Contagion spillovers between sovereign and financial European sector from a Delta CoVaR approach

  1. Javier Ojea Ferreiro 1
  1. 1 Universidad Complutense de Madrid

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

Documentos de Trabajo (ICAE)

ISSN: 2341-2356

Année de publication: 2018

Número: 12

Pages: 1-33

Type: Working Paper

D'autres publications dans: Documentos de Trabajo (ICAE)


Índice Dialnet de Revistas

  • Año 2018
  • Impacto de la revista: 0,240
  • Ámbito: ECONOMÍA Cuartil: C2 Posición en el ámbito: 49/171


I examine the evolution of contagion indexes between the European Financial sector and the sovereign sector (Austria, Belgium, France, Germany, Italy, Netherlands and Spain) during the European sovereign credit crisis. Contagion indexes, ∆CoV aR and ∆CoES, reflect events associated with extreme left tail returns and interdependencies between defaults different than those observed in tranquil times. These measures reveal very useful information concerning risk management. I use a copula approach with time-varying parameters to capture changes in the tail dependence between returns in the financial and the sovereign sectors. I employ a Switching Markov model to identify the most stressful moments of the contagion indicators. The results point out the emergence of Greek debt crisis on March 2010 and the vulnerable situation of Spain and Italy in summer 2011 as the main periods where the contagion from the sovereign to the financial sector was stronger. The decrease in contagion was gradual since the speech made by the ECB on July 26th; 2012. The statistical significance of the change in the contagion indicators is checked using boostrap tests.

Information sur le financement

I acknowledge financial support provided by the Spanish Ministry of Education under grant FPU15/04241.


  • Ministry of Education Spain
    • FPU15/042

Références bibliographiques

  • Abadie, A., 2002. Bootstrap tests for distributional treatment effects in instrumental variable models. Journal of the American Statistical Association 97 (457), 284–292.
  • Acharya, V., Drechsler, I., Schnabl, P., 2014. A Pyrrhic Victory? Bank Bailouts and Sovereign Credit Risk. Journal of Finance 69 (6), 2689–2739.
  • Adrian, T., Brunnermeier, M. K., 2016. CoVaR. American Economic Review 106 (7), 1705–41.
  • Albertazzi, U., Ropele, T., Sene, G., Signoretti, F. M., 2014. The impact of the sovereign debt crisis on the activity of Italian banks. Journal of Banking & Finance 46, 387–402.
  • Aloui, R., Hammoudeh, S., Nguyen, D. K., 2013. A time-varying copula approach to oil and stock market dependence: The case of transition economies. Energy Economics 39, 208–221.
  • Alter, A., Beyer, A., 2012. The dynamics of spillover effects during the European sovereign debt turmoil. CFS Working Paper Series 2012/13, Center for Financial Studies (CFS).
  • Alter, A., Schüler, Y. S., 2012. Credit spread interdependencies of European states and banks during the financial crisis. Journal of Banking & Finance 36 (12), 3444–3468.
  • Anson, M. J., Fabozzi, F. J., Choudhry, M., Chen, R.-R., 2004. Credit Derivatives: Instruments, Applications, and Pricing. Vol. 133. John Wiley & Sons.
  • Ao, S.-I., Kim, H. K., Amouzegar, M. A., 2017. Transactions on Engineering Technologies: World Congress on Engineering and Computer Science 2015. Springer.
  • Ballester, L., Casu, B., González-Urteaga, A., 2016. Bank fragility and contagion: Evidence from the bank CDS market. Journal of Empirical Finance 38, 394–416.
  • Bernal, O., Gnabo, J.-Y., Guilmin, G., 2014. Assessing the contribution of banks, insurance and other financial services to systemic risk. Journal of Banking & Finance 47, 270–287.
  • Berndt, A., Obreja, I., 2010. Decomposing European CDS returns. Review of Finance 14 (2), 189–233.
  • Bicu, A., Candelon, B., 2012. On the importance of indirect banking vulnerabilities in the Eurozone. Research Memorandum 033, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  • Candelon, B., Sy, A., Arezki, R., 2011. Sovereign Rating News and Financial Markets Spillovers; Evidence from the European Debt Crisis. Tech. rep., International Monetary Fund.
  • Chamizo, A., Novales Cinca, A., 2016. Looking Through Systemic Risk: Determinants, Stress Testing and Market Value. Journal of Financial Transformation 43, 117–123.
  • Chen, K.-H., Khashanah, K., 2014. Measuring Systemic Risk: Vine Copula GARCH Model . Tech. rep., World Congress on Engineering and Computer Science 2015.
  • Christoffersen, P., 1998. Evaluating interval forecasts. International Economic Review, 841–862.
  • Chudik, A., Fratzscher, M., 2012. Liquidity, risk and the global transmission of the 2007-08 financial crisis and the 2010-11 sovereign debt crisis. Globalization and Monetary Policy Institute Working Paper 107.
  • Creal, D., Koopman, S. J., Lucas, A., 2013. Generalized autoregressive score models with applications. Journal of Applied Econometrics 28 (5), 777–795.
  • Dieckmann, S., Plank, T., 2011. Default risk of advanced economies: An empirical analysis of Credit Default Swaps during the financial crisis. Review of Finance 16 (4), 903–934.
  • Durbin, J., 1973. Distribution theory for tests based on the sample distribution function. SIAM.
  • Ejsing, J., Lemke, W., January 2011. The Janus-headed salvation: Sovereign and bank credit risk premia during 2008-2009. Economics Letters 110 (1), 28–31.
  • Elliott, G., Timmermann, A., 2013. Handbook of economic forecasting. Elsevier.
  • Gerlach, S., Schulz, A., Wolff, G. B., 2010. Banking and Sovereign risk in the Euro area. Discussion Paper Series 1: Economic Studies 2010,09, Deutsche Bundesbank, Research Centre.
  • Girardi, G., Ergün, A. T., 2013. Systemic risk measurement: Multivariate GARCH estimation of CoVaR. Journal of Banking and Finance 37 (8), 3169–3180.
  • Gray, D. F., Merton, R. C., Bodie, Z., Nov. 2007. New Framework for Measuring and Managing Macrofinancial Risk and Financial Stability. NBER Working Papers 13607, National Bureau of Economic Research.
  • Hafner, C. M., Manner, H., March 2012. Dynamic stochastic copula models: estimation, inference and applications. Journal of Applied Econometrics 27 (2), 269–295.
  • Hansen, B. E., 1994. Autoregressive conditional density estimation. International Economic Review, 705– 730.
  • Hollo, D., Kremer, M., Lo Duca, M., Mar. 2012. CISS a Composite Indicator of Systemic Stress in the financial system. Working Paper Series 1426, European Central Bank.
  • Hurvich, C. M., Tsai, C.-L., 1989. Regression and time series model selection in small samples. Biometrika 76 (2), 297–307.
  • Jiang, C., 2012. Does tail dependence make a difference in the estimation of systemic risk? Tech. rep., CoVaR and MES Working Paper, Boston College.
  • Joe, H., Xu, J. J., 1996. The estimation method of inference functions for margins for multivariate models. Tech. rep., Department of Statistics, University of British Columbia.
  • Kok, C., Gross, M., Aug. 2013. Measuring contagion potential among sovereigns and banks using a mixedcross-section GVAR. Working Paper Series 1570, European Central Bank.
  • Kupiec, P., 1995. Techniques for verifying the accuracy of risk measurement models. The Journal of Derivatives 3 (2), 73–84.
  • MacKinnon, J. G., 2009. Bootstrap hypothesis testing. Handbook of Computational Econometrics 183, 213.
  • Mainik, G., Schaanning, E., 2014. On dependence consistency of CoVaR and some other systemic risk measures. Statistics and Risk Modeling 31 (1), 49–77.
  • Panetta, F., Correa, R., Davies, M., Di Cesare, A., Marques, J.-M., Nadal de Simone, F., Signoretti, F.,
  • Vespro, C., Vildo, S., Wieland, M., Apr. 2011. The impact of sovereign credit risk on bank funding conditions. MPRA Paper 32581, University Library of Munich, Germany.
  • Patton, A., 2013. Chapter 16 copula methods for forecasting multivariate time series. In: Elliott, G., Timmermann, A. (Eds.), Handbook of Economic Forecasting. Vol. 2 of Handbook of Economic Forecasting. Elsevier, pp. 899 – 960.
  • Patton, A. J., 2006. Modelling asymmetric exchange rate dependence. International Economic Review 47 (2), 527–556.
  • Reboredo, J., Ugolini, A., 2015a. Systemic risk in European sovereign debt markets: A CoVaR-copula approach. Journal of International Money and Finance 51 (C), 214–244.
  • Reboredo, J., Ugolini, A., 2015b. A vine-copula conditional Value-at-Risk approach to systemic sovereign debt risk for the financial sector. The North American Journal of Economics and Finance 32, 98–123.
  • Reboredo, J. C., Ugolini, A., 2016. Systemic risk of Spanish listed banks: a vine copula CoVaR approach. Spanish Journal of Finance and Accounting 45 (1), 1–31.
  • Rodríguez, J., 2007. Measuring financial contagion: A Copula approach. Journal of Empirical Finance 14 (3), 401–423.
  • Rodríguez-Moreno, M., Peña, J. I., 2013. Systemic risk measures: The simpler the better? Journal of Banking & Finance 37 (6), 1817–1831.
  • Zhang, J., 2015. Systemic Risk Measure: CoVaR and Copula. Ph.D. thesis, Humboldt-Universität zu Berlin.