The Long-term Impact of Normalized Pandemic on Nasdaq and SP 500: An Empirical Evidence from Time Series
DOI:
https://doi.org/10.54097/hbem.v5i.5044Keywords:
Covid-19 pandemic, Stock returns, Stock return volatility, Time series.Abstract
After Covid-19 pandemic, the global economy stagnated briefly and was deeply affected in the long-term. In the early days of the COVID-19 epidemic, the stock market was hit hard and stock prices fell sharply. The COVID-19 pandemic has brought turmoil to the global economy, and the implications are lasting and profound. Previous literature has highlighted the short-term impact of COVID-19 on stock and commodity markets. This study models the long-term dynamic response of the COVID 19 epidemic using time series. The VAR model was applied in the study to evaluate the link between variables, and the ARMA-GARCH model was used to determine and analyze stock volatility throughout the pandemic. Investors can easily recover from pessimism and reinvest in the market because the coronavirus pandemic has a huge short-term impact. However, long-term fluctuations in the US stock market are not significantly effected by the COVID-19 epidemic. The study forecasts the possible future of the U.S. stock market and provides managerial and investment recommendations to its stakeholders.
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References
Greenwood R, Landier A, Thesmar D. Vulnerable banks [J]. Journal of Financial Economics, 2015, 115(3): 471-485.
Ramelli S, Wagner A F. Feverish stock price reactions to COVID-19 [J]. The Review of Corporate Finance Studies, 2020, 9(3): 622-655.
Coronavirus Statistics Worldometer [EB/OL]. [2022-09-30]. https://www.worldometers.info/coronavirus/.
Zhang D, Hu M, Ji Q. Financial markets under the global pandemic of COVID-19[J]. Finance research letters, 2020, 36: 101528.
Gormsen N J, Koijen R S J. Coronavirus: Impact on stock prices and growth expectations[J]. The Review of Asset Pricing Studies, 2020, 10(4): 574-597.
Nelson B W, Pettitt A, Flannery J E, et al. Rapid assessment of psychological and epidemiological correlates of COVID-19 concern, financial strain, and health-related behavior change in a large online sample [J]. PLoS One, 2020, 15(11): e0241990.
Khan K, Zhao H, Zhang H, et al. The impact of COVID-19 pandemic on stock markets: An empirical analysis of world major stock indices [J]. The Journal of Asian Finance, Economics and Business, 2020, 7(7): 463-474.
Wren‐Lewis S. The economic effects of a pandemic Economics in the time of COVID‐19 [J]. 2020.
Capelle-Blancard G, Desroziers A. The stock market is not the economy? Insights from the COVID-19 crisis [J]. Insights from the COVID-19 Crisis (June 16, 2020). CEPR Covid Economics, 2020.
He Q, Liu J, Wang S, et al. The impact of COVID-19 on stock markets [J]. Economic and Political Studies, 2020, 8(3): 275-288.
Ashraf B N. Stock markets’ reaction to COVID-19: Cases or fatalities? [J]. Research in International Business and Finance, 2020, 54: 101249.
Goodell J W, Goutte S. Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis [J]. Finance Research Letters, 2021, 38: 101625.
Sharif A, Aloui C, Yarovaya L. COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach [J]. International Review of Financial Analysis, 2020, 70: 101496.
Azimli A. The impact of COVID-19 on the degree of dependence and structure of risk-return relationship: A quantile regression approach [J]. Finance Research Letters, 2020, 36: 101648.
Drobetz W, Schröder H, Tegtmeier L. The role of catastrophe bonds in an international multi-asset portfolio: Diversifier, hedge, or safe haven? [J]. Finance Research Letters, 2020, 33: 101198.
Mann H B, Wald A. On the statistical treatment of linear stochastic difference equations [J]. Econometrica, Journal of the Econometric Society, 1943: 173-220.
Sims C A. The role of approximate prior restrictions in distributed lag estimation [J]. Journal of the American Statistical Association, 1972, 67(337): 169-175.
Sims C A. Macroeconomics and reality [J]. Econometrica: journal of the Econometric Society, 1980: 1-48.
Orcutt G H, Irwin J O. A study of the autoregressive nature of the time series used for Tinbergen's model of the economic system of the United States, 1919-1932 [J]. Journal of the Royal Statistical Society. Series B (Methodological), 1948, 10(1): 1-53.
Freeman J R, Williams J T, Lin T. Vector autoregression and the study of politics [J]. American Journal of Political Science, 1989: 842-877.
Engle R. GARCH 101: The use of ARCH/GARCH models in applied econometrics [J]. Journal of economic perspectives, 2001, 15(4): 157-168.
Hill R C, Griffiths W E, Lim G C. Principles of econometrics[M]. John Wiley & Sons, 2018.
Ghani I M M, Rahim H A. Modeling and forecasting of volatility using arma-garch: Case study on malaysia natural rubber prices[C]//IOP Conference Series: Materials Science and Engineering. IOP Publishing, 2019, 548(1): 012023.
Tiwari A K, Abakah E J A, Karikari N K, et al. The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets [J]. The North American Journal of Economics and Finance, 2022, 62: 101735.
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