The first wave impact of the COVID-19 pandemic on the Nasdaq Helsinki stock exchange: Weak signal detection with managerial implications
DOI:
https://doi.org/10.37380/jisib.v11i2.702Keywords:
Covid-19, early signals, Nasdaq Helsinki, signal detection, social mediaAbstract
The global pandemic caused by the coronavirus disease (COVID-19) came mostly as a surprise and had a major effect on the global economy. This type of major events that can bring societies to nearly a total standstill are difficult to predict but have a significant impact on business activities. Nevertheless, weak signals might be possible to detect beforehand to enable preparation for the impact, both globally and locally. This study analyses the impact of the first wave of the COVID-19 pandemic on the Nasdaq Helsinki stock exchange by utilising large-scale media analytics. This entails gaining data through media monitoring over the entire duration of the pandemic by applying black-box algorithms and advanced analytics on real cases. The data analysis is carried out to understand the impact of a such global event in general, while aiming to learn from the potential weak signals to enable future market intelligence to prepare for similar events. A social media firestorm scale, similar to the Richter scale for earthquakes or Sapphir-Simpson scale for hurricanes, is utilised to support the analysis and assist in explaining the phenomenon. The results indicate that pandemics and their impact on markets can be studied as a subset of a media firestorms that produce a shark- fin type of pattern in analytics. The findings indicate that early signals from such events are possible to detect by means of media monitoring, and that the stock exchange behaviour is affected. The implications include highlighting the importance of weak signal detection from abundant data to have the possibility to instigate preventive actions and prepare for such events to avoid maximum negative business impact. The early reaction to this type of events requires a very streamlined connection between market intelligence and different business activities.
References
Apte, C. Dietrich B. & Fleming, M. (2012). Business leadership through analytics. IBM Journal of Research and Development, 56(6), 7:1-7:5. DOI: 10.1147/JRD.2012.2214555.
Aslam, F., Ferreira, P., Mughal, K.S. & Bashir, B. (2021) Intraday Volatility Spillovers among European Financial Markets during COVID-19. International Journal of Financial Studies, 9(1), 5. DOI: https://doi.org/10.3390/ijfs901000 Aven, T. (2013). On the meaning of a black swan in a risk context. Safety science, 57, 44-51. DOI: https://doi.org/10.1016/j.ssci.2013.01.016
Al-Awadhi, A.M., Alsaifi, K., Al-Awadhi, A. & Alhammadi, S. (2020). Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns. Journal of behavioral and experimental finance, 27, 100326. DOI: https://doi.org/10.1016/j.jbef.2020.100326
Baker, S.R., Bloom, N., Davis, S.J., Kost, K., Sammon, M. & Viratyosin, T. (2020). The Unprecedented Stock Market Reaction to COVID-19. The Review of Asset Pricing Studies, 10(4), 742–758. DOI:https://doi.org/10.1093/rapstu/raaa008
Basiri, M.E., Nemati, S., Abdar, M., Asadi, S. & Acharrya, U.R. (2021) A novel fusion-based deep learning model for sentiment analysis of COVID-19 tweets. Knowledge-Based Systems, 228,107242, DOI: https://doi.org/10.1016/j.knosys.2021.107242.
Bloom, D.E., Cadarette, D. & Sevilla, J.P. (2018). Epidemics and economics. Finance & Development, 55(2), 46-49. DOI: https://doi.org/10.5089/9781484357415.022
Carter, D.A. & Simkins, B.J. (2004). The market’s reaction to unexpected, catastrophic events: the case of airline stock returns and the September 11th attacks. The Quarterly Review of Economics and Finance, 44(4), 539-558. DOI: https://doi.org/10.1016/j.qref.2003.10.001
Casarotto, E.L., Malafaia, G.C., Martínez, M.P. & Binotto, E. (2020). Interpreting, analyzing and distributing information: A big data framework for competitive intelligence. Journal of Intelligence Studies in Business, 11(1), 6-18. DOI: https://doi.org/10.37380/jisib.v1i1
Chang, C.-P., Feng, G.-F. & Zheng, M. (2021).
Government Fighting Pandemic, Stock Market Return, and COVID-19 Virus Outbreak. Emerging Markets Finance and Trade, 57:8, 2389-2406. DOI: 10.1080/1540496X.2021.1873129
Chen, H., Chiang, R.H.L. & Storey, V.C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165-1188.
Chien, F., Sadiq, M., Kamran, H.W., Nawaz, M.A., Hussain, M.S. &Raza, M. (2021). Co- movement of energy prices and stock market return: environmental wavelet nexus of COVID-19 pandemic from the USA, Europe, and China. Environmental Science and Pollution Research, 28, 32359–32373. DOI:https://doi.org/10.1007/s11356-021- 12938-2
Contessi, S. & De Pace, P. (2021). The international spread of COVID-19 stock market collapses. Finance Research Letters, 42, 101894. DOI:https://doi.org/10.1016/j.frl.2020.101894.
Dai, PF., Xiong, X., Liu, Z., Huynh, T.L. & Sun, J. (2021). Preventing crash in stock market: The role of economic policy uncertainty during COVID-19. Financial Innovation, 7, 31. DOI:https://doi.org/10.1186/s40854-021-00248-y
Elnahas, A., Kim, D. & Kim, I. (2018). Natural disaster risk and corporate leverage. DOI: http://dx.doi.org/10.2139/ssrn.
Engelhardt, N., Krause, M., Neukirchen, D. & Posch, P.N. (2021). Trust and stock market volatility during the COVID-19 crisis. Finance Research Letters, 38, 101873. DOI: https://doi.org/10.1016/j.frl.2020.101873.
Ferrer, R. (2020) "COVID-19 Pandemic: the greatest challenge in the history of critical care", Medicina Intensiva, 44(6), 323-324.
Flage, R., & Aven, T. (2015). Emerging risk– Conceptual definition and a relation to black swan type of events. Reliability Engineering & System Safety, 144, 61-67. DOI: https://doi.org/10.1016/j.ress.2015.07.008
Gao, X., Ren, Y. & Umar, M. (2021). To what extent does COVID-19 drive stock market volatility? A comparison between the U.S. and China. Economic Research-Ekonomska Istraživanja. DOI:10.1080/1331677X.2021.1906730
Harjoto, M.A., Rossi, F. & Paglia, J.K. (2021). COVID-19: stock market reactions to the shock and the stimulus. Applied Economics Letters, 28(10), 795-801. DOI:10.1080/13504851.2020.1781767
Helm, D. (2020). The environmental impacts of the coronavirus. Environmental and Resource Economics, 76, 21-38. DOI: https://doi.org/10.1007/s10640-020-00426-z
Inayatullah, S. (2020). Neither a black swan nor a zombie apocalypse: the futures of a world with the covid-19 coronavirus. Journal of Futures Studies, 18.
Jeble, S., Kumari, S. & Patil, Y. (2016). Role of big data and predictive analytics. International Journal of Automation and Logistics, 2(4), 307–331.
Karabag, S.F. (2020). An unprecedented global crisis! The global, regional, national, political, economic and commercial impact of the coronavirus pandemic. Journal of Applied Economics and Business Research, 10(1), 1-6.
Kauppalehti. https://www.kauppalehti.fi/. Retrieved in 12.9.2021.
Larson, D. & Chang, V. (2016). A review and future direction of agile, business intelligence, analytics and data science. International Journal of Information Management, 36(5), 700-710.
Lee, H.S. (2020). Exploring the Initial Impact of COVID-19 Sentiment on US Stock Market Using Big Data. Sustainability, 12, 6648. DOI: https://doi.org/10.3390/su12166648
Leidner, J.L. & Schilder, F. (2010). Hunting for the black swan: risk mining from text. In Proceedings of the ACL 2010 System Demonstrations (pp. 54-59).
Lescab, H. (2019). Collective intelligence process to interpret weak signals and early warnings. Journal of Intelligence Studies in Business, 9(2), 19-29. DOI: https://doi.org/10.37380/jisib.v9i2.466
Li, J., Nguyen, T.H.H. & Coca-Stefaniak, J.A. (2020). Coronavirus impacts on post-pandemic planned travel behaviours. Annals of Tourism Research, 102964. Advance online publication. DOI: https://doi.org/10.1016/j.annals.2020.102964
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. DOI:https://doi.org/10.1016/j.ribaf.2021.101419.
Lu, H., Stratton, C.W. & Tang, Y.-T. (2020) "Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle", Medical Virology, 92(4), 401-402.
Parameswar, N., Chaubey, A. & Dhir, S. (2021). Black swan: bibliometric analysis and development of research agenda. Benchmarking: An International Journal, 28(7), 2259-2279.
Phan, D. H. B., & Narayan, P. K. (2020). Country responses and the reaction of the stock market to COVID-19—A preliminary exposition. Emerging Markets Finance and Trade, 56(10), 2138-2150.
Mazur, M., Dang, M., Vega, M. (2021). COVID-19 and the march 2020 stock market crash. Evidence from S&P1500. Finance Research Letters, 38, 101690. DOI: https://doi.org/10.1016/j.frl.2020.101690.
Nettleton, D. (2014). Commercial Data Mining: Processing, Analysis and Modeling for Predictive Analytics Projects. Morgan Kaufmann, Waltham.
Nuortimo, K., Karvonen, E. & Härkönen, J. (2020). Establishing social media firestorm scale via large dataset media analytics. Journal of Marketing Analytics, 8, 224-233. DOI: https://doi.org/10.1057/s41270-020-00080-w
Nuortimo, K. (2021). Hybrid approach in digital humanities research: a global comparative opinion mining media study, Acta Universitatis Ouluensis. B, Humaniora, University of Oulu
Pano, T. & Kashef, R.A. (2020). Complete VADER-Based Sentiment Analysis of Bitcoin (BTC) Tweets during the Era of COVID-19. Big Data and Cognitive Computing, 4, 33. DOI:https://doi.org/10.3390/bdcc4040033
Phan, D.H.B. & Narayan, P.K. (2020). Country Responses and the Reaction of the Stock Market to COVID-19—a Preliminary Exposition. Emerging Markets Finance and Trade, 56(10), 2138-2150. DOI: 10.1080/1540496X.2020.1784719
Rahman, M.L., Amin, A. & Al Mamun, M.A. (2021). The COVID-19 outbreak and stock market reactions: Evidence from Australia. Finance Research Letters 38, 101832. DOI: ttps://doi.org/10.1016/j.frl.2020.101832.
Romero, T.A.T., Ortiz, J.H., Khalaf, O.I. & Prado,
A.R. (2021). Business Intelligence: Business Evolution after Industry 4.0. Sustainability, 13, 10026. DOI: https://doi.org/10.3390/su131810026
Schneider, G. & Troeger, V.E. (2006). War and the world economy: Stock market reactions to international conflicts. Journal of conflict resolution, 50(5), 623-645.
Shmueli, G. & Koppius, O.R. (2011). Predictive analytics in information systems research. MIS Quarterly, 35(3), 553-572.
Takyi, P.O. & Bentum-Ennin, I. (2021). The impact of COVID-19 on stock market performance in Africa: A Bayesian structural time series approach. Journal of Economics and Business, 115, 105968. DOI: https://doi.org/10.1016/j.jeconbus.2020.10596 8
Taleb, N.N. (2007). The black swan: The impact of the highly improbable, Vol. 2, Random house.
Töllinen, A., Järvinen, J., & Karjaluoto, H. (2012). Social media monitoring in the industrial business to business sector. World Journal of Social Sciences.
Uddin, M., Chowdhury, A., Anderson, K. & Chaudhuri, K. (2021). The effect of COVID – 19 pandemic on global stock market volatility: Can economic strength help to manage the uncertainty? Journal of Business Research, 128, 31-44. DOI: https://doi.org/10.1016/j.jbusres.2021.01.061.
Valle-Cruz, D., Fernandez-Cortez, V., López-Chau, A. & Sandoval-Almazán, R. (2021). Does Twitter Affect Stock Market Decisions? Financial Sentiment Analysis During Pandemics: A Comparative Study of the H1N1 and the COVID-19 Periods. Cognitive Computation. DOI:https://doi.org/10.1007/s12559-021-09819-8
Walmsley, T., Rose, A. & Wei, D. (2021). The Impacts of the Coronavirus on the Economy of the United States. Economics of disasters and climate change, 5(1), 1-52. DOI: https://doi.org/10.1007/s41885-020-00080-1
Yan, L. & Qian, Y. (2020). The impact of COVID-19 on the Chinese stock market: An event study based on the consumer industry. Asian Economics Letters, 1(3), 1-5. DOI: 10.46557/001c.18068
Yaqub, U. (2020). Tweeting During the Covid-19 Pandemic: Sentiment Analysis of Twitter Messages by President Trump. Digital Government: Research and Practice, 2(1), Article 1.
Yousfi, M., Zaied, Y.B., Cheikh, N.B., Lahouel, B.B. & Bouzgarrou, H. (2021). Effects of the COVID-19 pandemic on the US stock market and uncertainty: A comparative assessment between the first and second waves. Technological Forecasting and Social Change, 167, 120710. DOI:https://doi.org/10.1016/j.techfore.2021.120710
Zaremba, A., Aharon, D.Y., Demir, E., Kizys, R. & Zawadka, D. (2021). COVID-19, government policy responses, and stock market liquidity around the world: A note. Research in International Business and Finance, 56, 101359. DOI:https://doi.org/10.1016/j.ribaf.2020.101359.
Zhang, X., Yang, Q., Albaradei, S. et al. (2021). Rise and fall of the global conversation and shifting sentiments during the COVID-19 pandemic. Humanities and social sciences communications, 8, 120. DOI:https://doi.org/10.1057/s41599-021-00798-7
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