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Exploring the Initial Impact of COVID-19 Sentiment on US Stock Market Using Big Data

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  • Hee Soo Lee

    (School of Business, Sejong University, Seoul 05006, Korea)

Abstract

This study explores the initial impact of COVID-19 sentiment on US stock market using big data. Using the Daily News Sentiment Index (DNSI) and Google Trends data on coronavirus-related searches, this study investigates the correlation between COVID-19 sentiment and 11 select sector indices of the Unites States (US) stock market over the period from 21st of January 2020 to 20th of May 2020. While extensive research on sentiment analysis for predicting stock market movement use tweeter data, not much has used DNSI or Google Trends data. In addition, this study examines whether changes in DNSI predict US industry returns differently by estimating the time series regression model with excess returns of industry as the dependent variable. The excess returns are obtained from the Fama-French three factor model. The results of this study offer a comprehensive view of the initial impact of COVID-19 sentiment on the US stock market by industry and furthermore suggests the strategic investment planning considering the time lag perspectives by visualizing changes in the correlation level by time lag differences.

Suggested Citation

  • Hee Soo Lee, 2020. "Exploring the Initial Impact of COVID-19 Sentiment on US Stock Market Using Big Data," Sustainability, MDPI, vol. 12(16), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:16:p:6648-:d:400164
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    Cited by:

    1. Mirosław Bełej, 2022. "Does Google Trends Show the Strength of Social Interest as a Predictor of Housing Price Dynamics?," Sustainability, MDPI, vol. 14(9), pages 1-14, May.
    2. Katerina Lyroudi & Sotirios Nikolopoulos, 2021. "Stock Market Reaction at the WHO’s Announcement of a Pandemic due to COVID-19 of the French Pharmaceuticals," European Research Studies Journal, European Research Studies Journal, vol. 0(3B), pages 482-496.
    3. Nikolaos Apostolopoulos & Panagiotis Liargovas & Nikolaos Rodousakis & George Soklis, 2022. "COVID-19 in US Economy: Structural Analysis and Policy Proposals," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
    4. Deimante Teresiene & Greta Keliuotyte-Staniuleniene & Yiyi Liao & Rasa Kanapickiene & Ruihui Pu & Siyan Hu & Xiao-Guang Yue, 2021. "The Impact of the COVID-19 Pandemic on Consumer and Business Confidence Indicators," JRFM, MDPI, vol. 14(4), pages 1-23, April.
    5. Tsai, I-Chun & Chen, Han-Bo & Lin, Che-Chun, 2024. "The ability of energy commodities to hedge the dynamic risk of epidemic black swans," Resources Policy, Elsevier, vol. 89(C).
    6. Cervantes, Paula & Díaz, Antonio & Esparcia, Carlos & Huélamo, Diego, 2022. "The impact of COVID-19 induced panic on stock market returns: A two-year experience," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 1075-1097.
    7. Ngo Thai Hung, 2022. "The COVID-19 effects on cryptocurrency markets: robust evidence from time-frequency analysis," Economics Bulletin, AccessEcon, vol. 42(1), pages 109-123.
    8. Jin, Lifu & Zheng, Bo & Ma, Jiahao & Zhang, Jiu & Xiong, Long & Jiang, Xiongfei & Li, Jiangcheng, 2022. "Empirical study and model simulation of global stock market dynamics during COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    9. Ahelegbey, Daniel Felix & Cerchiello, Paola & Scaramozzino, Roberta, 2022. "Network based evidence of the financial impact of Covid-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 81(C).
    10. Helen Chiappini & Gianfranco Vento & Leonardo De Palma, 2021. "The Impact of COVID-19 Lockdowns on Sustainable Indexes," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    11. Iustina Alina Boitan & Emilia Mioara Campeanu & Sanja Sever Malis, 2021. "Economic Sentiment Perceptions During COVID-19 Pandemic – A European Cross-Country Impact Assessment," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(Special15), pages 982-982, November.
    12. Ahelegbey, Daniel Felix & Celani, Alessandro & Cerchiello, Paola, 2024. "Measuring the impact of the EU health emergency response authority on the economic sectors and the public sentiment," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    13. Arhan Sheth & Tulasi Sushra & Ameya Kshirsagar & Manan Shah, 2022. "Global Economic Impact in Stock and Commodity Markets during Covid-19 pandemic," Annals of Data Science, Springer, vol. 9(5), pages 889-907, October.
    14. Li, Yanshuang & Shi, Yujie & Shi, Yongdong & Xiong, Xiong & Yi, Shangkun, 2024. "Time-frequency extreme risk spillovers between COVID-19 news-based panic sentiment and stock market volatility in the multi-layer network: Evidence from the RCEP countries," International Review of Financial Analysis, Elsevier, vol. 94(C).
    15. Al-Maadid, Alanoud & Alhazbi, Saleh & Al-Thelaya, Khaled, 2022. "Using machine learning to analyze the impact of coronavirus pandemic news on the stock markets in GCC countries," Research in International Business and Finance, Elsevier, vol. 61(C).
    16. Zeitun, Rami & Rehman, Mobeen Ur & Ahmad, Nasir & Vo, Xuan Vinh, 2023. "The impact of Twitter-based sentiment on US sectoral returns," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).

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