2014
DOI: 10.1111/abac.12022
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The Information Content of Ratings: An Analysis of Australian Credit Default Swap Spreads

Abstract: We examine the information content of Australian credit rating announcements by measuring the abnormal changes in credit default swap (CDS) spreads. CDS spreads provide a direct view of credit quality and thus should impound information quickly when investors receive new credit risk related information via a rating event. Using an event study methodology, we show that watch downs and rating upgrades contain valuable information even after controlling for sources of contamination. We find that watch downs elici… Show more

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Cited by 10 publications
(11 citation statements)
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References 24 publications
(45 reference statements)
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“…() and Wang et al . () also find an increase in CDS spreads up to 90 days ahead of a ratings downgrade, review for downgrade and a negative outlook event . Blanco et al .…”
Section: Empirical Literaturementioning
confidence: 78%
“…() and Wang et al . () also find an increase in CDS spreads up to 90 days ahead of a ratings downgrade, review for downgrade and a negative outlook event . Blanco et al .…”
Section: Empirical Literaturementioning
confidence: 78%
“…Our survey results are inconsistent with the indirect results from two empirical studies relating to credit ratings. For example, Dang and Partington (2014) find that the historical credit rating plays a more important role in predicting the next rating change than current rating, and Wang, Svec and Peat (2014) find that the movement in credit rating events contains value-relevant information in Australia.…”
Section: Do Firms Have Target Credit Ratings?mentioning
confidence: 99%
“…Wang et al . () find that credit rating announcements have significant impact on CDS spread changes. As mentioned previously, due to both CDSs and credit ratings being driven by the credit quality of the underlying asset, credit ratings published by rating agencies, are used as a proxy for the credit risk of issuers and issues.…”
Section: Econometric Model and Datamentioning
confidence: 96%