ANALYZING THE IMPACT OF GOVERNMENT’S RESPONSES TO THE COVID-19 PANDEMIC ON THE VIETNAMESE STOCK MARKET’S PERFORMANCE: A SECTOR-INDEX APPROACH
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Keywords

Covid-19 pandemic
Vietnam
government intervention
stock market performance

Abstract

This study aims to investigate the impact of the COVID-19 pandemic and how the government’s intervention influenced the performance of the Vietnamese stock market, including Ho Chi Minh and Hanoi stock exchanges, at the whole market level and especially at the sector level. Panel data at the sector level is obtained from 31 January 2020 to 23 July 2021 and divided into four different periods corresponding to the COVID-19 waves in Vietnam. GARCH (1,1) is used to predict stock market volatility and the random effect is employed in the panel regression model. The findings show that while stock market returns on the Ho Chi Minh stock exchange did not witness a significant change before and during the pandemic, empirical result indicates that stock market returns on the Hanoi stock exchange significantly changed. Stock market volatilities indicate a significant increase once the pandemic occurs in Vietnam on both stock exchanges. Specifically, the magnitude of the Covid-19 influence weakens over time. More importantly, we find that the intervention of the Vietnamese government significantly lessens the influence of the Covid-19 pandemic on the stock market, especially in the fourth period corresponding to the ongoing wave of COVID 19. The results of this study might offer a useful reference for governors, investors, and other scholars in future public policies and empirical research.

https://doi.org/10.26459/hueunijed.v131i5B.6523
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References

  1. Nguyen, K.G. (2020), Vietnam stocks become world’s best after extreme Turmoil in March. Retrieved from: https://www.bloomberg.com/news/articles/2020-04-14/from-extreme-turmoil-vietnam-stocks-become-world-s-best. (Accessed 5 July 2021).
  2. Black, G. (2020), Vietnam May Have the Most Effective Response to Covid-19, The Nation, Retrieved from: https://www.thenation.com/article/world/coronavirus-vietnam-quarantine-mobilization. (Accessed on 20 June 2021).
  3. Liu, H., Manzoor, A., Wang, C., Zhang, L., & Manzoor, Z. (2020), The COVID-19 outbreak and affected countries stock markets response, International Journal of Environmental Research and Public Health, 17(8), 2800.
  4. Al-Awadhi, A. M., Alsaifi, K., Al-Awadhi, A., & Alhammadi, S. (2020), Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns, Journal of behavioral and experimental finance, 27, 100326.
  5. Ramelli, S., & Wagner, A. F. (2020), Feverish stock price reactions to COVID-19, The Review of Corporate Finance Studies, 9(3), 622–655.
  6. He, Q., Liu, J., Wang, S., & Yu, J. (2020), The impact of COVID-19 on stock markets, Economic and Political Studies, 8(3), 275–288.
  7. Ashraf, B. N. (2020), Economic impact of government interventions during the COVID-19 pandemic: International evidence from financial markets, Journal of behavioral and experimental finance, 27, 100371.
  8. Bouri, E., Naeem, M. A., Nor, S. M., Mbarki, I., & Saeed, T. (2021), Government responses to COVID-19 and industry stock returns, Economic Research-Ekonomska Istraživanja, 1–24.
  9. Pagano, M., Wagner, C., & Zechner, J. (2020), Disaster resilience and asset prices, arXiv preprint arXiv:2005.08929.
  10. Goodell, J. W. (2020), COVID-19 and finance: Agendas for future research, Finance Research Letters, 35, 101512.
  11. Curto, J. D., & Serrasqueiro, P. (2021), The impact of COVID-19 on S&P500 sector indices and FATANG stocks volatility: An expanded APARCH model, Finance Research Letters, 102247.
  12. Baek, S., Mohanty, S. K., & Glambosky, M. (2020), COVID-19 and stock market volatility: An industry level analysis, Finance Research Letters, 37, 101748.
  13. Le, T. A. T., Vodden, K., Wu, J., & Atiwesh, G. (2021), Policy responses to the COVID-19 pandemic in Vietnam, International Journal of Environmental Research and Public Health, 18(2), 559.
  14. Anh, D. L. T., & Gan, C. (2020), The impact of the COVID-19 lockdown on stock market performance: Evidence from Vietnam, Journal of Economic Studies.
  15. Miller, J. I., & Ratti, R. A. (2009), Crude oil and stock markets: Stability, instability, and bubbles. Energy economics, 31(4), 559–568.
  16. Hahn, S. L. (2004), International transmission of stock market movements: A wavelet analysis. Applied Economics Letters, 11(3), 197–201.
  17. Kharchenko, I., & Tzvetkov, P. (2013), Estimation of volatilities and spillover effects between developed and emerging market economies.
  18. Nghi, L. D., & Kieu, N. M. (2021), Volatility spillover from the united states and Japanese stock markets to the Vietnamese stock market: A frequency domain approach, Panoeconomicus, (00), 3–3.
  19. Bollerslev, T. (1986), Generalized Autoregressive Conditional Heteroscedasticity, Journal of Econometrics, 31, 307–327.
  20. GC, S. B. (2008), Volatility analysis of Nepalese stock market. Journal of Nepalese Business Studies, 5(1), 76–84.
  21. Bollerslev, T., Chou, R. Y. & Kroner, K. F (1992), ARCH modeling in finance: A review of the theory and empirical evidence, Journal of Econometrics, 52, 5–59.
  22. Engle, R. F. (2001), GARCH 101: An Introduction to the Use of ARCH/GARCH Models in Applied Econometric (Vol. 30), NYU Working Paper No. FIN-01.
  23. Hansen, P. R., & Lunde, A. (2005), A forecast comparison of volatility models: Does anything beat a GARCH (1, 1)?, Journal of applied econometrics, 20(7), 873–889.
  24. Baltagi, B. H. (2021), Econometric analysis of panel data, Springer Nature.
  25. Hsiao, C. (2014), Analysis of panel data (No. 54), Cambridge university press.
  26. Bell, A., & Jones, K. (2015), Explaining fixed effects: Random effects modeling of time-series cross-sectional and panel data, Political Science Research and Methods, 3(1), 133–153.
  27. Schoenfeld, J. (2020), The invisible risk: Pandemics and the financial markets, Tuck School of Business Working Paper, (3567249).
  28. Choi, I. (2001), Unit root tests for panel data, Journal of international money and Finance, 20(2), 249–272.
  29. Kao, C. (1999), Spurious regression and residual-based tests for cointegration in panel data, Journal of econometrics, 90(1), 1–44.
  30. Park, H. M. (2011), Practical guides to panel data modeling: A step-by-step analysis using stata. Public Management and Policy Analysis Program, Graduate School of International Relations, International University of Japan, 12, 1–52.
  31. Coulibaly, S. (2021), COVID‐19 policy responses, inflation and spillover effects in the West African Economic and Monetary Union, African Development Review, 33, S139-S151.
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