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On the Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms

  • Francis X. Diebold
  • Kamil Yilmaz

We propose several connectedness measures built from pieces of variance decompositions, and we argue that they provide natural and insightful measures of connectedness among financial asset returns and volatilities. We also show that variance decompositions define weighted, directed networks, so that our connectedness measures are intimately-related to key measures of connectedness used in the network literature. Building on these insights, we track both average and daily time-varying connectedness of major U.S. financial institutions' stock return volatilities in recent years, including during the financial crisis of 2007-2008.

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File URL: http://www.nber.org/papers/w17490.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 17490.

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Date of creation: Oct 2011
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Publication status: published as Diebold, F.X. and Yilmaz, K. (2014), "On the Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms," Journal of Econometrics, 182, 119-134.
Handle: RePEc:nbr:nberwo:17490
Note: AP EFG IFM
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  1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
  2. 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.
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  6. Francis X. Diebold & Kamil Yilmaz, 2010. "Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 1001, Koc University-TUSIAD Economic Research Forum, revised Mar 2010.
  7. Francis X. Diebold & Kamil Yilmaz, 2007. "Measuring Financial Asset Return and Volatility Spillovers, With Application to Global Equity Markets," PIER Working Paper Archive 07-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  8. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2010. "Measuring systemic risk," Working Paper 1002, Federal Reserve Bank of Cleveland.
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  13. Viral V. Acharya, 2010. "Measuring systemic risk," Proceedings 1140, Federal Reserve Bank of Chicago.
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  17. repec:taf:jnlbes:v:30:y:2012:i:2:p:212-228 is not listed on IDEAS
  18. Allen, F. & Babus, A. & Carletti, E., 2010. "Financial Connections and Systemic Risk," Discussion Paper 2010-88S, Tilburg University, Center for Economic Research.
  19. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331.
  20. repec:fip:fedhpr:y:2010:i:may:p:65-71 is not listed on IDEAS
  21. Wolfgang Karl Härdle & Ostap Okhrin & Yarema Okhrin, 2010. "Time varying Hierarchical Archimedean Copulae," SFB 649 Discussion Papers SFB649DP2010-018, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  22. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
  23. Jean-Marie Dufour & Abderrahim Taamouti, 2008. "Short and long run causality measures: theory and inference," Economics Working Papers we083720, Universidad Carlos III, Departamento de Economía.
  24. Hansen, Peter R. & Lunde, Asger, 2014. "Estimating The Persistence And The Autocorrelation Function Of A Time Series That Is Measured With Error," Econometric Theory, Cambridge University Press, vol. 30(01), pages 60-93, February.
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