Contagious COVID 19: Leading to Hysteria in Indian Stock Marketsand Sectoral Indices Performance

Divya Jain

doi:10.65301/dias.2021.18.1.2

Articles 35th Edition of DTR Apr 2021 – Sep 2021

DOI 10.65301/dias.2021.18.1.2

Contagious COVID 19: Leading to Hysteria in Indian Stock Marketsand Sectoral Indices Performance

Authors

DI

Divya Jain

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Published 2021-09-30

Abstract

The eruption of the novel corona virus in India has led to the outflow of panic due to high media coverage. This unparalleled broadcast of news has led to swift flow of information to investors and reactions can be assessed with increased volatility in financial markets. EGARCH (1,1) Model is applied to determine the relationship between the market returns of different industries along with the panic generated due to media coverage about the corona virus outbreak. Imposition of mobility control in terms of Lockdown has exerted the significant impact on stock market and sectoral indices returns. And depending on the nature of the business associated, different sectors have performed in a different way to this corona virus outburst. Even if returns are not affected directly then conditional volatility pervasiveness can easily be detected. So, the news burdened with panic and negative sentiment has definitely contributed to a prodigious level of volatility in the sectors professed to be most affected by the corona virus outbreak in India

Keywords

Corona virus COVID-19 Sectoral Indices Performance EGARCH Model Conditional Volatility Panic Index Nifty 50 Media Coverage

References

i. A. M. Al-Awadhi, K. Alsaifi, A. Al-Awadhi, and S. Alhammadi (2020). “Death and Contagious Infectious Diseases: Impact of the COVID-19 Virus on Stock Market Returns.” Journal of Behavioral and Experimental Finance, 27, 100326. https://doi.org/10.1016/j.jbef.2020.100326
ii. A. Angabini and S. Wasiuzzaman (2011). “GARCH Models and the Financial Crisis: A Study of the Malaysian Market.” The International Journal of Applied Economics and Finance, 5(3), 226–236.
iii. A. S. Baig, H. A. Butt, O. Haroon, S. Aun, and R. Rizvi (2020). “Deaths, Panic, Lockdowns and US Equity Markets: The Case of COVID-19 Pandemic.” SSRN Electronic Journal, April, 1–14. Retrieved from https://dx.doi.org/10.2139/ssrn.3584947
iv. S. R. Baker, Nicholas Bloom, Steven J. Davis, K. Kost, M. Sammon, and T. Viratyosin (2020). “The Unprecedented Stock Market Reaction to COVID-19.” National Bureau of Economic Research Working Paper, 1(DP 14543), 33–42. Available at Working Paper PDF
v. Nicholas Barberis, Andrei Shleifer, and Robert Vishny (1998). “A Model of Investor Sentiment.” Journal of Financial Economics, 49(3), 307–343.
vi. M. Casas Monsegny and E. Cepeda Cuervo (2008). “Modelos ARCH, GARCH y EGARCH: Aplicaciones a Series Financieras.” Cuadernos de Economía, 27(48), 287–319.
vii. S. Corbet, C. J. Larkin, and B. M. Lucey (2020). “The Contagion Effects of the COVID-19 Pandemic: Evidence from Gold and Cryptocurrencies.” Financial Research Letters. Retrieved from https://doi.org/10.2139/ssrn.3564443
L. H. Ederington and J. H. Lee (1996). “The Creation and Resolution of Market Uncertainty: The Impact of Information Releases on Implied Volatility.” Journal of Financial and Quantitative Analysis, 31(4), 513–539.
H. Ezzat (2012). “The Application of GARCH and EGARCH in Modeling the Volatility of Daily Stock Returns during Massive Shocks: The Empirical Case of Egypt.” International Research Journal of Finance and Economics, 96, 143–154.
viii. A. Groß-Klußmann and N. Hautsch (2011). “When Machines Read the News: Using Automated Text Analytics to Quantify High Frequency News-Implied Market Reactions.” Journal of Empirical Finance, 18(2), 321–340.
ix. V. K. Liew and C. H. Puah (2020). “Chinese Stock Market Sector Indices Performance in the Time of Novel Coronavirus Pandemic.” May, 1–23. Retrieved from https://doi.org/10.20944/preprints202005.0279.v1
x. Daniel B. Nelson (1991). “Conditional Heteroscedasticity in Asset Returns: A New Approach.” Econometrica, 59, 347–370.
xi. Enrico Onali (2020). “COVID-19 and Stock Market Volatility.” SSRN Electronic Journal, February, 1–24. Retrieved from https://doi.org/10.2139/ssrn.3571453
xii. S. A. R. Rizvi and S. Arshad (2018). “Understanding Time-Varying Systematic Risks in Islamic and Conventional Sectoral Indices.” Economic Modelling, 70, 561–570. https://doi.org/10.1016/j.econmod.2017.10.011
xiii. L. Rogone, S. Hyde, and S. S. Zhang (2020). “News Sentiment in the Cryptocurrency Market: An Empirical Comparison with Forex.” International Review of Financial Analysis, 69, 101462.
xiv. Paul C. Tetlock (2007). “Giving Content to Investor Sentiment: The Role of Media in the Stock Market.” The Journal of Finance, 62(3), 1139–1168.
xv. Dacio Villarreal-Samaniego (2020). “COVID-19, Oil Prices, and Exchange Rates: A Five-Currency Examination.” SSRN Electronic Journal, May. Retrieved from SSRN Paper
xvi. Joakim Westerlund and Paresh Kumar Narayan (2015). “Testing for Predictability in Conditionally Heteroskedastic Stock Returns.” Journal of Financial Econometrics, 13(2), 342–375. https://doi.org/10.1093/jjfinec/nbu001
xvii. D. Zhang, M. Hu, and Q. Ji (2020). “Financial Markets under the Global Pandemic of COVID-19.” Finance Research Letters, April, 101528. https://doi.org/10.1016/j.frl.2020.101528
xviii. Statista Coronavirus Data
Source: Johns Hopkins University; World Health Organization; Worldometer; Ministry of Health and Family Welfare.
xix. RavenPack Coronavirus India Data
Source: RavenPack.

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Divya Jain . (2021). Contagious COVID 19: Leading to Hysteria in Indian Stock Marketsand Sectoral Indices Performance. DIAS Technology Review, 18(1).

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[1] i. A. M. Al-Awadhi, K. Alsaifi, A. Al-Awadhi, and S. Alhammadi (2020). “Death and Contagious Infectious Diseases: Impact of the COVID-19 Virus on Stock Market Returns.” Journal of Behavioral and Experimental Finance, 27, 100326. https://doi.org/10.1016/j.jbef.2020.100326

[2] ii. A. Angabini and S. Wasiuzzaman (2011). “GARCH Models and the Financial Crisis: A Study of the Malaysian Market.” The International Journal of Applied Economics and Finance, 5(3), 226–236.

[3] iii. A. S. Baig, H. A. Butt, O. Haroon, S. Aun, and R. Rizvi (2020). “Deaths, Panic, Lockdowns and US Equity Markets: The Case of COVID-19 Pandemic.” SSRN Electronic Journal, April, 1–14. Retrieved from https://dx.doi.org/10.2139/ssrn.3584947

[4] iv. S. R. Baker, Nicholas Bloom, Steven J. Davis, K. Kost, M. Sammon, and T. Viratyosin (2020). “The Unprecedented Stock Market Reaction to COVID-19.” National Bureau of Economic Research Working Paper, 1(DP 14543), 33–42. Available at Working Paper PDF

[5] v. Nicholas Barberis, Andrei Shleifer, and Robert Vishny (1998). “A Model of Investor Sentiment.” Journal of Financial Economics, 49(3), 307–343.

[6] vi. M. Casas Monsegny and E. Cepeda Cuervo (2008). “Modelos ARCH, GARCH y EGARCH: Aplicaciones a Series Financieras.” Cuadernos de Economía, 27(48), 287–319.

[7] vii. S. Corbet, C. J. Larkin, and B. M. Lucey (2020). “The Contagion Effects of the COVID-19 Pandemic: Evidence from Gold and Cryptocurrencies.” Financial Research Letters. Retrieved from https://doi.org/10.2139/ssrn.3564443

[8] L. H. Ederington and J. H. Lee (1996). “The Creation and Resolution of Market Uncertainty: The Impact of Information Releases on Implied Volatility.” Journal of Financial and Quantitative Analysis, 31(4), 513–539.

[9] H. Ezzat (2012). “The Application of GARCH and EGARCH in Modeling the Volatility of Daily Stock Returns during Massive Shocks: The Empirical Case of Egypt.” International Research Journal of Finance and Economics, 96, 143–154.

[10] viii. A. Groß-Klußmann and N. Hautsch (2011). “When Machines Read the News: Using Automated Text Analytics to Quantify High Frequency News-Implied Market Reactions.” Journal of Empirical Finance, 18(2), 321–340.

[11] ix. V. K. Liew and C. H. Puah (2020). “Chinese Stock Market Sector Indices Performance in the Time of Novel Coronavirus Pandemic.” May, 1–23. Retrieved from https://doi.org/10.20944/preprints202005.0279.v1

[12] x. Daniel B. Nelson (1991). “Conditional Heteroscedasticity in Asset Returns: A New Approach.” Econometrica, 59, 347–370.

[13] xi. Enrico Onali (2020). “COVID-19 and Stock Market Volatility.” SSRN Electronic Journal, February, 1–24. Retrieved from https://doi.org/10.2139/ssrn.3571453

[14] xii. S. A. R. Rizvi and S. Arshad (2018). “Understanding Time-Varying Systematic Risks in Islamic and Conventional Sectoral Indices.” Economic Modelling, 70, 561–570. https://doi.org/10.1016/j.econmod.2017.10.011

[15] xiii. L. Rogone, S. Hyde, and S. S. Zhang (2020). “News Sentiment in the Cryptocurrency Market: An Empirical Comparison with Forex.” International Review of Financial Analysis, 69, 101462.

[16] xiv. Paul C. Tetlock (2007). “Giving Content to Investor Sentiment: The Role of Media in the Stock Market.” The Journal of Finance, 62(3), 1139–1168.

[17] xv. Dacio Villarreal-Samaniego (2020). “COVID-19, Oil Prices, and Exchange Rates: A Five-Currency Examination.” SSRN Electronic Journal, May. Retrieved from SSRN Paper

[18] xvi. Joakim Westerlund and Paresh Kumar Narayan (2015). “Testing for Predictability in Conditionally Heteroskedastic Stock Returns.” Journal of Financial Econometrics, 13(2), 342–375. https://doi.org/10.1093/jjfinec/nbu001

[19] xvii. D. Zhang, M. Hu, and Q. Ji (2020). “Financial Markets under the Global Pandemic of COVID-19.” Finance Research Letters, April, 101528. https://doi.org/10.1016/j.frl.2020.101528

[20] xviii. Statista Coronavirus Data

[21] Source: Johns Hopkins University; World Health Organization; Worldometer; Ministry of Health and Family Welfare.

[22] xix. RavenPack Coronavirus India Data

[23] Source: RavenPack.