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Financial Stability and Interacting Networks of Financial Institutions and Market Infrastructures

Author

Listed:
  • León, C.

    (Tilburg University, School of Economics and Management)

  • Berndsen, R.J.

    (Tilburg University, School of Economics and Management)

  • Renneboog, L.D.R.

    (Tilburg University, School of Economics and Management)

Abstract

An interacting network coupling financial institutions’ multiplex (i.e. multi-layer) and financial market infrastructures’ single-layer networks gives an accurate picture of a financial system’s true connective architecture. We examine and compare the main properties of Colombian multiplex and interacting financial networks. Coupling financial institutions’ multiplex networks with financial market infrastructures’ networks removes modularity, which augments financial instability because the network then fails to isolate feedbacks and limit cascades while it retains its robust-yet-fragile features. Moreover, our analysis highlights the relevance of infrastructure-related systemic risk, corresponding to the effects caused by the improper functioning of FMIs or by FMIs acting as conduits for contagion.
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Suggested Citation

  • León, C. & Berndsen, R.J. & Renneboog, L.D.R., 2014. "Financial Stability and Interacting Networks of Financial Institutions and Market Infrastructures," Other publications TiSEM ec673981-aa01-48f9-9553-d, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:ec673981-aa01-48f9-9553-d92cb5995048
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    Cited by:

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    2. Li, Fuchun & Perez-Saiz, Hector, 2018. "Measuring systemic risk across financial market infrastructures," Journal of Financial Stability, Elsevier, vol. 34(C), pages 1-11.
    3. Poledna, Sebastian & Molina-Borboa, José Luis & Martínez-Jaramillo, Serafín & van der Leij, Marco & Thurner, Stefan, 2015. "The multi-layer network nature of systemic risk and its implications for the costs of financial crises," Journal of Financial Stability, Elsevier, vol. 20(C), pages 70-81.
    4. Fuchun Li & Héctor Pérez Saiz, 2016. "Measuring Systemic Risk Across Financial Market Infrastructures," Staff Working Papers 16-10, Bank of Canada.
    5. Kyriaki Tsilika, 2024. "A Mathematica-Based Interface for the Exploration of Inter- and Intra-Regional Financial Flows," Mathematics, MDPI, vol. 12(6), pages 1-15, March.
    6. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    7. Bartesaghi, Paolo & Clemente, Gian Paolo & Grassi, Rosanna & Luu, Duc Thi, 2022. "The multilayer architecture of the global input-output network and its properties," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 304-341.
    8. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto Calogero, 2017. "Estimation and model-based combination of causality networks," SAFE Working Paper Series 165, Leibniz Institute for Financial Research SAFE.
    9. Poledna, Sebastian & Martínez-Jaramillo, Serafín & Caccioli, Fabio & Thurner, Stefan, 2021. "Quantification of systemic risk from overlapping portfolios in the financial system," Journal of Financial Stability, Elsevier, vol. 52(C).
    10. Sebastian Poledna & Abraham Hinteregger & Stefan Thurner, 2018. "Identifying systemically important companies in the entire liability network of a small open economy," Papers 1801.10487, arXiv.org.
    11. Cuba, Walter & Rodriguez-Martinez, Anahi & Chavez, Diego A. & Caccioli, Fabio & Martinez-Jaramillo, Serafin, 2021. "A network characterization of the interbank exposures in Peru," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(3).
    12. 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).
    13. George Halkos & Shunsuke Managi & Kyriaki Tsilika, 2021. "Ranking Countries and Geographical Regions in the International Green Bond Transfer Network: A Computational Weighted Network Approach," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1301-1346, December.

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    More about this item

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation

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