The determinants of CDS spreads: evidence from the model space

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We apply Bayesian model averaging and a frequentistic model space analysis to assess the pricing determinants of credit default swaps (CDSs). Our study focuses on the complete model space of plausible models and thus supports ultimate robustness. Using a large dataset of CDS contracts we find that CDS price dynamics can be mainly explained by factors describing firms’ sensitivity to extreme market movements. More precisely, our results suggest that dynamic copula based measures of tail dependence incorporate most essential pricing information, making other potential determinants such as Merton-type factors or linear variables measuring the systematic market evolution negligible.

Original languageEnglish
JournalReview of Derivatives Research
Issue number1
Pages (from-to)63-118
Number of pages56
Publication statusPublished - 01.04.2018

    Research areas

  • Management studies - CDS, Bayesian Model averaging, Crash aversion, Tail Risk, Tail dependence, Time-varying copulas