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Covid-19 pandemic and stock returns in India

Author

Listed:
  • Munusamy Dharani

    (Indian Institute of Management Kashipur)

  • M. Kabir Hassan

    (Indian Institute of Management Kashipur
    University of New Orleans)

  • Makeen Huda

    (Nicolls State University)

  • Mohammad Zoynul Abedin

    (Hajee Mohammad Danesh Science and Technology University)

Abstract

This paper examines whether the Covid-19 pandemic has had a homogeneous or heterogeneous effect on stock returns in India. We consider panel data by using 1,318 companies that are listed on the National Stock Exchange of India. We find that the daily growth rate in Covid-19 cases and Covid-19 deaths are negatively associated with stock returns. Further, we observe that the average stock returns during Lockdown 2 are positive and highly significant, while the returns during Lockdowns 3 and 4 are negative. Moreover, our results show that the chemical, technology, and food and beverage industries earn higher returns. In contrast, the banking and finance, automotive, services, and cement and construction industries yield lower returns for the overall period. Interestingly, all industry groupings in this study earn a positive return during the lockdown period. In particular, the chemical, technology, automotive, metals and mining, and food and beverage industries provide higher returns during the lockdown period. Finally, this study supports the claim that the Covid-19 pandemic has had a heterogeneous effect in the Indian stock markets.

Suggested Citation

  • Munusamy Dharani & M. Kabir Hassan & Makeen Huda & Mohammad Zoynul Abedin, 2023. "Covid-19 pandemic and stock returns in India," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(1), pages 251-266, March.
  • Handle: RePEc:spr:jecfin:v:47:y:2023:i:1:d:10.1007_s12197-022-09586-8
    DOI: 10.1007/s12197-022-09586-8
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    1. Yen-Chang Chen & Ying-Sing Liu, 2023. "Market Efficiency and Stock Investment Loss Aversion Guide During COVID-19 Pandemic Events: The Case for Applying Data Mining," SAGE Open, , vol. 13(4), pages 21582440231, December.

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