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Size and complexity in model financial systems

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Author Info

  • Arinaminpathy, Nimalan

    ()
    (Princeton University)

  • Kapadia, Sujit

    ()
    (Bank of England)

  • May, Robert

    ()
    (Oxford University)

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    Abstract

    The global financial crisis has precipitated an increasing appreciation of the need for a systemic perspective towards financial stability. For example: What role do large banks play in systemic risk? How should capital adequacy standards recognize this role? How is stability shaped by concentration and diversification in the financial system? We explore these questions using a deliberately simplified, dynamical model of a banking system which combines three different channels for direct spillovers from one bank to another: liquidity hoarding, asset price contagion, and the propagation of defaults via counterparty credit risk. Importantly, we also introduce a mechanism for capturing how swings in ‘confidence’ in the system may contribute to instability. Our results highlight that the importance of relatively large, well-connected banks in system stability scales more than proportionately with their size: the impact of their collapse arises not only from their connectivity, but also from their effect on confidence in the system. Imposing tougher capital requirements on larger banks than smaller ones can thus enhance the resilience of the system. Moreover, these effects are more pronounced in more concentrated systems, and continue to apply even when allowing for potential diversification benefits which may be realised by larger banks. We discuss some tentative implications for policy, as well as conceptual analogies in ecosystem stability, and in the control of infectious diseases.

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    Bibliographic Info

    Paper provided by Bank of England in its series Bank of England working papers with number 465.

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    Length: 37 pages
    Date of creation: 07 Oct 2012
    Date of revision:
    Handle: RePEc:boe:boeewp:0465

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    Related research

    Keywords: Systemic risk; financial crises; contagion; network models; liquidity risk; confidence;

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    References

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    1. Kartik Anand & Alan Kirman & Matteo Marsili, 2010. "Epidemics of rules, information aggregation failure and market crashes," Working Papers halshs-00545144, HAL.
    2. 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.
    3. Acharya, Viral V. & Skeie, David, 2011. "A model of liquidity hoarding and term premia in inter-bank markets," Journal of Monetary Economics, Elsevier, vol. 58(5), pages 436-447.
    4. Upper, Christian, 2011. "Simulation methods to assess the danger of contagion in interbank markets," Journal of Financial Stability, Elsevier, vol. 7(3), pages 111-125, August.
    5. Battiston, Stefano & Delli Gatti, Domenico & Gallegati, Mauro & Greenwald, Bruce & Stiglitz, Joseph E., 2012. "Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1121-1141.
    6. Nier, Erlend & Yang, Jing & Yorulmazer, Tanju & Alentorn, Amadeo, 2008. "Network models and financial stability," Bank of England working papers 346, Bank of England.
    7. Joseph G. Haubrich & Andrew W. Lo, 2013. "Quantifying Systemic Risk," NBER Books, National Bureau of Economic Research, Inc, number haub10-1.
    8. Wolf Wagner, 2011. "Systemic Liquidation Risk and the Diversity–Diversification Trade‐Off," Journal of Finance, American Finance Association, vol. 66(4), pages 1141-1175, 08.
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    Cited by:
    1. Toivanen, Mervi, 2013. "Contagion in the interbank network: An epidemiological approach," Research Discussion Papers 19/2013, Bank of Finland.
    2. Matthias Raddant, 2012. "Structure in the Italian Overnight Loan Market," Kiel Working Papers 1772, Kiel Institute for the World Economy.

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