Potential Causes Related to Stock Market Volatility During COVID-19: Insights into the Performances in the Us

Xin Lian; Fernando Echevarria

doi:10.18282/ff.v10i4.2353

Xin Lian Cambridge Centre for the Integration of Science, Technology and Culture, University of Cambridge
Fernando Echevarria Cambridge Centre for the Integration of Science, Technology and Culture, University of Cambridge

DOI: https://doi.org/10.18282/ff.v10i4.2353

Keywords: COVID-19, Volatility, Regression Analysis, Time Series Analysis, Variance Inflation Factor, Stepwise Regression, Google Trend, VIX, People’s Focus on COVID-19, Autocorrelation

Abstract

The research aims to figure out the significant factors causing the volatility moves in the period from Feb 10 to Dec 28, 2020, which covers the outbreak and duration of COVID-19 in 2020, among the candidates: number of reports (cases, deaths, tests, and infection rate), number of medical resources needed (all beds needed, ICU beds needed, and invasive ventilators needed), and people’s anticipation toward reality (stock market, the pandemic, state of the economic and personal finance). After performing OLS regressions with stepwise regressions forward further, whose independent variables are chosen based on the values of VIF, we conclude that people’s focus on coronavirus is the most significant factor that induces the volatility, and the VIX values evolve dynamically. Nevertheless, the conclusions are somehow not robust as expected: in the second half of the period, not only none of the candidates are shown to have any influence on the volatility, but also the VIX series is proved to be not autocorrelated. By the results of the study, it is important not only to control the further spread of the pandemic but also to find approaches to stabilize people’s emotions towards the aspects of life which are affected by the pandemic. Apart from the meaningful insights from the research, the research paves the way for further studies in the future.

References

Wagner, A. F. (2020). What the stock market tells us about the post-COVID-19 world. Nature Human Behaviour, 4(5), 440-440. doi:10.1038/s41562-020-0869-y.

Devpura, N., & Narayan, P. (2020). Hourly Oil Price Volatility: The Role of COVID-19. Energy RESEARCH LETTERS. doi: 10.46557/001c.13683.

Baek, S., Mohanty, S. K., & Glambosky, M. (2020). COVID-19 and stock market volatility: An industry level analysis. Finance Research Letters, 101748.

Albulescu, C. (2020). Coronavirus and Financial Volatility: 40 Days of Fasting and Fear. SSRN Electronic Journal. doi: 10.2139/ssrn.3550630.

Baker, S., Bloom, N., Davis, S., Kost, K., Sammon, M., & Viratyosin, T. (2020). The Unprecedented Stock Market Reaction to COVID-19. The Review of Asset Pricing Studies. doi: 10.1093/rapstu/raaa008.

Haroon, O., & Rizvi, S. A. R. (2020). COVID-19: Media coverage and financial markets behavior—A sectoral inquiry. Journal of Behavioral and Experimental Finance, 100343.

Albulescu, C. (2020). COVID-19 and the United States financial markets’ volatility. Finance Research Letters, 101699. doi: 10.1016/j.frl.2020.101699.

Stephanos, P., Athanasios P., F., Dimitris, K., & Dimitris, D. (2020). Direct and Indirect Effects of COVID-19 Pandemic on Implied Stock Market Volatility: Evidence from Panel Data Analysis. Munich Personal Repec Archive, (100020).

Da, Z., Engelberg, J., & Gao, P. (2015). The sum of all FEARS investor sentiment and asset prices. The Review of Financial Studies, 28(1), 1-32.

Sharma, M., & Sharma, S. (2020). The Rising Number of COVID-19 Cases Reflecting Growing Search Trend and Concern of People: A Google Trend Analysis of Eight Major Countries. Journal of Medical Systems, 44(7). doi: 10.1007/s10916-020-01588-5.

Xu, S. Y., & Berkely, C. U. (2014). Stock price forecasting using information from Yahoo finance and Google trend. UC Berkeley.