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Estimating Global Bank Network Connectedness

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Listed author(s):
  • Mert Demirer
  • Francis X. Diebold
  • Laura Liu
  • Kamil Yılmaz

Abstract

We use LASSO methods to shrink, select and estimate the high-dimensional network linking the publicly-traded subset of the world's top 150 banks, 2003-2014. We characterize static network connectedness using full-sample estimation and dynamic network connectedness using rolling-window estimation. Statically, we find that global bank equity connectedness has a strong geographic component, whereas country sovereign bond connectedness does not. Dynamically, we find that equity connectedness increases during crises, with clear peaks during the Great Financial Crisis and each wave of the subsequent European Debt Crisis, and with movements coming mostly from changes in cross-country as opposed to within-country bank linkages.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 23140.

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Date of creation: Feb 2017
Handle: RePEc:nbr:nberwo:23140
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Find related papers by JEL classification:
  • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
  • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
  • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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  1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
  2. FrancisX. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, 01.
  3. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
  4. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
  5. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
  6. Matteo Barigozzi & Christian Brownlees, 2013. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona Graduate School of Economics.
  7. G.M. Constantinides & M. Harris & R. M. Stulz (ed.), 2013. "Handbook of the Economics of Finance," Handbook of the Economics of Finance, Elsevier, volume 2, number 2-b, December.
  8. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331, December.
  9. Gorton, Gary B., 2015. "The Maze of Banking: History, Theory, Crisis," OUP Catalogue, Oxford University Press, number 9780190204839, April.
  10. Viral Acharya & Robert Engle & Matthew Richardson, 2012. "Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks," American Economic Review, American Economic Association, vol. 102(3), pages 59-64, May.
  11. G.M. Constantinides & M. Harris & R. M. Stulz (ed.), 2013. "Handbook of the Economics of Finance," Handbook of the Economics of Finance, Elsevier, volume 2, number 2-a, December.
  12. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
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Cited by:

  1. Gorkem Bostanci & Kamil Yilmaz, 2015. "How Connected is the Global Sovereign Credit Risk Network?," Koç University-TUSIAD Economic Research Forum Working Papers 1515, Koc University-TUSIAD Economic Research Forum.
  2. Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian Nonparametric Sparse Seemingly Unrelated Regression Model (SUR)," Papers 1608.02740, arXiv.org, revised Dec 2016.
  3. Sachapon Tungsong & Fabio Caccioli & Tomaso Aste, 2017. "Relation between regional uncertainty spillovers in the global banking system," Papers 1702.05944, arXiv.org.
  4. Dungey, Mardi & Harvey, John & Volkov, Vladimir, 2017. "The changing international network of sovereign debt and financial institutions," Working Papers 2017-04, University of Tasmania, Tasmanian School of Business and Economics.

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