Stock market reactions to the COVID-19 pandemic: The moderating role of corporate big data strategies based on Word2Vec

Fujing Xue, Xiaoyu Li, Ting Zhang and Nan Hu

Pacific-Basin Finance Journal, 2021, vol. 68, issue C

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 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:pacfin:v:68:y:2021:i:c:s0927538x21001153

DOI: 10.1016/j.pacfin.2021.101608

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