Systemic Importance Index for financial institutions: A Principal Component Analysis approach
AbstractAs a result of the most recent global financial crisis literature has embraced size, connectedness and substitutability as key indicators for financial institutions’ systemic importance. Despite the intuitiveness of these concepts, identifying systemic important institutions remain a non-trivial task that implies two primary challenges. First, designing metrics for connectedness and substitutability may require, as acknowledged by literature, non-standard data sources and techniques. Second, choosing a methodology capable of aggregating the metrics designed for the three aforementioned concepts into a systemic importance index may be intricate. The herein paper addresses the second challenge. The chosen approach is to apply Principal Components Analysis to the metrics designed by León and Machado (2011) for assessing size, connectedness and substitutability, where those metrics rely on a combination of balance sheet data and the application of network theory to large-value payment system’s information. Results (i) demonstrate that the three concepts and their metrics are explanatory and non-redundant for differentiating financial institutions’ relative systemic importance; (ii) allow for constructing a PCA-based Systemic Importance Index, a valuable tool for financial authorities’ policy and decision-making; and (iii) confirm the importance of the too-connected-to-fail criteria and the presence of non-banking firms among the most systemically important financial institutions in the Colombian case.
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Bibliographic InfoPaper provided by Banco de la Republica de Colombia in its series Borradores de Economia with number 741.
Date of creation: Oct 2012
Date of revision:
Systemic Importance; Systemic Risk; Principal Components Analysis; Too-connected-to-fail; Too-big-to-fail. Classification JEL: D85; C63; E58; G28;
Other versions of this item:
- Carlos Eduardo León & Andrés Murcia, 2012. "Systemic Importance Index for financial institutions: A Principal Component Analysis approach," BORRADORES DE ECONOMIA 010067, BANCO DE LA REPÚBLICA.
- D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
- G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-11-03 (All new papers)
- NEP-BAN-2012-11-03 (Banking)
- NEP-CBA-2012-11-03 (Central Banking)
- NEP-RMG-2012-11-03 (Risk Management)
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- carlos León & Ron J. Berndsen, 2013.
"Modular scale-free architecture of Colombian financial networks: Evidence and challenges with financial stability in view,"
Borradores de Economia
799, Banco de la Republica de Colombia.
- Carlos León & Ron J. Berndsen, 2013. "Modular scale-free architecture of Colombian financial networks: Evidence and challenges with financial stability in view," BORRADORES DE ECONOMIA 011104, BANCO DE LA REPÚBLICA.
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