Stock market reactions to the COVID-19 pandemic: The moderating role of corporate big data strategies based on Word2Vec
Publication Type
Journal Article
Publication Date
9-2021
Abstract
By developing a machine learning-based measure of corporate big data strategies, this study empirically explores how stock markets respond to the COVID-19 pandemic and whether corporate big data strategies make firms immune to the pandemic effect. We find that except for information technology and health care sectors, firms in most sectors in China are negatively affected by the COVID-19 outbreak. Among these firms, an increase in the number of daily new confirmed cases in the city of a firm's headquarters is associated with a decrease in its stock prices, however, such a decline is attenuated for firms with a high emphasis on big data strategies. Our results are robust when we use COVID-19 cases at the whole country level.
Keywords
COVID-19 pandemic, Big data, Stock market, Machine learning
Discipline
Asian Studies | Numerical Analysis and Scientific Computing | Portfolio and Security Analysis
Research Areas
Information Systems and Management
Publication
Pacific Basin Finance Journal
Volume
68
First Page
1
Last Page
13
ISSN
0927-538X
Identifier
10.1016/j.pacfin.2021.101608
Publisher
Elsevier
Citation
XUE, Fujing; LI, Xiaoyu; ZHANG, Ting; and HU, Nan.
Stock market reactions to the COVID-19 pandemic: The moderating role of corporate big data strategies based on Word2Vec. (2021). Pacific Basin Finance Journal. 68, 1-13.
Available at: https://ink.library.smu.edu.sg/sis_research/8040
Copyright Owner and License
Authors
Additional URL
https://doi.org/10.1016/j.pacfin.2021.101608