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

  • Francis X. Diebold

    ()

    (Department of Economics, University of Pennsylvania)

  • Kamil Yılmaz

    ()

    (Department of Economics, Koç University)

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://economics.sas.upenn.edu/system/files/11-031.pdf
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Paper provided by Penn Institute for Economic Research, Department of Economics, University of Pennsylvania in its series PIER Working Paper Archive with number 11-031.

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Length: 36 pages
Date of creation: 30 Sep 2011
Date of revision:
Handle: RePEc:pen:papers:11-031
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  1. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2011. "Financial Network Systemic Risk Contributions," SFB 649 Discussion Papers SFB649DP2011-072, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  2. Pesaran, M. H. & Shin, Y., 1997. "Generalised Impulse Response Analysis in Linear Multivariate Models," Cambridge Working Papers in Economics 9710, Faculty of Economics, University of Cambridge.
  3. Marcella Lucchetta & Gianni De Nicolo, 2012. "Systemic Real and Financial Risks; Measurement, Forecasting, and Stress Testing," IMF Working Papers 12/58, International Monetary Fund.
  4. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  5. Peter R. Hansen & Asger Lunde, 2010. "Estimating the Persistence and the Autocorrelation Function of a Time Series that is Measured with Error," CREATES Research Papers 2010-08, Department of Economics and Business Economics, Aarhus University.
  6. Allen, Franklin & Babus, Ana & Carletti, Elena, 2012. "Asset commonality, debt maturity and systemic risk," Journal of Financial Economics, Elsevier, vol. 104(3), pages 519-534.
  7. Diebold, Francis X. & Yilmaz, Kamil, 2007. "Measuring financial asset return and volatility spillovers, with application to global equity markets," CFS Working Paper Series 2007/02, Center for Financial Studies (CFS).
  8. Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
  9. Daron Acemoglu & Asuman Ozdaglar & Alireza Tahbaz-Salehi, 2010. "Cascades in Networks and Aggregate Volatility," NBER Working Papers 16516, National Bureau of Economic Research, Inc.
  10. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, Elsevier.
  11. Taamouti, Abderrahim & Dufour, Jean-Marie, 2008. "Short and long run causality measures: theory and inference," UC3M Working papers. Economics we083720, Universidad Carlos III de Madrid. Departamento de Economía.
  12. Franklin Allen & Ana Babus & Elena Carletti, 2010. "Financial Connections and Systemic Risk," Economics Working Papers ECO2010/26, European University Institute.
  13. 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.
  14. White,Halbert, 1996. "Estimation, Inference and Specification Analysis," Cambridge Books, Cambridge University Press, number 9780521574464, November.
  15. Jean-Marie Dufour & Eric Renault, 1998. "Short Run and Long Run Causality in Time Series: Theory," Econometrica, Econometric Society, vol. 66(5), pages 1099-1126, September.
  16. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2010. "Measuring systemic risk," Working Paper 1002, Federal Reserve Bank of Cleveland.
  17. N. Lesca, 2010. "Introduction," Post-Print halshs-00640602, HAL.
  18. repec:taf:jnlbes:v:30:y:2012:i:2:p:212-228 is not listed on IDEAS
  19. Viral V. Acharya, 2010. "Measuring systemic risk," Proceedings 1140, Federal Reserve Bank of Chicago.
  20. Bech, Morten L. & Atalay, Enghin, 2008. "The topology of the federal funds market," Working Paper Series 0986, European Central Bank.
  21. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331, November.
  22. 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.
  23. Granger Clive W.J., 2008. "Non-Linear Models: Where Do We Go Next - Time Varying Parameter Models?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-11, September.
  24. 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.
  25. 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.
  26. repec:fip:fedhpr:y:2010:i:may:p:65-71 is not listed on IDEAS
  27. repec:cup:cbooks:9780511771576 is not listed on IDEAS
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