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Which bank is the \\"central\\" bank? an application of Markov theory to the Canadian Large Value Transfer System

Author

Listed:
  • Morten L. Bech
  • James T. E. Chapman
  • Rod Garratt

Abstract

Recently, economists have argued that a bank's importance within the financial system depends not only on its individual characteristics but also on its position within the banking network. A bank is deemed to be \\"central\\" if, based on our network analysis, it is predicted to hold the most liquidity. In this paper, we use a method similar to Google's PageRank procedure to rank banks in the Canadian Large Value Transfer System (LVTS). In doing so, we obtain estimates of the payment processing speeds for the individual banks. These differences in processing speeds are essential for explaining why observed daily distributions of liquidity differ from the initial distributions, which are determined by the credit limits selected by banks.

Suggested Citation

  • Morten L. Bech & James T. E. Chapman & Rod Garratt, 2008. "Which bank is the \\"central\\" bank? an application of Markov theory to the Canadian Large Value Transfer System," Staff Reports 356, Federal Reserve Bank of New York.
    • Handle: RePEc:fip:fednsr:356
    Note: For a published version of this report, see Morten L. Bech, James T. E. Chapman, and Rod Garratt, "Which Bank Is the 'Central' Bank?" Journal of Monetary Economics 57, no. 3 (April 2010): 352-63.
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    References listed on IDEAS

    as
    1. Michael Boss & Helmut Elsinger & Martin Summer & Stefan Thurner, 2004. "An Empirical Analysis of the Network Structure of the Austrian Interbank Market," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 7, pages 77-87.
    2. Morten L. Bech & Rodney J. Garratt, 2012. "Illiquidity in the Interbank Payment System Following Wide‐Scale Disruptions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(5), pages 903-929, August.
    3. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
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    Cited by:

    1. Sean O'Connor & James Chapman & Kirby Millar, 2008. "Liquidity Efficiency and Distribution in the LVTS: Non-Neutrality of System Changes under Network Asymmetry," Discussion Papers 08-11, Bank of Canada.
    2. Monica Billio & Mila Getmansky & Andrew W. Lo & Loriana Pelizzon, 2010. "Econometric Measures of Systemic Risk in the Finance and Insurance Sectors," NBER Working Papers 16223, National Bureau of Economic Research, Inc.
    3. B. Craig & D. Salakhova & M. Saldias, 2018. "Payments delay: propagation and punishment," Working papers 671, Banque de France.
    4. Mr. Jorge A Chan-Lau, 2010. "Balance Sheet Network Analysis of Too-Connected-to-Fail Risk in Global and Domestic Banking Systems," IMF Working Papers 2010/107, International Monetary Fund.

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    More about this item

    Keywords

    network; federal funds; money markets; interbank; topology;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

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