Detecting Abnormal Changes in Credit Default Swap Spreads Using Matching-Portfolio Models

44 Pages Posted: 8 Mar 2016 Last revised: 17 Apr 2018

See all articles by Fabio Bertoni

Fabio Bertoni

EM Lyon (Ecole de Management de Lyon) - Department of Economics, Finance, Control

Stefano Lugo

Utrecht University - School of Economics

Date Written: March 30, 2018

Abstract

We evaluate the size and power of different statistical tests and adjustment methods for matching-portfolio models to detect abnormal changes in credit default swap (CDS) spreads. The sign-test generally dominates the signed-rank test in terms of size, and dominates both the t-test and the signed-rank test in terms of power. Traditional adjustment methods often lead to a misspeci fied sign-test. We propose a new and parsimonious method (the spread-matched method), which leads to a well-specifi ed and more powerful sign-test. The superiority of the spread-matched method is particularly evident for observations characterized by extreme levels of CDS spread. Analyses of CDS samples differing by contract maturity, data source, and time period confi rm these results. We perform an event study on rating downgrades to illustrate how the choice of tests and adjustment methods can affect inference.

Keywords: Event studies, Credit default swap, Matching portfolio models, Size and power of tests

JEL Classification: G10, G14

Suggested Citation

Bertoni, Fabio and Lugo, Stefano, Detecting Abnormal Changes in Credit Default Swap Spreads Using Matching-Portfolio Models (March 30, 2018). Journal of Banking and Finance, Forthcoming, Available at SSRN: https://ssrn.com/abstract=2743243 or http://dx.doi.org/10.2139/ssrn.2743243

Fabio Bertoni (Contact Author)

EM Lyon (Ecole de Management de Lyon) - Department of Economics, Finance, Control ( email )

23, av. Guy de Collongue BP 174
69132 Ecully Cedex
France

Stefano Lugo

Utrecht University - School of Economics ( email )

Kriekenpitplein 21-22
Adam Smith Building
Utrecht, +31 30 253 7373 3584 EC
Netherlands

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