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Measuring changes in credit risk: The case of CDS event studies by Andres, Christian (author);Betzer, André (author);Doumet, Markus (author) is a Economics, Econometrics and Finance article available to read on EtoBox.

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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. ☆ We are grateful for the comments of Lars Norden, Erik Theissen, Stefan Ruenzi, seminar participants at the University of Mannheim, University of Cologne, University of Wuppertal, as well as the particpants of the EFMA annual meeting 2013 at the University of Reading, and the FMA European conferenc

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

Author

Andres, Christian (author);Betzer, André (author);Doumet, Markus (author)

Publisher

Elsevier BV

Published

2021

Language

EN

Field

Economics, Econometrics and Finance (Social Sciences)