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On the determinants of industry-CDS index spreads: Evidence from a nonlinear setting

Author

Listed:
  • Khaled Guesmi

    (IPAG Paris - IPAG Paris)

  • Abderrazak Dhaoui
  • Stéphane Goutte

    (UP8 - Université Paris 8 Vincennes-Saint-Denis)

  • Ilyes Abid

Abstract

This study uses a comprehensive data set of 11 sector indices of the S&P500 and some financial variables to study their dynamic interaction with industry credit default swaps (CDSs) from mid-December 2007 to the end of December 2016. More specifically, we attempt to measure the asymmetric long-run and short-run specification of the CDS spreads and their financial determinants. More extensive in some industry sectors compared to others, and the dependence between the CDS market and equity market may therefore be industry dependent. Our results indicate that positive and negative changes in industry stock price, business condition volatility, spot interest rates, and the SMB and HML Fama and French factors have asymmetric impacts on industry CDS index spreads. Nevertheless, while CDS spreads are sensitive to positive and negative shocks in the respective industry stock price as well as to the business condition, the sensitivity of CDS spreads to positive and negative unit changes in the rest of the financial determinants are sector dependent.
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Suggested Citation

  • Khaled Guesmi & Abderrazak Dhaoui & Stéphane Goutte & Ilyes Abid, 2018. "On the determinants of industry-CDS index spreads: Evidence from a nonlinear setting," Post-Print halshs-02148926, HAL.
  • Handle: RePEc:hal:journl:halshs-02148926
    DOI: 10.1016/j.intfin.2018.01.005
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    Cited by:

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    2. 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).
    3. Shahzad, Syed Jawad Hussain & Aloui, Chaker & Jammazi, Rania, 2020. "On the interplay between US sectoral CDS, stock and VIX indices: Fresh insights from wavelet approaches," Finance Research Letters, Elsevier, vol. 33(C).
    4. González-Fernández, Marcos & González-Velasco, Carmen, 2020. "An alternative approach to predicting bank credit risk in Europe with Google data," Finance Research Letters, Elsevier, vol. 35(C).
    5. Choi, Sun-Yong, 2022. "Credit risk interdependence in global financial markets: Evidence from three regions using multiple and partial wavelet approaches," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    6. Caiazza, Stefano & Galloppo, Giuseppe & La Rosa, Giovanni, 2023. "The mitigation role of corporate sustainability: Evidence from the CDS spread," Finance Research Letters, Elsevier, vol. 52(C).

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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