EconPapers    
Economics at your fingertips  
 

Using Social Media to Predict the Stock Market Crash and Rebound amid the Pandemic: The Digital ‘Haves’ and ‘Have-mores’

Chong Guan (), Wenting Liu and Jack Yu-Chao Cheng
Additional contact information
Chong Guan: Singapore University of Social Sciences
Wenting Liu: Singapore University of Social Sciences
Jack Yu-Chao Cheng: Intellectual Property Office of Singapore International

Annals of Data Science, 2022, vol. 9, issue 1, No 2, 5-31

Abstract: Abstract Since the 2019 novel Coronavirus disease (COVID-19) spread across the globe, risks brought by the pandemic set in and stock markets tumbled worldwide. Amidst the bleak economic outlook, investors’ concerns over the pandemic spread rapidly through social media but wore out shortly. Similarly, the crash only caused a relatively short-lived bear market, which bottomed out and recovered quickly. Meanwhile, technology stocks have grabbed the spotlight as the digitally advanced sectors seemed to show resilience in this Coronavirus-plagued market. This paper aims to examine market sentiments using social media to predict the stock market performance before, during and after the March 2020 stock market crash. In addition, using the Organisation for Economic Co-operation and Development Taxonomy of Sectoral Digital-intensity Framework, we identified market sectors that have outperformed others as the market sentiment was impacted by the unfolding of the pandemic. The daily stock performance of a usable sample of 1619 firms from 34 sectors was first examined via a combination of hierarchical clustering and shape-based distance measure. This was then tested against a time series of daily price changes through augmented vector auto-regression. Results show that market sentiments towards the pandemic have significantly impacted the price differences. More interestingly, the stock performance across sectors is characterized by the level of digital intensity, with the most digitally advanced sectors demonstrating resilience against negative market sentiments on the pandemic. This research is among the first to demonstrate how digital intensity mitigates the negative effect of a crisis on stock market performance.

Keywords: Stock market; COVID-19; Social media; Digital intensity (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://link.springer.com/10.1007/s40745-021-00353-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:aodasc:v:9:y:2022:i:1:d:10.1007_s40745-021-00353-w

Ordering information: This journal article can be ordered from
https://www.springer ... gement/journal/40745

DOI: 10.1007/s40745-021-00353-w

Access Statistics for this article

Annals of Data Science is currently edited by Yong Shi

More articles in Annals of Data Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:aodasc:v:9:y:2022:i:1:d:10.1007_s40745-021-00353-w