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How Does Systematic Risk Impact US Credit Spreads? A Copula Study

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  • Hayette Gatfaoui

    (The University of Paris 1 - Panthéon-Sorbonne)

Abstract

It is well known that some relationship between systematic risk and credit risk prevails in financial markets. In our study, S&P 500 stock index return is our market risk proxy whereas credit spreads represent our credit risk proxy as a function of maturity, rating and economic sector. We address the problem of studying the joint distributions and evolutions of S&P 500 return and credit spreads. Graphical and non parametric statistical analysis (i.e.: Kendall’s tau and Spearman’s rho) show that such bivariate distributions are asymmetric with some negative relationship between S&P 500 return and credit spreads. In-deed, credit spreads widen when S&P 500 return decreases or drops under some given level. We investigate then this stylized fact using copula functions to characterize observed dependence structures between S&P 500 return and credit spreads. We focus at least on one parameter copulas and at most on one parameter Archimedean copulas, namely Gumbel, FGM, Frank and Clayton copula functions. Starting from empirical Kendall’s tau observed for each bivariate dependence structure, we induce parameter values for each copula type function belonging to our copulas set. Finally, we exhibit optimal characterizations for such dependence structures and use the optimal selected copulas to achieve a scenario analysis among which stress testing.

Suggested Citation

  • Hayette Gatfaoui, 2003. "How Does Systematic Risk Impact US Credit Spreads? A Copula Study," Risk and Insurance 0308002, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpri:0308002
    Note: Type of Document - Acrobat PDF; prepared on PC; to print on HP/PostScript; pages: 27 ; figures: included. This paper is under submission for the special issue of the European Investment Review.
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    References listed on IDEAS

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    Cited by:

    1. Canela Miguel-Angel & Pedreira Eduardo, 2012. "Modelling Dependence in Latin American Markets Using Copula Functions," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 11(3), pages 231-270, December.
    2. Mathieu Bargès & Hélène Cossette & Etienne Marceau, 2009. "TVaR-based capital allocation with copulas," Working Papers hal-00431265, HAL.
    3. Bargès, Mathieu & Cossette, Hélène & Marceau, Étienne, 2009. "TVaR-based capital allocation with copulas," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 348-361, December.
    4. Cossette, Hélène & Côté, Marie-Pier & Marceau, Etienne & Moutanabbir, Khouzeima, 2013. "Multivariate distribution defined with Farlie–Gumbel–Morgenstern copula and mixed Erlang marginals: Aggregation and capital allocation," Insurance: Mathematics and Economics, Elsevier, vol. 52(3), pages 560-572.

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    More about this item

    Keywords

    systematic risk credit risk copulas Archimedean copulas stress testing;

    JEL classification:

    • 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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