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Emotions in Macroeconomic News and their Impact on the European Bond Market

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  • Sergio Consoli
  • Luca Tiozzo Pezzoli
  • Elisa Tosetti

Abstract

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.

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  • Sergio Consoli & Luca Tiozzo Pezzoli & Elisa Tosetti, 2021. "Emotions in Macroeconomic News and their Impact on the European Bond Market," Papers 2106.15698, arXiv.org.
    • Handle: RePEc:arx:papers:2106.15698
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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects

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