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The Complexity of Bank Holding Companies: A Topological Approach

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  • Mark D. Flood
  • Dror Y. Kenett
  • Robin L. Lumsdaine
  • Jonathan K. Simon

Abstract

Large bank holding companies (BHCs) are structured into intricate ownership hierarchies involving hundreds or even thousands of legal entities. Each subsidiary in these hierarchies has its own legal form, assets, liabilities, managerial goals, and supervisory authorities. In the event of BHC default or insolvency, regulators may need to resolve the BHC and its constituent entities. Each entity individually will require some mix of cash infusion, outside purchase, consolidation with other subsidiaries, legal guarantees, and outright dissolution. The subsidiaries are not resolved in isolation, of course, but in the context of resolving the consolidated BHC at the top of the hierarchy. The number, diversity, and distribution of subsidiaries within the hierarchy can therefore significantly ease or complicate the resolution process. We propose a set of related metrics intended to assess the complexity of the BHC ownership graph. These proposed metrics focus on the graph quotient relative to certain well identified partitions on the set of subsidiaries, such as charter type and regulatory jurisdiction. The intended measures are mathematically grounded, intuitively sensible, and easy to implement. We illustrate the process with a case study of one large U.S. BHC.

Suggested Citation

  • Mark D. Flood & Dror Y. Kenett & Robin L. Lumsdaine & Jonathan K. Simon, 2017. "The Complexity of Bank Holding Companies: A Topological Approach," NBER Working Papers 23755, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:23755
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    References listed on IDEAS

    as
    1. Robin L. Lumsdaine & Daniel N. Rockmore & Nicholas Foti & Gregory Leibon & J. Doyne Farmer, 2015. "The Intrafirm Complexity of Systemically Important Financial Institutions," Papers 1505.02305, arXiv.org.
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    3. Adam M. Kleinbaum & Toby E. Stuart & Michael L. Tushman, 2013. "Discretion Within Constraint: Homophily and Structure in a Formal Organization," Organization Science, INFORMS, vol. 24(5), pages 1316-1336, October.
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    7. Glasserman, Paul & Young, H. Peyton, 2016. "Contagion in financial networks," LSE Research Online Documents on Economics 68681, London School of Economics and Political Science, LSE Library.
    8. Paul Glasserman & H. Peyton Young, 2016. "Contagion in Financial Networks," Journal of Economic Literature, American Economic Association, vol. 54(3), pages 779-831, September.
    9. Cetorelli, Nicola & Goldberg, Linda S., 2014. "Measures of global bank complexity," Economic Policy Review, Federal Reserve Bank of New York, issue Dec, pages 107-126.
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    More about this item

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • 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
    • G3 - Financial Economics - - Corporate Finance and Governance
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure

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