Investors’ sentiment and equity markets during COVID-19 period: a quantile regression approach and wavelet analysis
Abstract
The purpose of this study is to investigate the relationship between investor sentiment and leading equity market indices from the U.S., Europe, Asia, and globally between January 2020 and June 2022. The methodological approaches utilized are quantile regression and wavelet analysis. The results of quantile regression suggested that Google Search Volume (GSV) and Twitter-based Market Uncertainty Index (TMU) negatively influenced the equity indices at lower quantiles. The wavelet coherence analysis highlighted that, at lower frequency bands, GSV moves in sync with the S&P 500, NASDAQ Composite, Dow Jones Industrials, and FTSE 100 but not with the DAX, CAC 40, TOPIX, Nikkei 225, or MSCI. Nonetheless, when the TMU was used to measure investors’ sentiment, the results revealed that the whole series was out of phase.
Keyword : investors’ sentiment, equity markets, COVID-19, quantile regression, wavelet coherence, wavelet cross-correlation
How to Cite
Gherghina, Ștefan C., Mehdian, S., & Stoica, O. (2023). Investors’ sentiment and equity markets during COVID-19 period: a quantile regression approach and wavelet analysis. Journal of Business Economics and Management, 24(3), 551–575. https://doi.org/10.3846/jbem.2023.19814
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Biktimirov, E. N., Sokolyk, T., & Ayanso, A. (2021). Sentiment and hype of business media topics and stock market returns during the COVID-19 pandemic. Journal of Behavioral and Experimental Finance, 31, 100542. https://doi.org/10.1016/j.jbef.2021.100542
Cevik, E., Altinkeski, B. K., Cevik, E. I., & Dibooglu, S. (2022). Investor sentiments and stock markets during the COVID-19 pandemic. Financial Innovation, 8, 69. https://doi.org/10.1186/s40854-022-00375-0
Chakraborty, M., & Subramaniam, S. (2020). Asymmetric relationship of investor sentiment with stock return and volatility: Evidence from India. Review of Behavioral Finance, 12(4), 435–454. https://doi.org/10.1108/RBF-07-2019-0094
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Chundakkadan, R., & Nedumparambil, E. (2022). In search of COVID-19 and stock market behavior. Global Finance Journal, 54, 100639. https://doi.org/10.1016/j.gfj.2021.100639
Costa, A., da Silva, C., & Matos, P. (2022). The Brazilian financial market reaction to COVID-19: A wavelet analysis. International Review of Economics & Finance, 82, 13–29. https://doi.org/10.1016/j.iref.2022.05.010
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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. https://doi.org/10.1093/rfs/hhu072
Dash, S. R., & Maitra, D. (2022). The COVID-19 pandemic uncertainty, investor sentiment, and global equity markets: Evidence from the time-frequency co-movements. The North American Journal of Economics and Finance, 62, 101712. https://doi.org/10.1016/j.najef.2022.101712
Debata, B., Ghate, K., & Renganathan, J. (2021). COVID-19 pandemic sentiment and stock market behavior: Evidence from an emerging market. Review of Behavioral Finance, 15(2). https://doi.org/10.1108/RBF-05-2021-0083
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Fang, L., & Peress, J. (2009). Media coverage and the cross-section of stock returns. The Journal of Finance, 64(5), 2023–2052. https://doi.org/10.1111/j.1540-6261.2009.01493.x
Gherghina, Ş. C., & Simionescu, L. N. (2022). Exploring the co-movements between stock market returns and COVID 19 pandemic: Evidence from wavelet coherence analysis. Applied Economics Letters, 29(15), 1405–1413. https://doi.org/10.1080/13504851.2021.1937034
Gong, X., Zhang, W., Wang, J., & Wang, C. (2022). Investor sentiment and stock volatility: New evidence. International Review of Financial Analysis, 80, 102028. https://doi.org/10.1016/j.irfa.2022.102028
Goupillaud, P., Grossmann, A., & Morlet, J. (1984). Cycle-octave and related transforms in seismic signal analysis. Geoexploration, 23(1), 85–102. https://doi.org/10.1016/0016-7142(84)90025-5
Guan, C., Liu, W., & Cheng, J. Y.-C. (2022). Using social media to predict the stock market crash and rebound amid the pandemic: The digital ‘haves’ and ‘have-mores’. Annals of Data Science, 9, 5–31. https://doi.org/10.1007/s40745-021-00353-w
Hasan, M. T. (2022). The sum of all SCARES COVID-19 sentiment and asset return. The Quarterly Review of Economics and Finance, 86, 332–346. https://doi.org/10.1016/j.qref.2022.08.005
Hirshleifer, D., Jiang, D., & DiGiovanni, Y. M. (2020). Mood beta and seasonalities in stock returns. Journal of Financial Economics, 137(1), 272–295. https://doi.org/10.1016/j.jfineco.2020.02.003
Ho, K. C., Gao, Y., Gu, Q., & Yang, D. (2022). Covid-19 vaccine approvals and stock market returns: The case of Chinese stocks. Economics Letters, 215, 110466. https://doi.org/10.1016/j.econlet.2022.110466
Hsu, Y.-L., & Tang, L. (2022). Effects of investor sentiment and country governance on unexpected conditional volatility during the COVID-19 pandemic: Evidence from global stock markets. International Review of Financial Analysis, 82, 102186. https://doi.org/10.1016/j.irfa.2022.102186
Huynh, T. L. D., Foglia, M., Nasir, M. A., & Angelini, E. (2021). Feverish sentiment and global equity markets during the COVID-19 pandemic. Journal of Economic Behavior & Organization, 188, 1088–1108. https://doi.org/10.1016/j.jebo.2021.06.016
Kamstra, M. J., Kramer, L. A., & Levi, M. D. (2003). Winter blues: A SAD stock market cycle. The American Economic Review, 93(1), 324–343. https://doi.org/10.1257/000282803321455322
Karamti, C., & Belhassine, O. (2022). COVID-19 pandemic waves and global financial markets: Evidence from wavelet coherence analysis. Finance Research Letters, 45, 102136. https://doi.org/10.1016/j.frl.2021.102136
Khoury, R. E., & Alshater, M. M. (2022). Spillovers between Twitter uncertainty indexes and sector indexes: Evidence from the US. Borsa Istanbul Review, 22(5), 961–974. https://doi.org/10.1016/j.bir.2022.07.002
Koenker, R., & Gilbert Bassett, J. (1978). Regression quantiles. Econometrica, 46(1), 33–50. https://doi.org/10.2307/1913643
Lazzini, A., Lazzini, S., Balluchi, F., & Mazza, M. (2022). Emotions, moods and hyperreality: Social media and the stock market during the first phase of COVID-19 pandemic. Accounting, Auditing & Accountability Journal, 35(1), 199–215. https://doi.org/10.1108/AAAJ-08-2020-4786
Liu, Z., Huynh, T. L. D., & Dai, P.-F. (2021). The impact of COVID-19 on the stock market crash risk in China. Research in International Business and Finance, 57, 101419. https://doi.org/10.1016/j.ribaf.2021.101419
Maia, V. M., Tommasetti, R., & Macedo, M. A. d. S. (2021). Australian market response to COVID-19 as moderated by social media. Pacific Accounting Review, 33(5), 625–635. https://doi.org/10.1108/PAR-09-2020-0138
Martins, A. M., & Cró, S. (2022). Airline stock markets reaction to the COVID-19 outbreak and vaccines: An event study. Journal of Air Transport Management, 105, 102281. https://doi.org/10.1016/j.jairtraman.2022.102281
Mezghani, T., Boujelbène, M., & Elbayar, M. (2021). Impact of COVID‐19 pandemic on risk transmission between googling investor’s sentiment, the Chinese stock and bond markets. China Finance Review International, 11(3), 322–348. https://doi.org/10.1108/CFRI-08-2020-0120
Nian, R., Xu, Y., Yuan, Q., Feng, C., & Lendasse, A. (2021). Quantifying time-frequency co-movement impact of COVID-19 on U.S. and China stock market toward investor sentiment index. Frontiers in Public Health, 9, 727047. https://doi.org/10.3389/fpubh.2021.727047
Niu, H., Lu, Y., & Wang, W. (2021). Does investor sentiment differently affect stocks in different sectors? Evidence from China. International Journal of Emerging Markets. https://doi.org/10.1108/IJOEM-11-2020-1298
Ortmann, R., Pelster, M., & Wengerek, S. T. (2020). COVID-19 and investor behavior. Finance Research Letters, 37, 101717. https://doi.org/10.1016/j.frl.2020.101717
Piñeiro-Chousa, J., López-Cabarcos, M. Á., Quiñoá-Piñeiro, L., & Pérez-Pico, A. M. (2022). US biopharmaceutical companies’ stock market reaction to the COVID-19 pandemic. Understanding the concept of the ‘paradoxical spiral’ from a sustainability perspective. Technological Forecasting and Social Change, 175, 121365. https://doi.org/10.1016/j.techfore.2021.121365
Ryu, D., Kim, H., & Yang, H. (2017). Investor sentiment, trading behavior and stock returns. Applied Economics Letters, 24, 826–830. https://doi.org/10.1080/13504851.2016.1231890
Salisu, A. A., & Akanni, L. O. (2020). Constructing a global fear index for the COVID-19 pandemic. Emerging Markets Finance and Trade, 56, 2310–2331. https://doi.org/10.1080/1540496X.2020.1785424
Sarirete, A. (2022). Sentiment analysis tracking of COVID-19 vaccine through tweets. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-022-03805-0
Sing, N. B., & Singh, R. G. (2023). Investor attention and reaction in COVID-19 crisis: Sentiment analysis in the Indian stock market. Managerial Finance, 49(3), 470–491. https://doi.org/10.1108/MF-06-2021-0258
Smales, L. A. (2021). Investor attention and global market returns during the COVID-19 crisis. International Review of Financial Analysis, 73, 101616. https://doi.org/10.1016/j.irfa.2020.101616
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