Emotions in macroeconomic news and their impact on the European bond market

Sergio Consoli, Luca Tiozzo Pezzoli and Elisa Tosetti

Journal of International Money and Finance, 2021, vol. 118, issue C

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.

Keywords: Sovereign bond yield spreads; News; Text analysis; Emotions extraction; GDELT (search for similar items in EconPapers)
JEL-codes: E43 G12 G17 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Working Paper: Emotions in Macroeconomic News and their Impact on the European Bond Market (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jimfin:v:118:y:2021:i:c:s0261560621001236

DOI: 10.1016/j.jimonfin.2021.102472

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