Systemic risk of Spanish listed banksa vine copula CoVaR approach

  1. Juan C. Reboredo 2
  2. Andrea Ugolini 1
  1. 1 Università di Firenze
  2. 2 Universidade de Santiago de Compostela. Departamento de Fundamentos da Análise Económica
Revista:
Revista española de financiación y contabilidad

ISSN: 0210-2412

Ano de publicación: 2016

Volume: 45

Número: 1

Páxinas: 1-31

Tipo: Artigo

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Outras publicacións en: Revista española de financiación y contabilidad

Resumo

En este trabajo se cuantifica el riesgo sistémico que generan las dificultades financieras de un banco español cotizado sobre los restantes bancos cotizados y sobre el sistema financiero europeo, utilizando para ello el valor condicional en riesgo (CoVaR) como medida de riesgo sistémico. Modelizamos la dependencia multivariante entre los bancos cotizados utilizando una estructura de dependencia jerárquica en forma de árbol dada por un modelo cópula denominado vine, mientras que utilizamos un modelo cópula bivariante para modelizar la dependencia entre cada uno de los bancos cotizados y el sistema financiero europeo. Para el período enero de 2003 a marzo de 2015, el riesgo sistémico aumentó de forma drástica durante la crisis financiera mundial y, en menor medida, durante la crisis de la deuda europea. El banco BBVA desempeñó un papel fundamental, transmitiendo y recibiendo riesgo sistémico de los restantes bancos cotizados. El banco Santander tuvo un papel menor, mientras que los bancos más pequeños, Sabadell y Bankinter, no tuvieron ningún papel determinante, incluso entre ellos mismos. Finalmente, el principal impacto sistémico de los bancos españoles sobre el sistema financiero europeo se origina desde los bancos BBVA, Popular y Santander, mientras que los restantes bancos cotizados tienen un papel menor en la transmisión de riesgos. Los resultados obtenidos tienen implicaciones para la regulación de capital de las instituciones financieras y para las decisiones de gestión de riesgos de los inversores.

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Información de financiamento

Juan C. Reboredo acknowledges financial support provided by the Xunta de Galicia and FEDER [research grant GPC2013-045]. Andrea Ugolini acknowledges the financial support by the project MIUR PRIN MISURA ? Multivariate Models for Risk Assessment.

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Referencias bibliográficas

  • K.Aas,, C.Czado,, A.Frigessi,, & H.Bakken, (2009). Pair-copula constructions of multiple dependence. Insurance: Mathematics and Economics, 44, 182–198.
  • V.Acharya,, L.H.Pedersen,, T.Philippon,, & M.Richardson, (2010). Measuring systemic risk (Working Paper). New York University. Retrieved from http://pages.stern.nyu.edu/~tphilipp/papers/Systemic.pdf
  • T.Adrian,, & M.K.Brunnermeier, (2011). CoVaR (NBER Working Paper Series No. W17454). Retrieved from http://www.nber.org/papers/w17454.pdf
  • L.Allen,, T.G.Bali,, & Y.Tang, (2012). Does systemic risk in the financial sector predict future economic downturns? Review of Financial Studies, 25(10), 3000–3036. Retrieved from http://rfs.oxfordjournals.org/content/25/10/3000.short
  • P.Avramidis,, & F.Pasiouras, (2015). Calculating systemic risk capital: A factor model approach. Journal of Financial Stability, 16, 138–150.
  • O.Bernal,, J.Gnabo,, & G.Guilmin, (2013). Assessing the contribution of banks, insurance and other financial services to systemic risk. Unpublished manuscript.
  • M.Billio,, M.Getmansky,, A.W.Lo,, & L.Pelizzon, (2012). Econometric measures of connectedness and systemic risk in the finance and insurance sectors. Journal of Financial Economics, 104, 535–559. doi:10.1016/j.jfineco.2011.12.010
  • D.Bisias,, M.Flood,, A.Lo,, & S.Valavanis, (2012). A survey of systemic risk analytics (Working Paper). Office of Financial Research. Retrieved from http://papers.ssrn.com/sol3/Papers.cfm?abstract_id=1983602
  • W.Breymann,, A.Dias,, & P.Embrechts, (2003). Dependence structures for multivariate high-frequency data in finance. Quantitative Finance, 3, 1–14. doi:10.1080/713666155
  • C.Brownlees,, & R.Engle, (2012). Volatility, correlation and tails for systemic risk measurement (Working Paper). New York University. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1611229
  • R.Engle,, & S.Manganelli, (2004). Caviar: Conditional autoregressive value at risk by regression quantiles. Journal of Business & Economic Statistics, 22, 367–381. doi:10.1198/073500104000000370
  • Financial Stability Board. (2010). Reducing the moral hazard posed by systemically important financial institutions. FSB Recommendations and Time Lines, October 20. Retrieved from http://www.financialstabilityboard.org/wp-content/uploads/r_101111a.pdf?page_moved=1
  • G.Girardi,, & A.T.Ergün, (2013). Systemic risk measurement: Multivariate GARCH estimation of CoVaR. Journal of Banking & Finance, 37, 3169–3180. doi:10.1016/j.jbankfin.2013.02.027
  • L.R.Glosten,, R.Jaganathan,, & D.Runkle, (1993). On the relation between the expected value and the volatility of the normal excess return on stocks. Journal of Finance, 48, 1779–1801.
  • B.Hansen, (1994). Autoregressive conditional density estimation. International Economic Review, 35, 705–730. doi:10.2307/2527081
  • I.Hobæk Haff, (2013). Parameter estimation for pair-copula constructions. Bernoulli, 19, 462–491.
  • X.Huang,, H.Zhou,, & H.Zhu, (2009). A framework for assessing the systemic risk of major financial institutions. Journal of Banking & Finance, 33, 2036–2049. doi:10.1016/j.jbankfin.2009.05.017
  • H.Joe, (1996). Families of m-variate distributions with given margins and m(m − 1)/2 bi-variate dependence parameters. In L.Rüschendorf, B.Schweizer, & M.D.Taylor (Eds.), Distributions with fixed marginals and related topics. Hayward: Institute of Mathematical Statistics.
  • H.Joe, (1997). Multivariate models and dependence concepts. Monographs in statistics and probability (Vol. 73). London: Chapman and Hall.
  • H.Joe,, & J.J.Xu, (1996). The estimation method of inference functions for margins for multivariate models (Technical Report No. 166). Columbia: Department of Statistics, University of British.
  • G.López-Espinosa,, A.Moreno,, A.Rubia,, & L.Valderrama, (2012). Short-term wholesale funding and systemic risk: A global CoVaR approach. Journal of Banking & Finance, 36(12), 3150–3162.
  • G.Mainik,, & E.Schaanning, (2014). On dependence consistency of CoVaR and some other systemic risk measures. Statistics & Risk Modeling, 31(1), 49–77. Retrieved from http://www.degruyter.com/view/j/strm.2014.31.issue-1/strm-2013-1164/strm-2013-1164.xml?format=INT
  • M.Moreno,, & J.Peña, (2012). Systemic risk measures: The simpler the better? Journal of Banking and Finance, 37, 1817–1831. doi:10.1016/j.jbankfin.2012.07.010
  • R.B.Nelsen, (2006). An introduction to copulas. New York: Springer-Verlag.
  • A.J.Patton, (2006). Modelling asymmetric exchange rate dependence. International Economic Review, 47(2), 527–556. doi:10.1111/iere.2006.47.issue-2
  • N.Puzanova,, & K.Dülllmann, (2013). Systemic risk contributions: A credit portfolio approach. Journal of Banking & Finance, 37, 1243–1257. doi:10.1016/j.jbankfin.2012.11.017
  • J.C.Reboredo, (2011). How do crude oil prices co-move? A copula approach. Energy Economics, 33, 948–955. doi:10.1016/j.eneco.2011.04.006
  • J.C.Reboredo, (2013). Is gold a safe haven or a hedge for the US dollar? Implications for risk management. Journal of Banking & Finance, 37, 2665–2676. doi:10.1016/j.jbankfin.2013.03.020
  • J.C.Reboredo, (2015). Is there dependence and systemic risk between oil and renewable energy stock prices? Energy Economics, 48, 32–45. doi:10.1016/j.eneco.2014.12.009
  • J.C.Reboredo,, & A.Ugolini, (2015a). A vine-copula conditional value-at-risk approach to systemic sovereign debt risk for the financial sector. TheNorth American Journal of Economics and Finance, 32, 98–123. doi:10.1016/j.najef.2015.02.002
  • J.C.Reboredo,, & A.Ugolini, (2015b). Systemic risk in European sovereign debt markets: A CoVaR-copula approach. Journal of International Money and Finance, 51, 214–244. doi:10.1016/j.jimonfin.2014.12.002
  • M.Segoviano,, & C.Goodhart, (2009). Banking stability measures (Working Paper). IMF. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1356460
  • A.Sklar, (1959). Fonctions de Riépartition á n Dimensions et Leurs Marges, 8, 229–231. Publications de l’Institut Statistique de l’Université de Paris. Retrieved from http://www.lsta.lab.upmc.fr/modules/resources/download/labsta/Annales_ISUP/Couv_ISUP_8-3.pdf
  • J.M.Zakoian, (1994). Threshold heteroskedastic models. Journal of Economics Dynamics and Control, 18, 931–944.
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