The Effect of Timeliness and Credit Ratings on the Information Content of Earnings Announcements

Abstract

This paper investigates the impact of timeliness and credit ratings on the information content of the earnings announcements of Greek listed firms from 2001 to 2008. Using the classical event study methodology and regression analysis, we find that firms tend to release good news on time and are inclined to delay the release of bad news. We also provide evidence that the level of corporate risk differentiates the information content of earnings according to the credit rating category. Specifically, firms displaying high creditworthiness enjoy positive excess returns on earnings announcement dates. In contrast, firms with low creditworthiness undergo significant share price erosions on earnings announcement days. We also observe a substitution effect between timeliness and credit ratings in relation to the information content of earnings announcements. Specifically, we find that as the credit category of earnings-announcing firms improves, the informational role of timeliness is mitigated.

Key Words:

• Earnings Announcements
• Credit Ratings
• Timeliness
• Information Asymmetry
• Athens Stock Exchange.

JEL classifications:

• G14
• G15.

The authors would like to thank two anonymous referees for their helpful comments and suggestions.

Notes

1. In a famous case, the ratings for the now defunct Enron remained at investment grade four days before it went bankrupt, despite the fact that credit rating agencies had been well aware of its problems for months (Borrus 2002).

2. For example, there have been press releases concerning EADS, the parent company of the Airbus jet manufacturer, about postponing the news of delayed delivery of the new A380 jetliner from April 2006 to June 2006. This caused severe criticism of the managers, which, in turn, led EADS to lose a quarter of its value (Kothari, Shu, and Wysocki 2009). For further examples and evidence, see Burns and Kedia (2006) and Cheng and Warfield (2005).

3. Jiang (2008) probed into the causal effect of earnings on the cost of debt as proxied by credit ratings, but not the reverse effect.

4. We use credit rating data from Amadeus, one of the leading credit rating agencies on corporate creditworthiness in Europe.

5. According to Brown and Warner (1985), the nonsynchronous trading problem may result in biased estimates of market model parameters.

6. Results remain similar at different thresholds (e.g., 1% and 2%).

7. According to Bartholdy et al. (2007), the standard estimation period for thin markets is between 200 and 250 observations (i.e., about a year of trading prior to the three-day event period).

8. An alternative way of calculating unexpected earnings changes is to use the consensus of financial analyst forecasts as a benchmark (the expected earnings). However, financial analyst forecasts were available for only a very limited number of Greek listed firms.

9. The number of firms belonging to the “risky” group is profoundly smaller compared to the other groups and, for this reason, solid conclusions could not be reached. Moreover, we cannot identify early announcing firms for this group of firms.