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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.

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  • 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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    Cited by:

    1. Lumsdaine, R.L. & Rockmore, D.N. & Foti, N.J. & Leibon, G. & Farmer, J.D., 2021. "The intrafirm complexity of systemically important financial institutions," Journal of Financial Stability, Elsevier, vol. 52(C).
    2. Tembo Nakamoto & Abhijit Chakraborty & Yuichi Ikeda, 2019. "Identification of Key Companies for International Profit Shifting in the Global Ownership Network," Papers 1904.12397, arXiv.org.
    3. Abad, Jorge & D’Errico, Marco & Killeen, Neill & Luz, Vera & Peltonen, Tuomas & Portes, Richard & Urbano, Teresa, 2022. "Mapping exposures of EU banks to the global shadow banking system," Journal of Banking & Finance, Elsevier, vol. 134(C).
    4. León, Carlos, 2021. "The dawn of a mobile payment scheme: The case of Movii," Working papers 78, Red Investigadores de Economía.
    5. Correa, Ricardo & Goldberg, Linda S., 2022. "Bank complexity, governance, and risk," Journal of Banking & Finance, Elsevier, vol. 134(C).
    6. Cao, Jin & Juelsrud, Ragnar E., 2022. "Opacity and risk-taking: Evidence from Norway," Journal of Banking & Finance, Elsevier, vol. 134(C).
    7. Claudia M. Buch & Linda S. Goldberg, 2021. "Complexity and Riskiness of Banking Organizations: Evidence from the International Banking Research Network," Staff Reports 966, Federal Reserve Bank of New York.
    8. Brunetti, Celso & Harris, Jeffrey H. & Mankad, Shawn, 2023. "Networks, interconnectedness, and interbank information asymmetry," Journal of Financial Stability, Elsevier, vol. 67(C).
    9. Gai, Prasanna & Kemp, Malcolm & Sánchez Serrano, Antonio & Schnabel, Isabel, 2019. "Regulatory complexity and the quest for robust regulation," Report of the Advisory Scientific Committee 8, European Systemic Risk Board.
    10. Aldasoro, Iñaki & Hardy, Bryan & Jager, Maximilian, 2022. "The Janus face of bank geographic complexity," Journal of Banking & Finance, Elsevier, vol. 134(C).
    11. León, Carlos, 2021. "The adoption of a mobile payment system: the user perspective," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(4).

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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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