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 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.

We examine whether and to what extent business shocks explain the puzzling instabilities of corporate leverage. We find that business shocks explain a large portion of the unexplained leverage deviation, cross-sectional leverage position migration, and evaporating leverage similarities in the cross-section of firms. The cross-sectional distribution of corporate leverage is relatively persistent when there are fewer and smaller business shocks but becomes unstable for firms with larger business shocks. Our findings suggest that business shocks lead to discontinuities in the corporate value creation process and investment, thereby affecting corporate financing decisions. Put simply, the lumpiness of investment creates a “lumpy need for external financing. Our analysis implies that the empirical modeling of capital structure adjustment and, indeed, the modeling of other corporate policies, should be conditioned on business shocks.