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Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic

As the 2019 novel coronavirus disease (COVID-19) pandemic rages globally, its impact has been felt in the stock markets around the world. Amidst the gloomy economic outlook, certain sectors seem to have survived better than others. This paper aims to investigate the sectors that have performed bette...

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Autores principales: Ding, Ding, Guan, Chong, Chan, Calvin M. L., Liu, Wenting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7502306/
http://dx.doi.org/10.1186/s11782-020-00089-z
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author Ding, Ding
Guan, Chong
Chan, Calvin M. L.
Liu, Wenting
author_facet Ding, Ding
Guan, Chong
Chan, Calvin M. L.
Liu, Wenting
author_sort Ding, Ding
collection PubMed
description As the 2019 novel coronavirus disease (COVID-19) pandemic rages globally, its impact has been felt in the stock markets around the world. Amidst the gloomy economic outlook, certain sectors seem to have survived better than others. This paper aims to investigate the sectors that have performed better even as market sentiment is affected by the pandemic. The daily closing stock prices of a total usable sample of 1,567 firms from 37 sectors are first analyzed using a combination of hierarchical clustering and shape-based distance (SBD) measures. Market sentiment is modeled from Google Trends on the COVID-19 pandemic. This is then analyzed against the time series of daily closing stock prices using augmented vector autoregression (VAR). The empirical results indicate that market sentiment towards the pandemic has significant effects on the stock prices of the sectors. Particularly, the stock price performance across sectors is differentiated by the level of the digital transformation of sectors, with those that are most digitally transformed, showing resilience towards negative market sentiment on the pandemic. This study contributes to the existing literature by incorporating search trends to analyze market sentiment, and by showing that digital transformation moderated the stock market resilience of firms against concern over the COVID-19 outbreak.
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spelling pubmed-75023062020-09-21 Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic Ding, Ding Guan, Chong Chan, Calvin M. L. Liu, Wenting Front. Bus. Res. China Research As the 2019 novel coronavirus disease (COVID-19) pandemic rages globally, its impact has been felt in the stock markets around the world. Amidst the gloomy economic outlook, certain sectors seem to have survived better than others. This paper aims to investigate the sectors that have performed better even as market sentiment is affected by the pandemic. The daily closing stock prices of a total usable sample of 1,567 firms from 37 sectors are first analyzed using a combination of hierarchical clustering and shape-based distance (SBD) measures. Market sentiment is modeled from Google Trends on the COVID-19 pandemic. This is then analyzed against the time series of daily closing stock prices using augmented vector autoregression (VAR). The empirical results indicate that market sentiment towards the pandemic has significant effects on the stock prices of the sectors. Particularly, the stock price performance across sectors is differentiated by the level of the digital transformation of sectors, with those that are most digitally transformed, showing resilience towards negative market sentiment on the pandemic. This study contributes to the existing literature by incorporating search trends to analyze market sentiment, and by showing that digital transformation moderated the stock market resilience of firms against concern over the COVID-19 outbreak. Springer Singapore 2020-09-21 2020 /pmc/articles/PMC7502306/ http://dx.doi.org/10.1186/s11782-020-00089-z Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Research
Ding, Ding
Guan, Chong
Chan, Calvin M. L.
Liu, Wenting
Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic
title Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic
title_full Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic
title_fullStr Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic
title_full_unstemmed Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic
title_short Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic
title_sort building stock market resilience through digital transformation: using google trends to analyze the impact of covid-19 pandemic
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7502306/
http://dx.doi.org/10.1186/s11782-020-00089-z
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