Machine learning sentiment analysis, COVID-19 news and stock market reactions

  • The possibility to investigate the impact of news on stock prices has observed a strong evolution thanks to the recent use of natural language processing (NLP) in finance and economics. In this paper, we investigate COVID-19 news, elaborated with the ”Natural Language Toolkit” that uses machine learning models to extract the news’ sentiment. We consider the period from January till June 2020 and analyze 203,886 online articles that deal with the pandemic and that were published on three platforms: MarketWatch.com, Reuters.com and NYtimes.com. Our findings show that there is a significant and positive relationship between sentiment score and market returns. This result indicates that an increase (decrease) in the sentiment score implies a rise in positive (negative) news and corresponds to positive (negative) market returns. We also find that the variance of the sentiments and the volume of the news sources for Reuters and MarketWatch, respectively, are negatively associated to market returns indicating that an increase of the uncertainty of the sentiment and an increase in the arrival of news have an adverse impact on the stock market.

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Author:Michele CostolaORCiD, Michael Nofer, Oliver HinzORCiDGND, Loriana PelizzonORCiDGND
URN:urn:nbn:de:hebis:30:3-552475
URL:https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3690922
Parent Title (English):SAFE working paper series ; No. 288
Series (Serial Number):SAFE working paper series (288)
Publisher:SAFE
Place of publication:Frankfurt am Main
Document Type:Working Paper
Language:English
Year of Completion:2020
Year of first Publication:2020
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2020/09/15
Tag:COVID-19 news; Sentiment Analysis; Stock Markets
Page Number:15
HeBIS-PPN:470270551
Institutes:Wirtschaftswissenschaften / Wirtschaftswissenschaften
Wissenschaftliche Zentren und koordinierte Programme / House of Finance (HoF)
Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS)
Wissenschaftliche Zentren und koordinierte Programme / Sustainable Architecture for Finance in Europe (SAFE)
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
Sammlungen:Universitätspublikationen
Licence (German):License LogoDeutsches Urheberrecht