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Liquidity requirements and payment delays - participant type dependent preferences

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  • Schulz, Christian

Abstract

The paper presents an analysis of the trade-offs of participants of different type between payment delay and liquidity requirement on the basis of synthetically generated data. The generation of the synthetic transaction data set for a simple RTGS system is described and calibrated using real world parameters. The payment system is simulated for various liquidity levels and it is shown that participants of different size in terms of transaction volume and value will have different optimal liquidity requirements, as the payment delays they face for each liquidity level will be different. This is shown using indifference curves between payment delay and liquidity requirements. JEL Classification: C15, C5, E58, L14, L41, L51

Suggested Citation

  • Schulz, Christian, 2011. "Liquidity requirements and payment delays - participant type dependent preferences," Working Paper Series 1291, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20111291
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    References listed on IDEAS

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    1. Fujiki, Hiroshi & Green, Edward J. & Yamazaki, Akira, 2008. "Incentive efficient risk sharing in a settlement mechanism," Journal of Economic Theory, Elsevier, vol. 142(1), pages 178-195, September.
    2. C. H. Furfine, 1999. "Interbank exposures: quantifying the risk of contagion," BIS Working Papers 70, Bank for International Settlements.
    3. 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.
    4. Docherty, Peter & Wang, Gehong, 2010. "Using synthetic data to evaluate the impact of RTGS on systemic risk in the Australian payments system," Journal of Financial Stability, Elsevier, vol. 6(2), pages 103-117, June.
    5. 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.
    6. Neil Wallace, 2000. "Knowledge of individual histories and optimal payment arrangements," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Sum, pages 11-21.
    7. Arco van Oord & Howie Lin, 2005. "Molling Inter- and Intraday Payment Flows," DNB Working Papers 074, Netherlands Central Bank, Research Department.
    8. Elisabeth Ledrut, 2007. "Simulating retaliation in payment systems: Can banks control their exposure to a failing participant?," DNB Working Papers 133, Netherlands Central Bank, Research Department.
    9. Ronald Heijmans, 2009. "Simulations in the Dutch interbank payment system: A sensitivity analysis," DNB Working Papers 199, Netherlands Central Bank, Research Department.
    10. C. H. Furfine, 1999. "The pricing of bank lending and borrowing: evidence from the federal funds market," BIS Working Papers 62, Bank for International Settlements.
    11. Craig Furfine, 1999. "Interbank exposures: quantifying the risk of contagion," Proceedings 633, Federal Reserve Bank of Chicago.
    12. Bank of Japan, 2001. "Real-Time Gross Settlement (RTGS) in Japan: An Evaluation of the First Six Months," Bank of Japan Research Papers 2001-11-01, Bank of Japan.
    13. Manning, Mark & Nier, Erlend & Schanz, Jochen (ed.), 2009. "The Economics of Large-value Payments and Settlement: Theory and Policy Issues for Central Banks," OUP Catalogue, Oxford University Press, number 9780199571116.
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    Cited by:

    1. Soramäki, Kimmo & Cook, Samantha, 2012. "Algorithm for identifying systemically important banks in payment systems," Economics Discussion Papers 2012-43, Kiel Institute for the World Economy (IfW).
    2. Soramäki, Kimmo & Cook, Samantha, 2013. "SinkRank: An algorithm for identifying systemically important banks in payment systems," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 7, pages 1-27.

    More about this item

    Keywords

    competition; data generation; oversight; payment system; simulation;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation

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