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Measuring changes in credit risk: The case of CDS event studies

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  • Andres, Christian
  • Betzer, André
  • Doumet, Markus

Abstract

This paper examines the size and power of test statistics designed to detect abnormal changes in credit risk as measured by credit default swap (CDS) spreads. We follow a simulation approach to examine the statistical properties of normal and abnormal CDS spread changes and assess the performance of normal return models and test statistics. Using daily CDS data, we find parametric test statistics to be generally inferior to non-parametric tests, with the rank test performing best. A CDS factor model based on factors identified in the empirical literature is generally well specified and more powerful in detecting abnormal performance than some of the classical normal return models. Finally, we examine abnormal CDS announcement spread changes around issuer's rating downgrades to demonstrate the effect of different CDS spread change measures and normal return models on event study results.

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  • Andres, Christian & Betzer, André & Doumet, Markus, 2021. "Measuring changes in credit risk: The case of CDS event studies," Global Finance Journal, Elsevier, vol. 49(C).
    • Handle: RePEc:eee:glofin:v:49:y:2021:i:c:s1044028321000454
    DOI: 10.1016/j.gfj.2021.100647
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    More about this item

    Keywords

    Event study; Credit default swap; Brown-Warner simulation;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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