We use data on financially distressed Chinese companies in order to study a debt market where property rights are crudely defined and poorly enforced. To help with identification we use an event where a business-friendly province published new guidelines regarding the administration and...

This paper analyses factors that account for credit risk in the Chinese market for bonds issued by non-financial enterprises. By exploring a data set of covering monthly observations of individual corporate and enterprise bonds a number of important structural features of the market are seen to...

This paper examines the relation between share pledging and corporate risk-taking in an environment featured by strong government intervention and high information opacity. We find that during the years 2005 through 2015, the level of share pledging is associated with less volatile earnings and...

The role of development finance institutions in low-income and emerging countries is fundamental to provide long-term capital for investments in climate mitigation and adaptation. Nevertheless, development finance institutions still lack sound and transparent metrics to assess the exposure of...

We study the market performance of Chinese companies listed in the U.S. stock exchanges using machine learning methods. Predicting the market performance of U.S. listed Chinese firms is a challenging task due to the scarcity of data and the large set of unknown predictors involved in the...

In response to the recent elevated corporate credit risk environment in China’s credit market, we develop a probability of default (PD) measure for Chinese companies using actual corporate bond defaults by applying the Least Absolute Shrinkage and Selection Operator (LASSO) machine learning...

This paper examines the intra-industry effects of bond defaults on corporate cash holdings. The staggered difference-in-differences regression results find that corporate cash holdings decrease following the first default within each industry, and the results are driven by firms with more severe...