The Information Efficiency of the Corporate Bond Market

• Main Author: YING, Cheng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2006
• Subjects: bonds; expected returns; information asymmetry; rate of return; securities markets; transaction costs; Portfolio and Security Analysis
• Online Access: https://ink.library.smu.edu.sg/etd_coll/45; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1044&context=etd_coll
• Institution: Singapore Management University

The link between asset prices and information fundamentals as embodied in news announcement effects is an extremely, if not the most, important area amongst current research in market microstructure. The lack of adequate transaction data posts an obstacle in this research. In this thesis, based on a valuable intraday transaction-by-transaction dataset for U.S. corporate bonds, we first examine the impact of public information contained in the macro-economic news and firm-specific information contained in corporate earnings annoucements on the prices of both corporate bonds and stocks. We find that both bonds and stocks react significantly to public news and firm-specific information, and this information is quickly incorporated into both bond and stock prices. More importantly, our results show that stocks do not lead bonds in reflecting firm-specific information, contrary to the conceived intuition that the bond market is less informationally efficient compared with the stock market. Next we examine the frequency of information arrivals of corporate bonds and its impacts on price duration at the intraday level. We find that there are differences in price durations between corporate bonds and stocks, and for a given company, the persistence of the impact on adjusted price duration is normally higher for stocks than bonds. Our results also show that the parameter estimates are more stable and statistically significant for stocks than for bonds in most cases, which indicate that the ACD model characterized the stock return behavior better than the bond data.