News-based sentiment: can it explain market performance before and after the Russia–Ukraine conflict?

Viet Hoang Le, Hans-Jörg von Mettenheim, Stéphane Goutte and Fei Liu

Journal of Risk Finance, 2022, vol. 24, issue 1, 72-88

Abstract: Purpose - The purpose of this paper is to analyze the market response of the aerospace and defense industry and the airline industry to the ongoing conflict between Ukraine and Russia based on the sentiments from war-related news articles over the period from October 2021 to June 2022. Design/methodology/approach - The study uses the news article database of Global Database of Events, Languages and Tone (GDELT) to create a new set of variables that reflect the news sentiment regarding war and conflict. By investigating the newly created sentiment variables in combination with traditional event study methodology, the authors seek to find out whether sentiment indicators can be helpful to rationalize the evolution of the different stock markets before and after the conflict. Findings - The authors' results point out a significant negative impact of the war on the airline market and a positive impact on the defense market. The authors' study also introduces a new set of war-related news-based sentiment variables that is significant to explain the evolution of the two markets before and after the war. The relationships between this study's new set of variables and the performance of the two markets are also proven to be significantly impacted by the invasion. Originality/value - To the best of the authors' knowledge, this is the first research to use the news sentiment related to the topic of war and conflict to explain the market movement of different industries during the Ukraine invasion.

Keywords: Ukraine war; Stock market prediction; Sentiment analysis; Big data; GDELT (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Working Paper: News-based sentiment: can it explain market performance before and after the Russia–Ukraine conflict? (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:eme:jrfpps:jrf-06-2022-0168

DOI: 10.1108/JRF-06-2022-0168

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