Anatomy of sovereign yield behaviour using textual news

Abstract

While the relationship between the information content of macroeconomic news and the behavior of asset prices has been studied extensively in the finance literature, this study provides a new perspective by examining the impact of textual news on sovereign bond yield spreads in an emerging country. This study used bond market news published in newspapers to develop the sentiment scores using a modified word dictionary to unravel news characteristics. A nonlinear regime-shifting regression model of Markov Regime Shifting (MRS) is used to understand the impact of news on sovereign bond yield spreads. The paper results show that textual news sentiment may explain both steepening and flattening of the yield curve, with monetary and fiscal policy news having the most significant impact on yield spread behaviour. The results hold key implications for policymakers, debt fund managers and other market participants.