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Forecasting systemic impact in financial networks

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Author Info

  • Nikolaus Hautsch
  • Julia Schaumburg
  • Melanie Schienle

Abstract

We propose a methodology for forecasting the systemic impact of financial institutions in interconnected systems. Utilizing a five-year sample including the 2008/9 financial crisis, we demonstrate how the approach can be used for timely systemic risk monitoring of large European banks and insurance companies. We predict firms’ systemic relevance as the marginal impact of individual downside risks on systemic distress. The so-called systemic risk betas account for a company’s position within the network of financial interdependencies in addition to its balance sheet characteristics and its exposure towards general market conditions. Relying only on publicly available daily market data, we determine time-varying systemic risk networks, and forecast systemic relevance on a quarterly basis. Our empirical findings reveal time-varying risk channels and firms’ specific roles as risk transmitters and/or risk recipients.

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Bibliographic Info

Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2013-008.

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Length: 28 pages
Date of creation: Jan 2013
Date of revision:
Handle: RePEc:hum:wpaper:sfb649dp2013-008

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Related research

Keywords: Forecasting systemic risk contributions; time-varying systemic risk network; model selection with regularization in quantiles;

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References

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  1. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2012. "Financial Network Systemic Risk Contributions," SFB 649 Discussion Papers SFB649DP2012-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  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.
  3. Viral V. Acharya, 2010. "Measuring systemic risk," Proceedings 1140, Federal Reserve Bank of Chicago.
  4. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2011. "Systemic risk diagnostics: coincident indicators and early warning signals," Working Paper Series 1327, European Central Bank.
  5. Bernd Schwaab & Andre Lucas & Siem Jan Koopman, 2010. "Systemic Risk Diagnostics," Tinbergen Institute Discussion Papers 10-104/2/DSF 2, Tinbergen Institute, revised 29 Nov 2010.
  6. Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.
  7. Kay Giesecke & Baeho Kim, 2011. "Systemic Risk: What Defaults Are Telling Us," Management Science, INFORMS, vol. 57(8), pages 1387-1405, August.
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Citations

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Cited by:
  1. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2012. "Financial Network Systemic Risk Contributions," SFB 649 Discussion Papers SFB649DP2012-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  2. Matteo Barigozzi & Christian T. Brownlees, 2013. "Nets: Network estimation for time series," Economics Working Papers 1391, Department of Economics and Business, Universitat Pompeu Fabra.
  3. Poeschel, Friedrich, 2012. "Assortative matching through signals," Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62061, Verein für Socialpolitik / German Economic Association.

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