Covid-19 vaccines and investment performance: Evidence from equity funds in European Union

Mirza, Nawazish; Umar, Muhammad; Mangafić, Jasmina

doi:10.1016/j.frl.2023.103650

Cited by 9 publications

(1 citation statement)

References 23 publications

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“…In India, major COVID-19 studies focused on market reactions to governmental actions such as lockdowns (Alam et al , 2020; Basumatary and Jain, 2020), vaccination (Behera et al , 2022; Gupta and Gupta, 2023; Mirza et al , 2023; Yunus Kasim et al , 2022; Maneenop and Kotcharin, 2023) and COVID-19 cases (Kumar Digal et al , 2020), whereas a few investigated the impact of business announcements (Pandey et al , 2022).…”

Section: Literature Reviewmentioning

confidence: 99%

What determines the performance of pharmaceutical firms in India on account of COVID-19 interventions?

Lamba,

Aggarwal,

Gupta

et al. 2023

IJPHM

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Purpose This paper aims to examine the impact of announcements related to 77 interventions by 46 listed Indian pharmaceutical firms during COVID-19 on the abnormal returns of the firms. The study also finds the variables which explain cumulative abnormal returns (CARs). Design/methodology/approach This study uses standard event methodology to compute the abnormal returns of firms announcing pharmaceutical interventions in 2020 and 2021. Besides this, the multilayer perceptron technique is applied to identify the variables that influence the CARs of the sample firms. Findings The results show the presence of abnormal returns of 0.64% one day before the announcement, indicating information leakage. The multilayer perceptron approach identifies five variables that explain the CARs of the sample companies, which are licensing_age, licensing_size, size, commercialization_age and approval_age. Originality/value The study contributes to the efficient market literature by revealing how firm-specific nonfinancial disclosures affect stock prices, especially in times of crisis like pandemics. Prior research focused on determining the effect of COVID-19 variables on abnormal returns. This is the first research to use artificial neural networks to determine which firm-specific variables and pharmaceutical interventions can influence CARs.

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