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Investigating the Dependence Structure between Credit Default Swap Spreads and the U.S. Financial Market

Author

Listed:
  • Hayette Gatfaoui

    (Pôle Finance Responsable - Rouen Business School - Rouen Business School)

Abstract

Under Basel II framework, credit risk assessment is of high significance in the light of correlation risk. Correlation risk is often envisioned along with business conditions and financial market's impact.We employ copula methodology to identify the dependence structures that may exist between market risk fundamentals and credit risk fundamentals. Considering credit derivative spreads as credit risk fundamentals and market data asmarket risk determinants, we describe and quantify the asymmetric link prevailing between credit risk and market risk. Credit risk is negatively linked with market price risk whereas it becomes positively linked with market volatility risk. Such patterns give rise to interesting asymmetric dependence structures between both risk sources. We are then able to balance reliably market price risk with market volatility feedback, the market trend supporting a common correlation between securities. In the light of the previous trade-off, we propose also a simple credit risk management rule.

Suggested Citation

  • Hayette Gatfaoui, 2010. "Investigating the Dependence Structure between Credit Default Swap Spreads and the U.S. Financial Market," Post-Print hal-00565525, HAL.
    • Handle: RePEc:hal:journl:hal-00565525
    DOI: 10.1007/s10436-009-0139-5
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    Cited by:

    1. Gatfaoui, Hayette, 2019. "Diversifying portfolios of U.S. stocks with crude oil and natural gas: A regime-dependent optimization with several risk measures," Energy Economics, Elsevier, vol. 80(C), pages 132-152.
    2. Saker Sabkha & Christian Peretti & Dorra Hmaied, 2019. "On the informational market efficiency of the worldwide sovereign credit default swaps," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 581-608, December.
    3. Naifar, Nader, 2012. "Modeling the dependence structure between default risk premium, equity return volatility and the jump risk: Evidence from a financial crisis," Economic Modelling, Elsevier, vol. 29(2), pages 119-131.
    4. Gatfaoui, Hayette, 2016. "Linking the gas and oil markets with the stock market: Investigating the U.S. relationship," Energy Economics, Elsevier, vol. 53(C), pages 5-16.
    5. Gatfaoui, Hayette, 2017. "Equity market information and credit risk signaling: A quantile cointegrating regression approach," Economic Modelling, Elsevier, vol. 64(C), pages 48-59.

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    Keywords

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    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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