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Volatility relation between credit default swap and stock market: new empirical tests

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  • Miroslav Mateev

    (American University in the Emirates)

Abstract

This paper investigates the relation between volatility of CDS and stock prices using a sample of 109 European investment-grade companies, during the period of January 2012 to January 2016. To analyse the volatility relation between CDS and stock prices and its time persistence, we use the Dynamic Conditional Correlation (DCC) model. We also test the volatility spillover hypothesis and investigate the direction of the spillover effect using the BEKK-GARCH model. We find strong evidence in support of the hypothesis that the volatility of CDS and stock prices across European investment-grade companies can be modelled under the dynamic conditional correlation assumption. When we split the volatility into two components, namely, ARCH-effect (that is, short-run persistence of shocks) and GARCH-effect (that is, long-run persistence), we find that, in general, the persistence of correlation is statistically significant, while the impact of innovations (shocks) on correlation is not. Our tests of the volatility spillover hypothesis provide new evidence that the volatility spillover is bi-directional, with the predominant leadership of the European CDS market over the stock market.

Suggested Citation

  • Miroslav Mateev, 2019. "Volatility relation between credit default swap and stock market: new empirical tests," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(4), pages 681-712, October.
    • Handle: RePEc:spr:jecfin:v:43:y:2019:i:4:d:10.1007_s12197-018-9467-5
    DOI: 10.1007/s12197-018-9467-5
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    1. Li, Hong & Majerowska, Ewa, 2006. "Stock market integration: a multivariate GARCH analysis on Poland and Hungary," Economics Discussion Papers 2006-2, School of Economics, Kingston University London.
    2. Francis A. Longstaff & Sanjay Mithal & Eric Neis, 2005. "Corporate Yield Spreads: Default Risk or Liquidity? New Evidence from the Credit Default Swap Market," Journal of Finance, American Finance Association, vol. 60(5), pages 2213-2253, October.
    3. Ansgar Belke & Christian Gokus, 2011. "Volatility Patterns of CDS, Bond and Stock Markets before and during the Financial Crisis: Evidence from Major Financial Institutions," Discussion Papers of DIW Berlin 1107, DIW Berlin, German Institute for Economic Research.
    4. Schreiber, Irene & Müller, Gernot & Klüppelberg, Claudia & Wagner, Niklas, 2012. "Equities, credits and volatilities: A multivariate analysis of the European market during the subprime crisis," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 57-65.
    5. Julien Chevallier, 2012. "Econometric Analysis of Carbon Markets," Springer Books, Springer, number 978-94-007-2412-9, September.
    6. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    7. 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 339-350, July.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Roberto Blanco & Simon Brennan & Ian W. Marsh, 2004. "An empirical analysis of the dynamic relationship between investment grade bonds and credit default swaps," Working Papers 0401, Banco de España.
    10. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    11. Scheicher, Martin, 2008. "How has CDO market pricing changed during the turmoil? Evidence from CDS index tranches," Working Paper Series 910, European Central Bank.
    12. Jiri Podpiera & Ms. Inci Ötker, 2010. "The Fundamental Determinants of Credit Default Risk for European Large Complex Financial Institutions," IMF Working Papers 2010/153, International Monetary Fund.
    13. Coudert, Virginie & Gex, Mathieu, 2010. "Contagion inside the credit default swaps market: The case of the GM and Ford crisis in 2005," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(2), pages 109-134, April.
    14. L. Meng & O. Gwilym & J. Varas, 2009. "Volatility transmission among the CDS, equity, and bond markets," Post-Print halshs-00487331, HAL.
    15. Haibin Zhu, 2004. "An empirical comparison of credit spreads between the bond market and the credit default swap market," BIS Working Papers 160, Bank for International Settlements.
    16. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    17. Fabozzi, Frank J. & Cheng, Xiaolin & Chen, Ren-Raw, 2007. "Exploring the components of credit risk in credit default swaps," Finance Research Letters, Elsevier, vol. 4(1), pages 10-18, March.
    18. 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.
    19. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

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    2. Veysel Karagol, 2023. "How Vulnerable is the Turkish Stock Market to the Credit Default Swap? Evidence from the Markov Switching GARCH Model," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 73(73-1), pages 513-531, June.
    3. Ibhagui, Oyakhilome, 2021. "How do sovereign risk, equity and foreign exchange derivatives markets interact?," Economic Modelling, Elsevier, vol. 97(C), pages 58-78.
    4. Laura Ballester & Ana Mónica Escrivá & Ana González-Urteaga, 2021. "The Nexus between Sovereign CDS and Stock Market Volatility: New Evidence," Mathematics, MDPI, vol. 9(11), pages 1-23, May.
    5. Christian Manicaro, 2023. "Sectoral and Regional Volatility Connectedness: The Case of CDS Spreads and Equities," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 15(4), pages 1-8, April.
    6. Katz, Yuri A. & Biem, Alain, 2021. "Time-resolved topological data analysis of market instabilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    7. Theodoros Bratis & Nikiforos T. Laopodis & Georgios P. Kouretas, 2023. "CDS and equity markets’ volatility linkages: lessons from the EMU crisis," Review of Quantitative Finance and Accounting, Springer, vol. 60(3), pages 1259-1281, April.
    8. Faruk Balli & Hatice O. Balli & Mudassar Hasan & Russell Gregory-Allen, 2020. "Economic policy uncertainty spillover effects on sectoral equity returns of New Zealand," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(4), pages 670-686, October.

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    More about this item

    Keywords

    Credit default swap; iTraxx index; Volatility spillover; Multivariate GARCH;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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