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Centrality-based Capital Allocations

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  • Adrian Alter
  • Ben R. Craig
  • Peter Raupach

Abstract

This paper looks at the effect of capital rules on a banking system that is connected through correlated credit exposures and interbank lending. Keeping total capital in the system constant, the reallocation rules, which combine individual bank characteristics and interconnectivity measures of interbank lending, are to minimize a measure of systemwide losses. Using the detailed German Credit Register for estimation, we find that capital rules based on eigenvectors dominate any other centrality measure, saving about 15 percent in expected bankruptcy costs.

Suggested Citation

  • Adrian Alter & Ben R. Craig & Peter Raupach, 2015. "Centrality-based Capital Allocations," Working Papers (Old Series) 1501, Federal Reserve Bank of Cleveland.
    • Handle: RePEc:fip:fedcwp:1501
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    Cited by:

    1. Gabrielle Demange, 2018. "Contagion in Financial Networks: A Threat Index," Management Science, INFORMS, vol. 64(2), pages 955-970, February.
    2. Christoph Siebenbrunner, 2017. "Clearing algorithms and network centrality," Papers 1706.00284, arXiv.org.
    3. Sylvain Benoit & Jean-Edouard Colliard & Christophe Hurlin & Christophe Pérignon, 2017. "Where the Risks Lie: A Survey on Systemic Risk," Review of Finance, European Finance Association, vol. 21(1), pages 109-152.
    4. Murat Cakir, 2017. "A conceptual design of "what and how should a proper macro-prudential policy framework be?" A globalistic approach to systemic risk and procuring the data needed," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Uses of central balance sheet data offices' information, volume 45, Bank for International Settlements.
    5. Julia Müller & Thorsten Upmann, 2017. "Eigenvalue Productivity: Measurement of Individual Contributions in Teams," CESifo Working Paper Series 6679, CESifo.
    6. Marco Bardoscia & Ginestra Bianconi & Gerardo Ferrara, 2019. "Multiplex network analysis of the UK over‐the‐counter derivatives market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1520-1544, October.
    7. Gabriele Galati & Richhild Moessner, 2018. "What Do We Know About the Effects of Macroprudential Policy?," Economica, London School of Economics and Political Science, vol. 85(340), pages 735-770, October.
    8. Thibaut PIQUARD & Dilyara SALAKHOVA, 2018. "Macroprudential policy instruments: a bulwark against interbank contagion risk [Les instruments de politique macroprudentielle : un rempart contre les risques de contagion interbancaire]," Bulletin de la Banque de France, Banque de France, issue 218.
    9. Fricke, Daniel & Wilke, Hannes, 2020. "Connected funds," Discussion Papers 48/2020, Deutsche Bundesbank.
    10. Fink, Kilian & Krüger, Ulrich & Meller, Barbara & Wong, Lui-Hsian, 2016. "The credit quality channel: Modeling contagion in the interbank market," Journal of Financial Stability, Elsevier, vol. 25(C), pages 83-97.
    11. Torri, Gabriele & Giacometti, Rosella & Paterlini, Sandra, 2018. "Robust and sparse banking network estimation," European Journal of Operational Research, Elsevier, vol. 270(1), pages 51-65.
    12. Betz, Frank & Hautsch, Nikolaus & Peltonen, Tuomas A. & Schienle, Melanie, 2016. "Systemic risk spillovers in the European banking and sovereign network," Journal of Financial Stability, Elsevier, vol. 25(C), pages 206-224.
    13. Ms. Camelia Minoiu & Mr. Tümer Kapan & Galina Hale, 2016. "Crisis Transmission in the Global Banking Network," IMF Working Papers 2016/091, International Monetary Fund.
    14. Diem, Christian & Pichler, Anton & Thurner, Stefan, 2020. "What is the minimal systemic risk in financial exposure networks?," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    15. Paul Glasserman & Peyton Young, 2015. "Contagion in Financial Networks," Economics Series Working Papers 764, University of Oxford, Department of Economics.
    16. Berlinger, Edina & Dömötör, Barbara & Daróczi, Gergely & Vadász, Tamás, 2017. "Pénzügyi hálózatok mag-periféria szerkezete. A magyar bankközi fedezetlen hitelek piaca, 2003-2012 [The core periphery structure of financial networks: investigating Hungary s interbank deposit mar," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(11), pages 1160-1185.
    17. Paul Glasserman & H. Peyton Young, 2015. "Contagion in Financial Markets," Working Papers 15-21, Office of Financial Research, US Department of the Treasury.
    18. Fukker, Gábor & Kok, Christoffer, 2021. "On the optimal control of interbank contagion in the euro area banking system," Working Paper Series 2554, European Central Bank.
    19. Paul Glasserman & H. Peyton Young, 2016. "Contagion in Financial Networks," Journal of Economic Literature, American Economic Association, vol. 54(3), pages 779-831, September.
    20. Marco Bardoscia & Paolo Barucca & Stefano Battiston & Fabio Caccioli & Giulio Cimini & Diego Garlaschelli & Fabio Saracco & Tiziano Squartini & Guido Caldarelli, 2021. "The Physics of Financial Networks," Papers 2103.05623, arXiv.org.

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    More about this item

    Keywords

    interbank connectivity; credit exposures; capital requirements; banking system; bank contagion; network centrality measure; bankruptcy costs; systemic risk;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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