Abstract

This paper first sets up a theoretical model to describe a credit rating agency's (CRA) two roles, namely rating and monitoring. Through CRA's monitoring role, bonds no longer represent loan contracts without monitoring. In the model, bond issuers have to decide whether to go through CRA or borrow directly, and whether to take action to prevent future risk or not. CRA's monitoring ability is shown to be crucial. If CRA can observe creditworthiness changes more accurately so as to offer ratings with less noise, there will be more issuers willing to signal their qualities and take action. If CRA can attract issuers to take action but cannot function in its monitoring role well enough, social welfare will be reduced after introducing CRA into the market.;This paper then examines price adjustments in bond and equity markets according to Moody's bond rating watchlist announcements and actual rating change announcements afterwards. Based on different methods of calculating excess returns, we find that asset prices react in response to Moody's rating announcements, suggesting that they convey valuable information to both bond and equity markets and investors adjust prices according to both upgrading and downgrading directions. When we control for bond rating grades, the evidence of market reactions is more significant than without the control; in contrast, controlling for a stock's beta is not so beneficial. Stronger evidence of market reactions is found in bond markets than in equity markets.;Lastly, Generalized Linear Models (GLMs) with fixed and mixed effects are applied to describe how an issuer matches with an underwriter for an initial public offering (IPO). The study focuses on the issuer's preference over underwriter reputation. From GLM with fixed effects, we find that the issuer tends to choose a high-reputation underwriter when the IPO's expected offer size is large, the expected offer price is high, the issuer is a young firm, there is venture capital backing, the issuer has more assets, or the issuer's leverage ratio is small. From the random effect in GLM with mixed effects, we find that issuers in the state of California or in the Service and Utility industries are more likely to choose high-reputation underwriters than issuers in other states or industries. Underwriters with high reputation tend to have larger sales forces and have headquarters in New York. Using propensity score matching methods, we find that underwriters with high reputation are generally associated with larger underpricings. The subsamples by the location of offer price in the filing range confirm such positive relation. However, evidence from subperiods shows that the larger underpricing is likely to be both an issuer's industry effect and an underwriter's reputation effect.

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