal of Business, University of Chicago Press, vol. 74(1), pages 33-57, January.
    10. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521839198.
    11. 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.
    12. Craig H. Furfine, 2003. "When is inter-transaction time informative?," Working Paper Series WP-03-04, Federal Reserve Bank of Chicago.
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    Cited by:

    1. Office of Financial Research (ed.), 2012. "Office of Financial Research 2012 Annual Report," Reports, Office of Financial Research, US Department of the Treasury, number 12-1.
    2. Krug, Sebastian & Wohltmann, Hans-Werner, 2016. "Shadow banking, financial regulation and animal spirits: An ACE approach," Economics Working Papers 2016-08, Christian-Albrechts-University of Kiel, Department of Economics.
    3. Richard Bookstaber, 2012. "Using Agent-Based Models for Analyzing Threats to Financial Stability," Working Papers 12-03, Office of Financial Research, US Department of the Treasury.
    4. Krug, Sebastian, 2018. "The interaction between monetary and macroprudential policy: Should central banks 'lean against the wind' to foster macro-financial stability?," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-69.
    5. Paulick, Jan & Berndsen, Ron & Diehl, Martin & Heijmans, Ronald, 2021. "No more Tears without Tiers? The Impact of Indirect Settlement on liquidity use in TARGET2," Other publications TiSEM 57477131-2199-46bf-a2f1-5, Tilburg University, School of Economics and Management.
    6. Leonardo dos Santos Pinheiro & Flavio Codeco COelho, 2017. "An Agent-based Model of Contagion in Financial Networks," Papers 1703.07513, arXiv.org.
    7. Krug, Sebastian, 2015. "The interaction between monetary and macroprudential policy: Should central banks "lean against the wind" to foster macrofinancial stability?," Economics Working Papers 2015-08, Christian-Albrechts-University of Kiel, Department of Economics.
    8. Pablo S. Castro & Ajit Desai & Han Du & Rodney Garratt & Francisco Rivadeneyra, 2021. "Estimating Policy Functions in Payments Systems Using Reinforcement Learning," Staff Working Papers 21-7, Bank of Canada.

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    More about this item

    Keywords

    Agent-Based Modeling; Payment Systems; RTGS; Liquidity; Crisis Simulation;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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