The Impact of Former US President Donald Trump's Tweets on Financial Markets

Elisabete Mendes Duarte (), Paulo Malaquias Filho and Maria João Jorge
Additional contact information
Elisabete Mendes Duarte: Politécnico de Leiria
Paulo Malaquias Filho: Politécnico de Leiria
Maria João Jorge: Politécnico de Leiria

A chapter in Rethinking Management and Economics in the New 20’s, 2023, pp 173-194 from Springer

Abstract: Abstract The present work addresses the impact of the tweets of the former US president, Donald Trump, on the international financial markets. This study aims to verify, through sentiment analysis, the relationship between the sentiments (positive, negative, and neutral) of the ex-president's tweets and the returns of the stock exchanges from the US (S&P500), Europe (Euronext 100) and China (CSI 300), using the text content analysis tool called VADER. For this, the returns of the stock market indexes were calculated, and the sentiment of the tweets were analyzed. It is observed that there were no statistically significant results between the sentiment analysis of the information published in the tweets by former President Donald Trump and the returns in the analyzed stock markets.

Keywords: Trump; Tweet impact; VADER; Financial markets; USA; Europe; China (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-981-19-8485-3_7

Ordering information: This item can be ordered from
http://www.springer.com/9789811984853

DOI: 10.1007/978-981-19-8485-3_7

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().