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An empirical study on the correlation structure of credit spreads based on the dynamic and pair copula functions

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  • Changqing Luo
  • Mengzhen Li
  • Zisheng Ouyang

Abstract

Purpose - – The purpose of this paper is to study the correlation structure of the credit spreads. Design/methodology/approach - – The minimal spanning tree is used to find the risk center node and the basic correlation structure of the credit spreads. The dynamic copula and pair copula models are applied to capture the dynamic and non-linear correlation structure. Findings - – The authors take the enterprise bond with trading data from January 2013 to December 2013 as the research sample. The empirical study of minimum spanning tree shows that the credit risk of corporate bonds forms a network structure with a center node. Meanwhile, the correlation between credit spreads shows dynamic characteristics. Under the framework of dynamic copula, the lower tail dependence is less than the upper tail dependence, thus, in economic boom period, the dynamic correlation is more significant than in recession period. The authors also find that the centrality of credit risk network is not significant according to the pair copula and Granger causality test. The empirical study shows that the goodness-of-fit of D vine is superior to Canonical vine, and the Granger causality test additionally proves that the center node has influence on few other nodes in the risk network, thus the center node captured by the minimum spanning tree is a weak center node, and this characteristic of credit risk network indicates that the risk network of credit spreads is generated mostly by the external shocks rather than the internal risk contagion. Originality/value - – This paper provides new ideas for investors and researchers to analyze the credit risk correlation or contagion.

Suggested Citation

  • Changqing Luo & Mengzhen Li & Zisheng Ouyang, 2016. "An empirical study on the correlation structure of credit spreads based on the dynamic and pair copula functions," China Finance Review International, Emerald Group Publishing Limited, vol. 6(3), pages 284-303, August.
  • Handle: RePEc:eme:cfripp:v:6:y:2016:i:3:p:284-303
    DOI: 10.1108/CFRI-08-2015-0118
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    1. Reboredo, Juan C., 2011. "How do crude oil prices co-move?: A copula approach," Energy Economics, Elsevier, vol. 33(5), pages 948-955, September.
    2. Chiarella, Carl & Fanelli, Viviana & Musti, Silvana, 2011. "Modelling the evolution of credit spreads using the Cox process within the HJM framework: A CDS option pricing model," European Journal of Operational Research, Elsevier, vol. 208(2), pages 95-108, January.
    3. Charles R. Hulten & Esra Bennathan & Sylaja Srinivasan, 2006. "Infrastructure, Externalities, and Economic Development: A Study of the Indian Manufacturing Industry," The World Bank Economic Review, World Bank, vol. 20(2), pages 291-308.
    4. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    5. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    6. Finnerty, John D. & Miller, Cameron D. & Chen, Ren-Raw, 2013. "The impact of credit rating announcements on credit default swap spreads," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2011-2030.
    7. Kim, Jong-Min & Jung, Yoon-Sung & Choi, Taeryon & Sungur, Engin A., 2011. "Partial correlation with copula modeling," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1357-1366, March.
    8. Crook, Jonathan & Moreira, Fernando, 2011. "Checking for asymmetric default dependence in a credit card portfolio: A copula approach," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 728-742, September.
    9. Pagnoncelli, Bernardo K. & Cifuentes, Arturo, 2014. "Credit risk assessment of fixed income portfolios using explicit expressions," Finance Research Letters, Elsevier, vol. 11(3), pages 224-230.
    10. Alter, Adrian & Schüler, Yves S., 2012. "Credit spread interdependencies of European states and banks during the financial crisis," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3444-3468.
    11. Liang, Xue & Wang, Guojing & Dong, Yinghui, 2013. "A Markov regime switching jump-diffusion model for the pricing of portfolio credit derivatives," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 373-381.
    12. Iscoe, Ian & Kreinin, Alexander & Mausser, Helmut & Romanko, Oleksandr, 2012. "Portfolio credit-risk optimization," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1604-1615.
    13. Rosenberg, Joshua V. & Schuermann, Til, 2006. "A general approach to integrated risk management with skewed, fat-tailed risks," Journal of Financial Economics, Elsevier, vol. 79(3), pages 569-614, March.
    14. Corò, Filippo & Dufour, Alfonso & Varotto, Simone, 2013. "Credit and liquidity components of corporate CDS spreads," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5511-5525.
    15. Maalaoui Chun, Olfa & Dionne, Georges & François, Pascal, 2014. "Credit spread changes within switching regimes," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 41-55.
    16. Bada, Oualid & Kneip, Alois, 2014. "Parameter cascading for panel models with unknown number of unobserved factors: An application to the credit spread puzzle," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 95-115.
    17. Perrakis, Stylianos & Zhong, Rui, 2015. "Credit spreads and state-dependent volatility: Theory and empirical evidence," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 215-231.
    18. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    19. Batten, Jonathan A. & Hogan, Warren P., 2003. "Time variation in the credit spreads on Australian Eurobonds," Pacific-Basin Finance Journal, Elsevier, vol. 11(1), pages 81-99, January.
    20. Guo, Liang, 2013. "Determinants of credit spreads: The role of ambiguity and information uncertainty," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 279-297.
    21. Alizadeh, Amir H. & Gabrielsen, Alexandros, 2013. "Dynamics of credit spread moments of European corporate bond indexes," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3125-3144.
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