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Common factors in credit defaults swap markets

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  • Cathy Chen
  • Wolfgang Härdle

Abstract

We examine what are the common factors that determine systematic credit risk, and estimate and interpret these factors. We also compare the contributions of common factors in explaining the changes of credit default swap spreads during the pre-crisis, the crisis and the post-crisis period; there is evidence to suggest that the eigenstructures across these three sub-periods are distinct. Furthermore, we examine whether the observable economic variables are in fact the underlying latent factors and analyze the predictability in the factors that capture the time-variation of credit default swap spreads. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Cathy Chen & Wolfgang Härdle, 2015. "Common factors in credit defaults swap markets," Computational Statistics, Springer, vol. 30(3), pages 845-863, September.
  • Handle: RePEc:spr:compst:v:30:y:2015:i:3:p:845-863
    DOI: 10.1007/s00180-015-0578-6
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    Cited by:

    1. Chamizo, Álvaro & Novales, Alfonso, 2020. "Looking through systemic credit risk: Determinants, stress testing and market value," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 64(C).
    2. Lidija Lovreta & Joaquín López Pascual, 2020. "Structural breaks in the interaction between bank and sovereign default risk," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 11(4), pages 531-559, December.
    3. Alfonso Novales & Alvaro Chamizo, 2019. "Splitting Credit Risk into Systemic, Sectorial and Idiosyncratic Components," JRFM, MDPI, vol. 12(3), pages 1-33, August.
    4. Xiu Xu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2019. "Dynamic credit default swap curves in a network topology," Quantitative Finance, Taylor & Francis Journals, vol. 19(10), pages 1705-1726, October.
    5. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.

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