In this paper we employ a new approach to test the contribution of information in rating announcements. This is the first study to test and corroborate how the CDS market responds to rating actions after controlling for the presence of concurrent public and private information. We show that since the clustering of rating announcements characterizes economically significant developments, the common practice of using “uncontaminated” samples underestimates market response. As in previous studies, we find that the market response to bad news is stronger than to good news. Nevertheless, bad news and negative rating announcements tend to cluster. Therefore, the residual contribution of negative rating announcements is small and in some cases insignificant. Positive rating announcements are less frequent and less clustered, though their residual contribution is still significant.

This work examines the information value of local Israeli credit rating announcements. This matter is also important to other small markets, in which a debt issuer may take advantage of a “rating shopping” process or choose to avoid a rating procedure altogether, because the agencies do not carry out unsolicited rating. We analyze the bond and equity markets response to various rating announcements at different time periods. We find that except for downgrades in 2008–2009 the rating announcements have no information value. It seems that generally the market internalizes most of the information prior to the rating announcements.

Prior studies indicate that rating agencies have adopted more stringent rating criteria over time. In this paper, we hypothesize that improvements in rating accuracy can explain some of these observed patterns. We present empirical evidence supporting this hypothesis, demonstrating that enhancements in rating methodologies have resulted in better default prediction. Our analysis also reveals that, over time, ratings have become more closely aligned with accounting fundamentals and a market-based measure of default risk (distance-to-default). These findings provide a fresh perspective on the factors influencing changes in credit rating standards and emphasize the significance of methodological advancements in credit risk assessment. This research introduces the novel argument that enhancing rating accuracy is an economic rationale for long-term rating trends. The findings underscore the continued importance of credit ratings despite criticisms, suggesting that ratings remain a valuable tool for investors.

Prior research on the impact of market power on firms’ willingness to extend trade credit has produced inconsistent results, highlighting a critical gap in understanding firm behavior. This study addresses this issue by analyzing a comprehensive dataset of industrial firms across 26 countries, focusing on how the relationship between market power and trade credit depends on a country’s financial development level. Firms with monopolistic power often restrict credit provision to improve cash flow. However, our findings reveal a U-shaped relationship, where monopolistic firms in countries with either underdeveloped or highly developed financial sectors are more likely to extend trade credit than those in mid-level financial systems. This highlights the moderating role of financial development in shaping the interaction between market power and trade credit behavior.

This study proposes models that can be used as shorthand analysis tools for CDS spreads and CDS spread changes. For this purpose, we examine the determinants of CDS spreads and spread changes on a broad database of 718 US firms during the period from early 2002 to early 2013. Contrary to previous studies, we find that market variables have explanatory power after controlling for firm-specific variables inspired by structural models. Three explanatory variables appear to outperform the other variables examined in this paper: Stock Return, the change in stock return volatility, and the change in the median CDS spread in the rating class. We also find that models used in the event study literature to explain spread changes can be improved by adding market variables. Furthermore, we show that ratings explain cross-sectional variation in CDS spreads even after controlling for structural model variables.