Impacts of COVID-19 local spread and Google search trend on the US stock market

Dey, Asim Kumer; Hoque, G.M. Toufiqul; Das, Kumer Pial; Panovska, Irina

doi:10.1016/j.physa.2021.126423

Cited by 17 publications

(18 citation statements)

References 80 publications

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“…Our findings complement recent studies on COVID-19 news and the financial market. Differently from the branch that emerged with the use of Google search volume as a proxy of public attention ( Lyócsa et al, 2020 , Costola et al, 2020 , Salisu and Vo, 2020 , Dey et al, 2022 ), we contribute to the stream of literature on news sentiment analysis. In this regard, Haroon and Rizvi (2020) investigate the relationship between coronavirus-related news and volatility of equity markets and find that panic news is associated with volatility in the stock markets.…”

Section: Discussionmentioning

confidence: 99%

Machine learning sentiment analysis, COVID-19 news and stock market reactions

Costola

Nofer

Hinz

et al. 2023

Research in International Business and Finance

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Section: Discussionmentioning

confidence: 99%

Machine learning sentiment analysis, COVID-19 news and stock market reactions

Costola

Nofer

Hinz

et al. 2023

Research in International Business and Finance

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“…A few recent studies, such as Ding et al (2020), Costola et al (2021), Subramaniam and Chakraborty (2021), Batool et al (2021), and Dey et al (2022), have examined the effects of Covid‐19 on stock markets by employing Google Trends data. Following the similar approach adopted by these studies, the key phrase ‘Covid‐19’ was chosen.…”

Section: Data and Variablesmentioning

confidence: 99%

America's decoupling from China: A perspective from stock markets

Liu

2023

Economic Affairs

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America's decoupling‐from‐China debate started after July 2018, reached its peak in August 2020, and is likely to continue even if it may not be a high priority for the Biden administration. Many studies have examined various aspects of this issue, especially the potential economic impacts on the US economy. Unlike previous research, this study looks at the response of stock markets. Using Google Trends data, this study created a weekly dataset from January 2020 to June 2021 to measure investor sentiment towards the US decoupling from China. Employing the generalised autoregressive conditional heteroskedasticity (GARCH) models, the study finds that concern over decoupling is associated with significant variations in stock market prices. From this we can infer that the overall effects of decoupling on the US economy are likely to be considerable.

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“…The econometric models are used to study the impact of COVID-19 on stock market returns and volatilities [28] , [29] , [30] , and the deep learning models are applied to analyze the commodity prices [31] . Incorporating information about the epidemic improves the performance of forecasting the abnormal stock prices [32] , [33] . In this paper, we generalize the well-known Heston model to simulate the stock market dynamics under the influence of COVID-19, and explain the empirical findings from the real market data.…”

Section: Introductionmentioning

confidence: 99%