This paper investigates whether bond fund managers with credit rating experience outperform their peers. We document that bond fund managers who previously worked in credit rating agencies on average create higher risk-adjusted returns than their peers by 11–16 bps per month, with better security picking and market timing skills. We further confirm that this outperformance is sourced from their industry-specific knowledge gained via rating experience (specialization), rather than information advantage provided by previous colleagues (network). Last, we document net inflows to funds managed by agent managers, indicating the investor awareness of analyst managers' skill.

This study employs a broad set of machine learning (ML) methods to examine cross-sectional variation in corporate bond returns in China. Using macroeconomic indicators together with bond- and issuer-specific characteristics, we find that ML techniques outperform traditional linear models in both statistical and economic terms. These models are particularly effective at capturing distinctive features of the Chinese market, including the dominance of state-owned enterprises, implicit government guarantees, and rapid market evolution. We compare long-short and long-only portfolio strategies to account for practical constraints on short selling. The results indicate that ML methods are effective in markets where institutional features and information asymmetries play a central role in asset pricing.

We investigate the informational roles of foreign ownership in local credit rating agencies (CRAs) in the Chinese onshore debt market, which was the world's largest emerging debt market from 2008 to 2017. We find a robust negative relationship between the bond offering yield and foreign ownership in local CRAs, which suggests that these ratings certify the credit quality of debt issuers and thus enhance the market values of new debt issues. The information content of these ratings, however, is in contrast with the information provision role of foreign-owned CRAs (global CRAs). We find that these ratings provide no or weak better predictive power of issuers’ future credit performances than domestic CRAs. In addition, we find that stock and bond market reactions at the announcements of rating revisions made by global CRAs are not significantly different from those made by their domestic counterparts. We attribute the seemingly contradictory results to the preference for foreign brands in emerging markets and/or the improved bond liquidity associated with global CRA ratings.

We examine how the issuer-paid incumbent credit rating agencies (CRAs) in China adjust their rating strategies in response to the 2010 entry of an independent credit rating agency, China Bond Rating (CBR) between 2006 and 2015. The business model that CBR employs is a combination of the public utility model and the investor-paid model. We find that the CBR's ratings coverage effectively reduced the information asymmetry in the Chinese corporate bond market. The evidence shows decreased ratings inflation and increased informativeness of rating change announcements by incumbent issuer-paid CRAs after CBR entered the market. The findings suggest that a firm's credibility is an important channel driving issuer-paid incumbent CRAs’ strategic ratings. Our paper provides new information and insight into the debate of whether CRAs with alternative business models can alleviate the information asymmetry problem.

Regulatory punishment in an oligopolistic credit rating market can be costly. Utilizing the Chinese bond market’s unique features, particularly a third-party rating agency, we investigate the regulatory suspension of Dagong Rating by Chinese regulators and its market impact. The punishment initially deters Dagong but diminishes the quality of its ratings post-punishment, altering market competition. Upon returning, Dagong inflates ratings to regain market share, reflecting a “temporary suppression” strategy. Non-Dagong agencies respond by adjusting their ratings; higher power agencies lower ratings, while lower power agencies raise them to stay competitive. Investors remain skeptical of these inflated ratings. Despite Dagong’s suspension, we find no significant differences in bond or stock price reactions between Dagong-rated and non-Dagong-rated firms, suggesting investors did not penalize Dagong-rated entities. This study highlights the complex dynamics and unintended consequences of regulatory interventions in the credit rating market.