Corporate credit rating announcements : information content of rating announcements models : evidence from the Australian financial markets

University of Technology, Sydney. Faculty of Business.Rating agencies have claimed that their rating announcements incorporate both publicly available information and information provided directly by rated issuers. Thus the announcements of rating have the potential to provide information that will impact on the equity and bond markets. The dissertation examines the impact that the release of ratings announcements had on equity and bond returns and also the factors that play a major role in determining the ratings assigned. The first part of the thesis examines the role of information asymmetry in determining the price effects of announcements of both rating changes and the placing of issuers on CreditWatch. Results from the event studies indicate that firms whose ratings were rerated downgrades and/or placed on negative CreditWatch record statistically significant negative excess equity returns. However, no such evidence is found in the bond market during the rating downgrades. The results support the presumption that rating downgrades and negative CreditWatch announcements provide new information to the market. Furthermore, we find some evidences of bond market positively reacting to issuers whose ratings were upgraded and/or placed on positive CreditWatch but no such evidence is found in the equity market. Interestingly, we find that equity and bond markets respond more vigorously to information preceding rating announcements, which suggests that rating announcements provided by the rating agencies are anticipated by market participants. Further, we document that markets tend to react more significantly when the rating announcement is unexpected, contaminated, a cross-classes rating changes and/or due to the firm changing its financial structure. The second part of the thesis examines the impact of various accounting; financial and economic variables in the determination of the ratings. A multiple logistic regression model, which incorporates accounting; finance and economic variables, suggests that debt coverage and earning stability have the most pronounced effect on rating change announcements. When conducting both in-sample and out-of-sample forecast, the model is consistently forecast towards rating no changes. Also, we document that the success rate of out-of-sample forecasts using a moving window procedure is higher than normal out-of-sample forecast procedure