IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v15y2022i7p299-d857007.html
   My bibliography  Save this article

Evidence of Abnormal Trading on COVID-19 Pfizer Vaccine Development Information

Author

Listed:
  • Andrew N. Mason

    (School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan)

  • Ahmed Elkassabgi

    (College of Business, Arkansas Tech University, 106 West O Street, Rothwell Building #443, Russellville, AR 72801-2222, USA)

Abstract

The 2019 COVID-19 pandemic led to an economic slowdown worldwide and shook the investment world. Pharmaceutical investments were influenced by the anticipation of COVID-19 vaccine developments. Our study examines the real-time impact of public announcements concerning COVID-19 vaccine developments on stock returns and volatilities for Pfizer, Moderna, and the S&P 500. Market Return and Information Event methodology were used to analyze stock activities immediately before important public COVID-19 vaccine development announcements related to Pfizer and Moderna vaccines. This methodology was employed for vaccine news announcements between 2 January 2020 and 4 March 2022. Stock returns and volatility were analyzed with time-series regression analysis. Findings demonstrated that increased trade volatilities occurred immediately prior to COVID-19 vaccine development news was made public. Specifically, Pfizer stock returns were significantly higher (above the mean) immediately before positive COVID-19 vaccine development information was made public. Also, increased volume volatility was observed for Pfizer, Moderna, and the S&P 500 index stocks immediately before positive vaccine development information concerning Pfizer and Moderna vaccines were made public. These findings suggest that the vaccine information may have been leaked before being made public. If so, the findings may indicate that investors were taking advantage of insider information while trying to mitigate the appearance that they engaged in insider trading.

Suggested Citation

  • Andrew N. Mason & Ahmed Elkassabgi, 2022. "Evidence of Abnormal Trading on COVID-19 Pfizer Vaccine Development Information," JRFM, MDPI, vol. 15(7), pages 1-10, July.
    • Handle: RePEc:gam:jjrfmx:v:15:y:2022:i:7:p:299-:d:857007
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/15/7/299/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/15/7/299/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
    2. Kumar, Sushant & Dhir, Amandeep & Talwar, Shalini & Chakraborty, Debarun & Kaur, Puneet, 2021. "What drives brand love for natural products? The moderating role of household size," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    3. Dinh Hoang Bach Phan & Paresh Kumar Narayan, 2020. "Country Responses and the Reaction of the Stock Market to COVID-19—a Preliminary Exposition," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(10), pages 2138-2150, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kropiński, Paweł & Bosek, Bartłomiej & Pudo, Mikołaj, 2024. "State ownership, probability of informed trading, and profitability potential: Evidence from the Warsaw Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    2. Tom Deweerdt, 2022. "Why Is the Australian Health Sector So Far behind in Practising Climate-Related Disclosures?," IJERPH, MDPI, vol. 19(19), pages 1-11, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    2. Yue-Jun Zhang & Han Zhang, 2023. "Volatility Forecasting of Crude Oil Market: Which Structural Change Based GARCH Models have Better Performance?," The Energy Journal, , vol. 44(1), pages 175-194, January.
    3. Morais, Ana Catarina & Ishida, Akira & Matsuda, Ruriko, 2024. "Ethical food consumption drivers in Japan. A S–O-R framework application using PLS-SEM with a MGA assessment based on clustering," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    4. Mohsen Bahmani-Oskooee & Tsangyao Chang & Zahra (Mila) Elmi & Omid Ranjbar, 2018. "Re-testing Prebisch–Singer hypothesis: new evidence using Fourier quantile unit root test," Applied Economics, Taylor & Francis Journals, vol. 50(4), pages 441-454, January.
    5. Fleissig, Adrian & Swofford, James L., 1996. "A dynamic asymptotically ideal model of money demand," Journal of Monetary Economics, Elsevier, vol. 37(2-3), pages 371-380, April.
    6. Siyi Liu & Xin Liu & Chuancai Zhang & Lingli Zhang, 2023. "Institutional and individual investors' short‐term reactions to the COVID‐19 crisis in China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 4333-4355, December.
    7. Zhenkai Yang & Mei-Chih Wang & Tsangyao Chang & Wing-Keung Wong & Fangjhy Li, 2022. "Which Factors Determine CO 2 Emissions in China? Trade Openness, Financial Development, Coal Consumption, Economic Growth or Urbanization: Quantile Granger Causality Test," Energies, MDPI, vol. 15(7), pages 1-18, March.
    8. Tue Gørgens & Allan Würtz, 2012. "Testing a parametric function against a non‐parametric alternative in IV and GMM settings," Econometrics Journal, Royal Economic Society, vol. 15(3), pages 462-489, October.
    9. Uctum, Remzi & Renou-Maissant, Patricia & Prat, Georges & Lecarpentier-Moyal, Sylvie, 2017. "Persistence of announcement effects on the intraday volatility of stock returns: Evidence from individual data," Review of Financial Economics, Elsevier, vol. 35(C), pages 43-56.
    10. Atanu Ghoshray & Yurena Mendoza & Mercedes Monfort & Javier Ordoñez, 2018. "Re-assessing causality between energy consumption and economic growth," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-15, November.
    11. Claudio Morana & Giacomo Sbrana, 2017. "Temperature Anomalies, Radiative Forcing and ENSO," Working Papers 2017.09, Fondazione Eni Enrico Mattei.
    12. Lutho Mbekeni & Andrew Phiri, 2019. "Can the South African Reserve Bank (SARB) protect the purchasing power of citizens? A new look at Fisher’s hypothesis," Working Papers 1906, Department of Economics, Nelson Mandela University, revised Sep 2019.
    13. Prelorentzos, Arsenios-Georgios N. & Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Xidonas, Panos & Goutte, Stephane & Thomakos, Dimitrios D., 2024. "Introducing the GVAR-GARCH model: Evidence from financial markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    14. Apostolos Serletis, 2012. "International Evidence on Sectoral Interfuel Substitution," World Scientific Book Chapters, in: Interfuel Substitution, chapter 3, pages 37-65, World Scientific Publishing Co. Pte. Ltd..
    15. Talwar, Shalini & Kaur, Puneet & Escobar, Octavio & Lan, Sai, 2022. "Virtual reality tourism to satisfy wanderlust without wandering: An unconventional innovation to promote sustainability," Journal of Business Research, Elsevier, vol. 152(C), pages 128-143.
    16. Morana, Claudio, 2024. "A new macro-financial condition index for the euro area," Econometrics and Statistics, Elsevier, vol. 29(C), pages 64-87.
    17. Yingzhuo Yu & Cesar Escalante & Xiaohui Deng & Jack Houston & Lewell Gunter, 2011. "Analysing scale and scope specialization efficiencies of US agricultural and nonagricultural banks using the Fourier flexible functional form," Applied Financial Economics, Taylor & Francis Journals, vol. 21(15), pages 1103-1116.
    18. Łukasz Lenart & Błażej Mazur, 2016. "On Bayesian Inference for Almost Periodic in Mean Autoregressive Models," FindEcon Chapters: Forecasting Financial Markets and Economic Decision-Making, in: Magdalena Osińska (ed.), Statistical Review, vol. 63, 2016, 3, edition 1, volume 63, chapter 1, pages 255-272, University of Lodz.
    19. Tsangyao Chang & Tsung-Pao Wu & Rangan Gupta, 2015. "Are house prices in South Africa really nonstationary? Evidence from SPSM-based panel KSS test with a Fourier function," Applied Economics, Taylor & Francis Journals, vol. 47(1), pages 32-53, January.
    20. Harley Frazis & Jay Stewart, 2006. "How Does Household Production Affect Earnings Inequality?: Evidence from the American Time Use Survey," Economics Working Paper Archive wp_454, Levy Economics Institute.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jjrfmx:v:15:y:2022:i:7:p:299-:d:857007. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.