Using a comprehensive database of corporate news, we find that bond funds trade against the direction of news sentiment. The trading against news phenomenon is concentrated in funds selling on positive news and in the post-financial crisis period when dealer liquidity provision is constrained....

Using a comprehensive database of corporate news, we examine how bond mutual funds trade on the sentiment of news releases. We find that bond funds trade against the direction of news sentiment (e.g., selling after good news about a firm). The results are more pronounced in bonds that lie within...

We use supervised machine learning to develop a financial sentiment dictionary from 3.1 million Chinese-language financial news articles. Our dictionary maps semantically similar words to a subset of human-expert generated financial sentiment words. In validation tests, our dictionary scores the...

We examine the unique role played by institutional investors in the private corporate debt marketfor Rule 144A debt. We use the recent global financial crisis as a quasi-natural experiment to studyhow qualified institutional buyers (QIBs) facilitated funding to the foreign debt issuers in...

Remote islands, comprising over one-sixth of the Earth's surface area and home to approximately 9% of the global population, face formidable challenges in securing affordable, sustainable, and reliable energy. This paper presents a pioneering investigation into Mornington Island's transition...

Theory offers equivocal guidance on how enhanced corporate disclosure and transparency impact underlying liquidity. We examine the market liquidity effects of enhanced information induced by the public registration of 144A bonds, a significant and growing segment of the U.S. bond market. Using...

We examine institutional trading surrounding corporate news by combining a comprehensive database of newswire releases on U.S. firms with a high-frequency database of institutional trades. To identify the ability of institutions to predict or quickly interpret news, we form “news clusters”...