What Influenced Stock Investment Decision During the COVID-19 Pandemic? Environment, Expectations, and Biases: A Systematic Review
Keywords:
equity market, decision-making, investment behavior, coronavirus, narrative synthesisAbstract
Diverse decisions and behavior of investors in stock markets under unforeseeable situations of the COVID-19 pandemic were influenced by environmental and psychological factors. This study aimed to identify the factors affecting individual investor decisions through a systematic review with a narrative synthesis. Scopus and ScienceDirect were academic databases used as sources of searched studies. The five included studies were correlational studies conducted through archival and survey data, and had a variety of study objectives. The risk of bias in the included studies assessment was presented through traffic light and summary plots. The analysis revealed that the COVID-19 cases, time spent on stock markets, expectations, and investor biases were the factors collaborating in influencing stock investment decisions in the ambiguous situations. The findings were interpretable that the four key factors had a role in perceiving, evaluating, and judging choices of stock investment. Implications of the findings will be shared with appropriate investment authorities in Thailand so as to reduce a degree of stock market volatility through issuing guidelines on investing in stocks under uncertainties and to researchers having the purpose of conducting the future study regarding investor decisions under the post-COVID-19 circumstances.
References
Abdeldayem, M. M., & Al Dulaimi, S. H. (2020). Investors’ herd behavior related to the pandemic-risk reflected on the GCC stock markets. Zbornik radova Ekonomskog fakulteta u Rijeci, 38(2), 563-584.
Adekoya, O. B., Oliyide, J. A., & Tiwari, A. K. (2022). Risk transmissions between sectoral Islamic and conventional stock markets during COVID-19 pandemic: What matters more between actual COVID-19 occurrence and speculative and sentiment factors?. Borsa Istanbul Review, 22(2), 363-376.
Aggarwal, S., Nawn, S., & Dugar, A. (2021). What caused global stock market meltdown during the COVID pandemic–Lockdown stringency or investor panic?. Finance Research Letters, 38.
Almehmadi, A. (2021). COVID-19 pandemic data predict the stock market. Computer Systems Science and Engineering, 36(3), 451-460.
Aloui, C., Asadov, A., Al-kayed, L., Hkiri, B., & Danila, N. (2022). Impact of the COVID-19 outbreak and its related announcements on the Chinese conventional and Islamic stocks’ connectedness. The North American Journal of Economics and Finance, 59. https://doi.org/10.1016/j.najef.2021.101585
American Psychological Association. (2022, December 9). APA Dictionary of Psychology. Retrieved from https://dictionary.apa.org/bias
Archuleta, K. L., Glenn, C., Lawson, D. R., Clady, J. P., & Solomon, S. (2021). I know I should, but do I do it? Connecting covert and overt financial behaviors. Journal of Financial Counseling and Planning, 32(3), 550–563.
Ashraf, B. N. (2020). Stock markets' reaction to COVID-19: Cases or fatalities?. Research in International Business and Finance, 54.
Aslam, F., Awan, T. M., Syed, J. H., Kashif, A., & Parveen, M. (2020). Sentiments and emotions evoked by news headlines of coronavirus disease (COVID-19) outbreak. Borsa Istanbul Review, 20(1), 49-61.
Baig, A. S., Butt, H. A., Haroon, O., & Rizvi, S. A. R. (2021). Deaths, panic, lockdowns and US equity markets: The case of COVID-19 pandemic. Finance Research Letters, 38.
Baker, H. K., & Ricciardi, V. (2014). Investor behavior: The psychology of financial planning and investing. New Jersey: John Wiley and Sons Incorporated.
Baylor College of Medicine. (2023, May 18). Emerging Infectious Diseases. Retrieved from department of molecular virology and microbiology https://www.bcm.edu/departments/molecular-virology-and-microbiology/emerging-infections-and-biodefense/emerging-infectious-diseases
Best, J. B. (1999). Cognitive psychology (5th ed.). Pennsylvania: Brooks/Cole Wadsworth.
Bhandari, P. (2022). Levels of measurement: Nominal, ordinal, interval and ratio. Retrieved from Scribbr https://www.scribbr.com/statistics/levels-of-measurement
Bhatia, S., & Mullett, T. L. (2016). The dynamics of deferred decision. Cognitive Psychology, 86, 112-151. https://doi.org/10.1016/j.cogpsych.2016.02.002
Bickley, S. J., Brumpton, M., Chan, H. F., Colthurst, R., & Torgler, B. (2021). The stabilizing effect of social distancing: Cross-country differences in financial market response to COVID-19 pandemic policies. Research in International Business and Finance, 58.
Bradley, R. (2016). Decision theory with a human face. Retrieved from London School of Economics and Political Science Retrieved from https://personal.lse.ac.uk/
bradleyr/pdf/Decision%20theory%20with%20a%20human%20face.pdf
Burnham, J. F. (2006). Scopus database: A review. Biomedical Digital Libraries, 3(1).
Burnes, B., & Cooke, B. (2013). Kurt Lewin's field theory. International Journal of Management Reviews, 15, 408-425.
Chatterjee, U., & French, J. J. (2022). A note on tweeting and equity markets before and during the Covid-19 pandemic. Finance Research Letters, 46.
Chiah, M., Tain, X., & Zhong, A. (2022). Lockdown and retail trading in the equity market. Journal of Behavioral and Experimental Finance, 33.
Chundakkadan, R., & Nedumparambil, E. (2022). In search of COVID-19 and stock market behavior. Global Finance Journal, 54.
Congressional Research Service (2020, April 20). COVID-19 and stock market stress. Retrieved from https://crsreports.congress.gov/product/pdf/IN/IN11309
Costola, M., Iacopini, M., & Santagiustina, C. (2021). Google search volumes and the financial markets during the COVID-19 outbreak. Finance Research Letters, 42.
Del Lo, G., Bassene, T., & Sene, B. (2022). COVID-19 And the African financial markets: Less infection, less economic impact?. Finance Research Letters, 45.
Deng, T., Xu, T., & Lee, Y. J. (2022). Policy responses to COVID-19 and stock market reactions-An international evidence. Journal of Economics and Business, 119.
Denyer, D., & Tranfield, D. (2009). Producing a systematic review. In D. Buchanan & A. Bryman (Eds.), The Sage handbook of organizational research methods (pp. 671–689). California: Sage Publications Ltd.
Dertat, A. (2017). Applied deep learning - part 1: Artificial neural networks. Retrieved from Towards Data Science https://towardsdatascience.com/applied-deep-learning-part-1-artificial-neural-networks-d7834f67a4f6
Dey, A. K., Hoque, G. M. T., Das, K. P., & Panovska, I. (2022). Impacts of COVID-19 local spread and Google search trend on the US stock market. Physica A, 589.
Fernandez-Perez, A., Gilbert, A., Indriawan, I., & Nguyen, N. H. (2021). COVID-19 pandemic and stock market response: A culture effect. Journal of Behavioral and Experimental Finance, 29.
Ftiti, Z., Ameur, H. B., & Louhichi W. (2021). Does non-fundamental news related to COVID-19 matter for stock returns? Evidence from Shanghai stock market. Economic Modelling, 99.
Gallagher, J. (2020, November 9). Covid vaccine: First milestone vaccine offers 90% protection. Retrieved from BBC News https://www.bbc.com/news/health-54873105
Ghosh, I., & Sanyal, M. K. (2021). Introspecting predictability of market fear in Indian context during COVID-19 pandemic: An integrated approach of applied predictive modelling and explainable AI. International Journal of Information Management Data Insights, 1(2).
Gurbaxani, A., & Gupte, R. (2021). A study on the impact of COVID- 19 on investor behaviour of individuals in a small town in the state of Madhya Pradesh, India. Australasian Accounting Business and Finance Journal, 15(1), 70-92.
Harnegie M. P. (2013). SciVerse science direct. Journal of the Medical Library Association: Journal of the Medical Library Association, 101(2).
Hayes, A. (2021, September 27). Understanding common types of bias in investing. Retrieved from Investopedia https://www.investopedia.com/terms/b/bias.asp
Higgins, J, P, T., Altman, D, G., & Sterne, J, A, C. (2011). Assessing risk of bias in included studies. In J.P.T. Higgins, & S. Green (Eds.), Cochrane handbook for systematic reviews of interventions. Retrieved from The Cochrane Collaboration https://handbook-5-1.cochrane.org/chapter_8/8_assessing_risk_of_bias_in_
included_studies.htm
Higgins, J, P, T., Altman,D, G., Gøtzsche, P, C., Jüni, P., Moher, D., Oxman, A, D., Savović, J., Schulz, K, F., Weeks, L., & Sterne, J, A, C. (2011). The Cochrane Collaboration tool for assessing risk of bias in randomised trials. BMJ.
Higgins, J, P, T., & Green, S. (2011). Cochrane handbook for systematic reviews of interventions, version 5.1.0. Retrieved from The Cochrane Collaboration https://handbook-5-1.cochrane.org/
Higgins, J, P, T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M, J., & Welch, V, A. (2022). Cochrane handbook for systematic reviews of interventions, version 6.3. Retrieved from The Cochrane Collaboration https://training.cochrane.org/
handbook/archive/v6.3
Himanshu, Ritika, Mushir, N., & Suryavanshi, R. (2021). Impact of COVID-19 on portfolio allocation decisions of individual investors. Journal of Public Affairs, 21(4).
Hoang, H. V., Nguyen, C., & Nguyen, D. K. (2022). Corporate immunity, national culture and stock returns: Startups amid the COVID-19 pandemic. International Review of Financial Analysis, 79.
Holmes, W. R., Trueblood, J. S., & Heathcote, A. (2016). A new framework for modeling decisions about changing information: The piecewise linear ballistic accumulator model. Cognitive Psychology, 85, 1-29.
Hommes, C. (2013). Behavioral rationality and heterogeneous expectations in complex economic systems. Cambridge: Cambridge University Press.
Huber, C., Huber, J., & Kirchler, M. (2021). Market shocks and professionals' investment behavior - Evidence from the COVID-19 crash. Journal of Banking and Finance, 133.
Hunjra, A. I., Kijkasiwat, P., Arunachalam, M., & Hammami, H. (2021). Covid-19 health policy intervention and volatility of Asian capital markets. Technological Forecasting & Social Change, 169.
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 and Organization, 188, 1088-1108.
Ichev, R. (2021). Stock price reaction to appointment of a chief health officer during COVID-19. Journal of Behavioral and Experimental Finance, 31.
Kartasova, J., Gaspareniene, L., & Remeikiene, R. (2014). Influence of “snake-bite” effect on investment return rate: Lithuanian example. Mediterranean Journal of Social Sciences, 5(27), 1769-1773.
Kathpal, S., Akhtar, A., Zaheer, A., & Khan, M. N. (2021). Covid-19 and heuristic biases: Evidence from India. Journal of Financial Services Marketing, 26(4), 305-316
Kelly, T. (2022). Bias: A philosophical study (1st ed.). Oxford: Oxford Academic.
Kizys, R., Tzouvanas, P., & Donadelli, M. (2021). From COVID-19 herd immunity to investor herding in international stock markets: The role of government and regulatory restrictions. International Review of Financial Analysis, 74.
Korstanje, J. (2021). Structural equation modeling. Retrieved from Towards Data Science https://towardsdatascience.com/structural-equation-modeling-dca298798f4d
Lachmann, P. (2019). The influence of infection on society. In S. Giordano, J. Harris, & L. Piccirillo (Eds.), The freedom of scientific research: Bridging the gap between science and society (pp. 19-31). Manchester, UK: Manchester University Press.
Li, J., An, Y., Wang, L., & Zhang, Y. (2022). Combating the COVID-19 pandemic: The role of disaster experience. Research in International Business and Finance, 60.
Lin, Y., Wang, Y., & Fu, X. M. (2022). Margin purchases, short sales and stock return volatility in China: Evidence from the COVID-19 outbreak. Finance Research Letters, 46.
Malekian, A., & Chitsaz, N. (2021). Chapter 4 - Concepts, procedures, and applications of artificial neural network models in streamflow forecasting. Advances in Streamflow Forecasting, 2021, 115-147.
McGuinness, L. A., & Higgins, J. P. T. (2020). Risk of bias visualization (robvis): An R package and Shiny web app for visualizing risk of bias assessments. Research Synthesis Methods, 12 (1), 1-7.
Nepp, A., Okhrin, O., Egorova, J., Dzhuraeva, Z., & Zykov, A. (2022). What threatens stock markets more - The coronavirus or the hype around it?. International Review of Economics & Finance, 78, 519-539.
Nudelman, G., & Otto, K. (2020). The development of a new generic risk of bias measure for systematic reviews of surveys. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 16(4), 278–298.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hrobjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372(n71).
Petticrew, M., & Roberts, H. (2006). Systematic reviews in the social sciences: A practical guide. Massachusetts: Blackwell Publishing.
Pompain, M. M. (2021). Behavioral finance and your portfolio: A navigation guide for building wealth. New Jersey: John Wiley and Sons Incorporated.
Popay, J., Roberts, H.M., Sowden, A.J., Petticrew, M., Arai, L., Rodgers, M., & Britten, N. (2006). Guidance on the conduct of narrative synthesis in systematic reviews: A product from the ESRC methods programme. Lancaster: Lancaster University.
Pratkanis, A., & Turner, M. (2021). Kurt Lewin's field theory. Salem Press Encyclopedia of Health. Retrieve from Research Starters https://connect.ebsco.com
Price, P., Jhangiani, R., & Chiang, I. (2015). Nonexperimental research. Research Methods of Psychology (2nd Canadian ed). Retrieved from https://opentextbc.ca/
researchmethods/chapter/overview-of-nonexperimental-research/
Priem, R. (2021). An exploratory study on the impact of the COVID-19 confinement on the financial behavior of individual investors. Economics, Management, and Financial Markets, 16(3), 9–40.
Rai, A., Mahata, A., Nurujjaman, M., Majhi, S., & Debnath, K. (2022). A sentiment-based modeling and analysis of stock price during the COVID-19: U- and Swoosh-shaped recovery. Physica A, 592
Ramanathan, R. (2004). Multicriteria analysis of energy. Encyclopedia of Energy, 2004, 77-88.
Ratcliff, R., & McKoon, G. (2020). Decision making in numeracy tasks with spatially continuous scales. Cognitive Psychology, 116.
Rosca, V. I. (2020). Implications of Lewin’s field theory on social change. Proceedings of the International Conference on Business Excellence, 14(1), 617-625.
Salisu, A. A., & Vo, X. V. (2020). Predicting stock returns in the presence of COVID-19 pandemic: The role of health news. International Review of Financial Analysis, 71.
Salvatore, D., & Reagle, D. (2011). Statistics and econometrics (2nd ed.). United State of America: McGraw-Hill.
Seven, Ü., & Yılmaz, F. (2021). World equity markets and COVID-19: Immediate response and recovery prospects. Research in International Business and Finance, 56.
Sha, Y., Zhang, Y., & Lu, X. (2022). Household investment diversification amid Covid-19 pandemic: Evidence from Chinese investors. Finance Research Letters, 47(Part A).
Shah, S. F., Alshurideh, M., Kurdi, B. A., & Salloum S. A. (2021). The impact of the behavioral factors on investment decision-making: A systemic review on financial institutions. Proceedings of International Conference on Advanced Intelligent Systems and Informatics 2020,1261,100-112.
Shankar, B. (2022, May 20). Lessons in behavioral bias: The COVID-19 equity markets. Retrieved from Enterprising Investor https://blogs.cfainstitute.org/investor/2022/05/20/lessons-in-cognitive-bias-the-covid-19-equity-markets/
Sharma, G. D., Erkut, B., Jain, M., Kaya, T., Mahendru, M., Srivastava, M., Uppal, R. S., & Singh, S. (2020). Sailing through the COVID-19 crisis by using AI for financial market predictions. Retrieved from Mathematical Problems in Engineering https://onlinelibrary.wiley.com/doi/10.1155/2020/1479507
Smales, L. A. (2021). Investor attention and global market returns during the COVID-19 crisis. International Review of Financial Analysis, 73.
Størdal, S., Lien, G., Mydland, Ø., & Haugom, E. (2021). Effects of strong and weak non-pharmaceutical interventions on stock market returns: A comparative analysis of Norway and Sweden during the initial phase of the COVID-19 pandemic. Economic Analysis and Policy, 70, 341-350.
Su, Z., Liu, P., & Fang, T. (2022). Pandemic-induced fear and stock market returns: Evidence from China. Global Finance Journal, 54.
Syed, S. A. S. (2022). Stock market in the age of COVID19: Mere acclimatization or Stockholm syndrome?. The Journal of Economic Asymmetries, 25.
Takahashi, H., & Yamada, K. (2021). When the Japanese stock market meets COVID-19: Impact of ownership, China and US exposure, and ESG channels. International Review of Financial Analysis, 74.
Talwar, S., Talwar, M., Tarjanne, V., & Dhir, A. (2021). Why retail investors traded equity during the pandemic? An application of artificial neural networks to examine behavioral biases. Psychology & Marketing, 38(11), 2142-2163.
Tawfik, G. M., Dila,K.A.S., Mohamed, M.Y.F., Tam, D.N.H., Kien, N.D., Ahmed, A.M., & Huy, N.T. (2019). A step by step guide for conducting a systematic review and meta-analysis with simulation data. Tropical Medicine and Health, 47(1).
The Decision Lab. (2022, December 9). Cognitive biases: A list of the most relevant biases in behavioral economics. Retrieved from https://thedecisionlab.com/biases
U.S. Food and Drug Administration. (2021, August 23). FDA approves first COVID-19 vaccine: Approval signifies key achievement for public health. Retrieved from https://www.fda.gov/news-events/press-announcements/fda-approves-first-covid-19-vaccine
Vowels, M.J. (2022). A causal research pipeline and tutorial for psychologists and social scientists. Retrieved from arXiv https://arxiv.org/abs/2206.05175
World Health Organization. (2023, May 18). The true death toll of COVID-19: Estimating global excess mortality. Retrieved from The true death toll of COVID-19 https://www.who.int/data/stories/the-true-death-toll-of-covid-19-estimating-global-excess-mortality
World Health Organization Regional Office for the Western Pacific. (2020). Calibrating long-term non-pharmaceutical interventions for COVID-19: Principles and facilitation tools. Retrieved from WHO Regional Office for the Western Pacific https://apps.who.int/iris/handle/10665/332099
Yu, X., Xiao, K., & Liu, J. (2022). Dynamic co-movements of COVID-19 pandemic anxieties and stock market returns. Finance Research Letters, 46.
Zaremba, A., Kizys, R., Tzouvanas, P., Aharon, D. Y., & Demir, E. (2021). The quest for multidimensional financial immunity to the COVID-19 pandemic: Evidence from international stock markets. Journal of International Financial Markets, Institutions and Money, 71.
Zheng, W., Li, B., Huang, Z., & Chen, L. (2022). Why was there more household stock market participation during the COVID-19 pandemic?. Finance Research Letters, 46.
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2025 Thailand and The World Economy

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.







