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Dynamics in the correlations of the Credit Default Swaps’ G14 dealers: Are there any contagion effects due to Lehman Brothers’ bankruptcy and the global financial crisis?

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  • Irfan Akbar Kazi
  • Suzanne Salloy
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    Abstract

    This article investigates the dynamics of conditional correlation among the G14 banks’ dealer for the credit default swap market from January 2004 until May 2009. By using the asymmetric dynamic conditional correlation model developed by Cappiello, Engle and Sheppard (2006), we examine if there is contagion during the global financial crisis, following Lehman Brothers’ bankruptcy of September 15th, 2008. The main contribution of this article is to analyze if the interdependence structure between the G14 banks changed significantly during the crisis period. We try to identify the banks which were the most or the least affected by losses induced by the crisis and we draw some conclusions in terms of their vulnerability to financial shocks. We find that all banks became highly interdependent during Lehman Brothers’ bankruptcy (short term impact), but only some banks faced high contagion during the global financial crisis (long term impact). Regulators who try to reinforce banks’ stability with the Basel 3 reforms proposals should be interested by these results.

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    Bibliographic Info

    Paper provided by Department of Research, Ipag Business School in its series Working Papers with number 2014-237.

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    Length: 50 pages
    Date of creation: 28 Apr 2014
    Date of revision:
    Handle: RePEc:ipg:wpaper:2014-237

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    Related research

    Keywords: Financial Crisis; Contagion; Credit Default Swap; Lehman Brothers; Asymmetric Dynamic Conditional Correlation.;

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    1. BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen, 2003. "Multivariate GARCH models: a survey," CORE Discussion Papers 2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-50, July.
    3. Douglas W. Diamond & Philip H. Dybvig, 2000. "Bank runs, deposit insurance, and liquidity," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 14-23.
    4. Go Tamakoshi & Yuki Toyoshima & Shigeyuki Hamori, 2012. "A dynamic conditional correlation analysis of European stock markets from the perspective of the Greek sovereign debt crisis," Economics Bulletin, AccessEcon, vol. 32(1), pages 437-448.
    5. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    6. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(4), pages 537-572.
    7. Kristin J. Forbes, 2012. "The “Big C”: identifying and mitigating contagion," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 23-87.
    8. Wang, Ping & Moore, Tomoe, 2012. "The integration of the credit default swap markets during the US subprime crisis: Dynamic correlation analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(1), pages 1-15.
    9. Christian Hafner & Philip Hans Franses, 2009. "A Generalized Dynamic Conditional Correlation Model: Simulation and Application to Many Assets," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 612-631.
    10. Heiko Hesse & Nathaniel Frank & Brenda González-Hermosillo, 2008. "Transmission of Liquidity Shocks," IMF Working Papers 08/200, International Monetary Fund.
    11. Kristin Forbes, 2012. "The "Big C": Identifying Contagion," NBER Working Papers 18465, National Bureau of Economic Research, Inc.
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