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Ranking systemically important financial institutions

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We propose a simple network–based methodology for ranking systemically important financial institutions. We view the risks of firms –including both the financial sector and the real economy– as a network with nodes representing the volatility shocks. The metric for the connections of the nodes is the correlation between these shocks. Daily dynamic centrality measures allow us to rank firms in terms of risk connectedness and firm characteristics. We present a general systemic risk index for the financial sector. Results from applying this approach to all firms in the S&P500 for 2003–2011 are twofold. First, Bank of America, JP Morgan and Wells Fargo are consistently in the top 10 throughout the sample. Citigroup and Lehman Brothers also were consistently in the top 10 up to late 2008. At the end of the sample, insurance firms emerge as systemic. Second, the systemic risk in the financial sector built–up from early 2005, peaked in September 2008, and greatly reduced after the introduction of TARP and the rescue of AIG. Anxiety about European debt markets saw the systemic risk begin to rise again from April 2010. We further decompose these results to find that the systemic risk of insurance and deposit– taking institutions differs importantly, the latter experienced a decline from late 2007, in line with the burst of the housing price bubble, while the former continued to climb up to the rescue of AIG.

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  • Dungey, Mardi & Luciani, Matteo & Veredas, David, 2012. "Ranking systemically important financial institutions," Working Papers 15473, University of Tasmania, Tasmanian School of Business and Economics, revised 21 Nov 2012.
  • Handle: RePEc:tas:wpaper:15473
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    Cited by:

    1. Matteo Barigozzi & Christian Brownlees, 2019. "NETS: Network estimation for time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 347-364, April.
    2. Mardi Dungey & Matteo Luciani & David Veredas, 2012. "Ranking Systemically Important Financial Institutions," CAMA Working Papers 2012-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Mardi Dungey & Moses Kangogo & Vladimir Volkov, 2022. "Dynamic effects of network exposure on equity markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 569-629, December.
    4. Dahlqvist, Carl-Henrik & Gnabo, Jean-Yves, 2018. "Effective network inference through multivariate information transfer estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 376-394.
    5. Ahelegbey, Daniel Felix, 2015. "The Econometrics of Bayesian Graphical Models: A Review With Financial Application," MPRA Paper 92634, University Library of Munich, Germany, revised 25 Apr 2016.
    6. Vitali Alexeev & Mardi Dungey, 2015. "Equity portfolio diversification with high frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1205-1215, July.
    7. Masciantonio, Sergio, 2013. "Identifying, ranking and tracking systemically important financial institutions (SIFIs), from a global, EU and Eurozone perspective," MPRA Paper 46788, University Library of Munich, Germany.
    8. 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.
    9. Kleinow, Jacob & Moreira, Fernando, 2016. "Systemic risk among European banks: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 27-42.
    10. Yao, Wenying & Tian, Jing, 2015. "The role of intra-day volatility pattern in jump detection: empirical evidence on how financial markets respond to macroeconomic news announcements," Working Papers 2015-05, University of Tasmania, Tasmanian School of Business and Economics.
    11. 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.
    12. Vitali Alexeev & Katja Ignatieva, 2021. "Biases in variance of decomposed portfolio returns," International Review of Finance, International Review of Finance Ltd., vol. 21(4), pages 1152-1178, December.
    13. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
    14. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2014. "Identifying periods of financial stress in Asian currencies: the role of high frequency financial market data," Working Papers 2014-12, University of Tasmania, Tasmanian School of Business and Economics.
    15. Jerzy Korczak & Maria Sasin & Dorota Janiszewska, 2021. "Smart Logistics Infrastructure in Peripheral Region," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 4), pages 535-548.
    16. Stefano Gurciullo, 2014. "Stess-testing the system: Financial shock contagion in the realm of uncertainty," Papers 1412.1679, arXiv.org.
    17. Jacob Kleinow & Tobias Nell, 2015. "Determinants of systemically important banks: the case of Europe," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 7(4), pages 446-476, November.
    18. Jacob Kleinow & Andreas Horsch & Mario Garcia-Molina, 2017. "Factors driving systemic risk of banks in Latin America," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(2), pages 211-234, April.
    19. Daniel Felix Ahelegbey, 2015. "The Econometrics of Networks: A Review," Working Papers 2015:13, Department of Economics, University of Venice "Ca' Foscari".

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    More about this item

    Keywords

    Systemic risk; ranking; financial institutions; Lehman;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation

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