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The Complexity of Bank Holding Companies: A Topological Approach

机译:银行控股公司的复杂性:一种拓扑方法

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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.
机译:大型银行控股公司(BHC)构成了复杂的所有权层次结构,涉及数百甚至数千个法人实体。这些层次结构中的每个子公司都有自己的法律形式,资产,负债,管理目标和监管机构。如果BHC违约或破产,监管机构可能需要解决BHC及其组成实体。每个实体将分别需要现金注入,外部购买,与其他子公司合并,法律担保和彻底解散的某种组合。子公司当然不是孤立地解决,而是在层次结构顶部解决合并的BHC的情况下。因此,层次结构中子公司的数量,多样性和分布可以极大地简化解决方案或使其复杂化。我们提出了一组相关的指标,旨在评估BHC所有权图的复杂性。这些建议的度量标准着重于相对于子公司集合中某些明确确定的分区(例如,章程类型和监管权限)的商数。预期的措施以数学为基础,直观易懂且易于实施。我们通过对一个美国大型BHC的案例研究来说明这一过程。

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  • 来源
    《Working Paper Series》 |2017年第23755期|1-54qt001-qt001|共55页
  • 作者单位

    Department of the Treasury Office of Financial Research 290 Broadway New York, NY 10007;

    Johns Hopkins University Zanvyl Krieger School of Arts and Sciences Advanced Academics Programs 1717 Massachusetts Avenue, NY Washington, DC 20036;

    Kogod School of Business American University 4400 Massachusetts Avenue NW Washington, DC 20016 and NBER;

    Department of Mathematics 14 MacLean Hall University of Iowa Iowa City, IA 2242;

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