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Designing large value payment systems: an agent based approach

Author

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  • Jing Yang
  • Sheri Markose
  • Amadeo Alentorn

Abstract

In this paper, we report on the main building blocks of an ongoing project to develop a computational agent-based simulator for a generic real-time large-value interbank payment system with a central processor that can implement different rules for payment settlement. The main types of payment system in their polar forms are Real Time Gross Settlement (RTGS) and Deferred Net Settlement (DNS). DNS generates large quantities of settlement risk; in contrast, the elimination of settlement risk in RTGS comes with excessive demands for liquidity on banks. This could lead them to adopt various delaying tactics to minimise liquidity needs with free-riding and other ‘bad’ equilibria as potential outcomes. The introduction of hybrid systems with real-time netting is viewed as a means by which liquidity costs can be reduced while settlement risk is unchanged. Proposed reforms for settlement rules make it imperative to have a methodology to assess the efficiency of the different variants along three dimensions: the cost of liquidity to the individual banks and the system as a whole, settlement risk at both bank and system levels, and how early in the day payments are processed, since this proxies the impact of an operational incident. In this paper, we build a simulator for interbank payments capable of handling real time payment records along with autonomous bank behaviour and show that it can be used to evaluate different payment system designs against these three criteria

Suggested Citation

  • 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.
    • Handle: RePEc:sce:scecf5:396
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    Cited by:

    1. Sheri M Markose, 2013. "Systemic risk analytics: A data-driven multi-agent financial network (MAFN) approach," Journal of Banking Regulation, Palgrave Macmillan, vol. 14(3-4), pages 285-305, July.
    2. 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.
    3. Bartolini, Leonardo & Hilton, Spence & McAndrews, James J., 2010. "Settlement delays in the money market," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 934-945, May.
    4. Sepahvand , Mehrdad, 2011. "Intraday Liquidity Demand of Banks in Real-Time Gross Settlement System," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 6(1), pages 151-160, October.

    More about this item

    Keywords

    Agent based modeling; Real Time Gross Settlement; Deferred Net Settlement; Agent-based simulation; Payment Concentration; Liquidity; Systemic Risk;
    All these keywords.

    JEL classification:

    • H30 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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