The first wave impact of the COVID-19 pandemic on the Nasdaq Helsinki stock exchange: Weak signal detection with managerial implications


  • Kalle Nuortimo
  • Janne Härkönen


Covid-19, early signals, Nasdaq Helsinki, signal detection, social media


The global pandemic caused by the coronavirus disease (COVID-19) came mostlyas a surprise and had a major effect on the global economy. This type of major events that canbring societies to nearly a total standstill are difficult to predict but have a significant impacton business activities. Nevertheless, weak signals might be possible to detect beforehand toenable preparation for the impact, both globally and locally. This study analyses the impact ofthe first wave of the COVID-19 pandemic on the Nasdaq Helsinki stock exchange by utilisinglarge-scale media analytics. This entails gaining data through media monitoring over the entireduration of the pandemic by applying black-box algorithms and advanced analytics on realcases. The data analysis is carried out to understand the impact of a such global event ingeneral, while aiming to learn from the potential weak signals to enable future marketintelligence to prepare for similar events. A social media firestorm scale, similar to the Richterscale for earthquakes or Sapphir-Simpson scale for hurricanes, is utilised to support theanalysis and assist in explaining the phenomenon. The results indicate that pandemics andtheir impact on markets can be studied as a subset of a media firestorms that produce a sharkfintype of pattern in analytics. The findings indicate that early signals from such events arepossible to detect by means of media monitoring, and that the stock exchange behaviour isaffected. The implications include highlighting the importance of weak signal detection fromabundant data to have the possibility to instigate preventive actions and prepare for such eventsto avoid maximum negative business impact. The early reaction to this type of events requiresa very streamlined connection between market intelligence and different business activities.


Apte, C. Dietrich B. &Fleming, M. (2012).

Business leadership through analytics. IBM

Journal of Research and Development, 56(6),

: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-

International Journal of Financial Studies,

(1), 5. DOI:

Aven, T. (2013). On the meaning of a black swan

in a risk context. Safety science, 57, 44-51.


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,


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.


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,

,107242, DOI:

Bloom, D.E., Cadarette, D. & Sevilla, J.P. (2018).

Epidemics and economics. Finance &

Development, 55(2), 46-49. DOI:

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-


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.


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:


Chen, H., Chiang, R.H.L. & Storey, V.C. (2012).

Business Intelligence and Analytics: From Big

Data to Big Impact. MIS Quarterly, 36(4),


Chien, F., Sadiq, M., Kamran, H.W., Nawaz,

M.A., Hussain, M.S. &Raza, M. (2021). Comovement

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.



Contessi, S. & De Pace, P. (2021). The

international spread of COVID-19 stock

market collapses. Finance Research Letters,

, 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.



Elnahas, A., Kim, D. & Kim, I. (2018). Natural

disaster risk and corporate leverage. DOI:

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:

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:

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:


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:


Helm, D. (2020). The environmental impacts of

the coronavirus. Environmental and Resource

Economics, 76, 21-38. DOI:

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),


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.


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),


Lee, H.S. (2020). Exploring the Initial Impact of

COVID-19 Sentiment on US Stock Market

Using Big Data. Sustainability, 12, 6648. DOI:

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.


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.


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.


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:

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,

-233. DOI:


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.


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:


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:


Romero, T.A.T., Ortiz, J.H., Khalaf, O.I. & Prado,

A.R. (2021). Business Intelligence: Business

Evolution after Industry 4.0. Sustainability,

, 10026. DOI:

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:

Taleb, N.N. (2007). The black swan: The impact

of the highly improbable, Vol. 2, Random


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 –

pandemic on global stock market volatility:

Can economic strength help to manage the

uncertainty? Journal of Business Research,

, 31-44. DOI:

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




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:

Yan, L. & Qian, Y. (2020). The impact of COVID-

on the Chinese stock market: An event

study based on the consumer industry. Asian

Economics Letters, 1(3), 1-5. DOI:


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,

, 120710. DOI:

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,


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.





2021-10-13 — Updated on 2021-10-19