Emotions in Macroeconomic News and their Impact on the European Bond Market
| Autor: | Elisa Tosetti, Sergio Consoli, Luca Tiozzo Pezzoli |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
I.2
FOS: Computer and information sciences Economics and Econometrics Computer Science - Machine Learning Physics - Physics and Society General Economics (econ.GN) J.4 G.3 Settore SECS-P/05 - Econometria Emotions extraction FOS: Physical sciences Monetary economics Physics and Society (physics.soc-ph) News Statistics - Applications Machine Learning (cs.LG) Power (social and political) FOS: Economics and business Politics Yield spread GDELT 62P20 68T01 Economics Applications (stat.AP) Neighbourhood (mathematics) Economics - General Economics Government Text analysis Tone (literature) Settore SECS-S/03 - Statistica Economica Sovereign bond yield spreads Bond market Construct (philosophy) Finance |
| DOI: | 10.48550/arxiv.2106.15698 |
| Popis: | We show how emotions extracted from macroeconomic news can be used to explain and forecast future behaviour of sovereign bond yield spreads in Italy and Spain. We use a big, open-source, database known as Global Database of Events, Language and Tone to construct emotion indicators of bond market affective states. We find that negative emotions extracted from news improve the forecasting power of government yield spread models during distressed periods even after controlling for the number of negative words present in the text. In addition, stronger negative emotions, such as panic, reveal useful information for predicting changes in spread at the short-term horizon, while milder emotions, such as distress, are useful at longer time horizons. Emotions generated by the Italian political turmoil propagate to the Spanish news affecting this neighbourhood market. Comment: Journal of International Money and Finance (to appear); 39 pages; 14 figures |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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