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Interbank Exposure Networks

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  • Sam Langfield
  • Kimmo Soramäki

Abstract

Financial institutions are highly interconnected. Consequently, they form complex systems which are inherently unstable. This paper reviews empirical research on the instability of complex interbank systems. Three network approaches are distinguished: descriptions of interbank exposure networks; simulation and modelling; and the development of new metrics to describe network topology and individual banks’ relative importance. The paper concludes by inferring policy implications and priorities for future research. Copyright Springer Science+Business Media New York 2016

Suggested Citation

  • Sam Langfield & Kimmo Soramäki, 2016. "Interbank Exposure Networks," Computational Economics, Springer;Society for Computational Economics, vol. 47(1), pages 3-17, January.
    • Handle: RePEc:kap:compec:v:47:y:2016:i:1:p:3-17
    DOI: 10.1007/s10614-014-9443-x
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    3. Xingxing Ye & Raphael Douady, 2018. "Systemic Risk Indicators Based on Nonlinear PolyModel," JRFM, MDPI, vol. 12(1), pages 1-24, December.
    4. Ahelegbey, Daniel Felix & Giudici, Paolo & Hashem, Shatha Qamhieh, 2021. "Network VAR models to measure financial contagion," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    5. Pierre Nkou Mananga & Shiqiang Lin & Hairui Zhang, 2023. "A network approach to interbank contagion risk in South Africa," Working Papers 11052, South African Reserve Bank.
    6. Yun, Tae-Sub & Jeong, Deokjong & Park, Sunyoung, 2019. "“Too central to fail” systemic risk measure using PageRank algorithm," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 251-272.
    7. Lai, Yujie & Hu, Yibo, 2021. "A study of systemic risk of global stock markets under COVID-19 based on complex financial networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    8. I�aki Aldasoro & Ignazio Angeloni, 2015. "Input-output-based measures of systemic importance," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 589-606, April.
    9. Liang He & Shouwei Li, 2017. "Network Entropy and Systemic Risk in Dynamic Banking Systems," Complexity, Hindawi, vol. 2017, pages 1-7, November.
    10. Zappa, Paola & Vu, Duy Q., 2021. "Markets as networks evolving step by step: Relational Event Models for the interbank market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    11. Huang, Wei-Qiang & Wang, Dan, 2018. "A return spillover network perspective analysis of Chinese financial institutions’ systemic importance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 405-421.
    12. Hüser, Anne-Caroline, 2016. "Too interconnected to fail: A survey of the Interbank Networks literature," SAFE Working Paper Series 91, Leibniz Institute for Financial Research SAFE, revised 2016.
    13. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARS," Working Papers ECARES ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    14. Huang, Wei-Qiang & Wang, Dan, 2018. "Systemic importance analysis of chinese financial institutions based on volatility spillover network," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 19-30.

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