Abstract
We enhance the modelling and risk assessment of sovereign bond spreads by taking into account quantitative information gained from macro-economic news sentiment. We investigate sovereign bonds spreads of five European countries and improve the prediction of spread changes by incorporating news sentiment from relevant entities and macro-economic topics. In particular, we create daily news sentiment series from sentiment scores as well as positive and negative news volume and investigate their effects on yield spreads and spread volatility. We conduct a correlation and rolling correlation analysis between sovereign bond spreads and accumulated sentiment series and analyse changing correlation patterns over time. Market regimes are detected through correlation series and the impact of news sentiment on sovereign bonds in different market circumstances is investigated. We find best-suited external variables for forecasts in an ARIMAX model set-up. Error measures for forecasts of spread changes and volatility proxies are improved when sentiment is considered. These findings are then utilised to monitor sovereign bonds from European countries and detect changing risks through time.
Highlights
In the wake of the sovereign debt crisis in Europe, managing and monitoring credit risk arising from sovereign bonds are increasingly important
Less effort has been put into establishing the link between daily news sentiment and the dynamics of bond spreads
Our analysis finds significant correlations between aggregated daily macroeconomic news time series and sovereign bond spreads in five European countries
Summary
In the wake of the sovereign debt crisis in Europe, managing and monitoring credit risk arising from sovereign bonds are increasingly important. Modelling of sovereign bond spreads is often linked to various macroeconomic factors such as the countries’ GDP growth rate or inflation. These macroeconomic factors are monitored via scheduled announcements from official bodies e.g., treasuries and national banks but are covered in news articles and unscheduled announcements. Changes in country dynamics and risks are reported and captured in news, which are classified as “macroeconomic news”, and can be closely monitored and quantified through news sentiment analysis. The dynamics of asset prices, in particular their volatility, is clearly affected by news events These events are classified and quantified, and news sentiment can be utilised to enhance volatility prediction (see, e.g., (Mitra et al 2009)).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
