Measuring Abnormal Credit Default Swap Spreads

53 Pages Posted: 29 Dec 2012 Last revised: 5 Jan 2017

See all articles by Christian Andres

Christian Andres

WHU - Otto Beisheim School of Management

André Betzer

BUW- Schumpeter School of Business and Economics

Markus Doumet

University of Mannheim - Finance Area

Date Written: January 22, 2016

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 spreads 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 returns around issuer's rating downgrades to demonstrate the effect of CDS spread change measures and normal return models on the inferences drawn from the results of CDS event studies.

Keywords: CDS spread, event study, Brown-Warner simulation

JEL Classification: G14

Suggested Citation

Andres, Christian and Betzer, André and Doumet, Markus, Measuring Abnormal Credit Default Swap Spreads (January 22, 2016). Available at SSRN: https://ssrn.com/abstract=2194320 or http://dx.doi.org/10.2139/ssrn.2194320

Christian Andres

WHU - Otto Beisheim School of Management ( email )

Burgplatz 2
Vallendar, 56179
Germany

André Betzer

BUW- Schumpeter School of Business and Economics ( email )

Gaußstraße 20
Wuppertal
Germany

HOME PAGE: http://finance.uni-wuppertal.de/index.php?id=1153

Markus Doumet (Contact Author)

University of Mannheim - Finance Area ( email )

Mannheim, 68131
Germany

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