Stock Market Investors’ Reactions to the Tone of Press Articles

Ewelina Niedzielska

Abstract


Theoretical background: The investigation into investor reactions to non-financial information was motivated by two key considerations. First, within financial theory, an unresolved debate persists regarding how stock market investors discount information. This article references two paradigms central to this issue: the neoclassical and the behavioral. The second motivation stems from the emergence of a new type of data in the literature, known as Big Text, which refers to large, unstructured collections of textual data. This phenomenon is associated with the development of non-financial reporting and the increasing quantity and diversity of information providers in financial markets.

Purpose of the article: The aim of the study was to assess investors' reactions to the content of press articles based on their emotional tone. To achieve this goal, two hypotheses were tested. First, it was hypothesized that the appearance of a press article would be reflected in the stock returns of the companies under study. Second, it was hypothesized that this reaction would be asymmetrical, depending on whether the article's tone was positive or negative.

Research methods: The study focused on companies included in the WIG20 index of the Warsaw Stock Exchange from 2013 to 2022. For these companies, a database of English-language press publications with a high degree of positive or negative emotional tone was constructed. The research was conducted using the event study methodology, with the event defined as the day the article appeared.

Main findings: The results suported the hypotheses. Additionally, differences in the way information was discounted depending on emotional tone were observed. Negative publications triggered strong, abrupt, and short-lived reactions, while reactions to positive publications were weaker and more prolonged over time.


Keywords


stock exchange; text analysis; sentiment analysis; behavioral finance; Efficient Market Hypothesis

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References


Agrawal, A., Jaffe, J. F., & Mandelker, G.N. (2009). The long-term performance of acquiring firms: A re-examination of an anomaly. Journal of Banking and Finance, 33(8). https://doi.org/10.1016/j.jbankfin.2009.02.004

Akerlof, G.A. (1984). The market for “lemons”: Quality uncertainty and the market mechanism. In G.A. Akerlof (Ed.), An Economic Theorist’s Book of Tales (pp. 7–22). Cambridge University Press.

Allen, D.E., McAleer, M., & Singh, A.K. (2019). Daily market news sentiment and stock prices. Applied Economics, 51(30), 3212–3235. https://doi.org/10.1080/00036846.2018.1564115

Alomari, M., Al Rababa’a, A.R., El-Nader, G., Alkhataybeh, A., & Ur Rehman, M. (2021). Examining the effects of news and media sentiments on volatility and correlation: Evidence from the UK. Quarterly Review of Economics and Finance, 82. https://doi.org/10.1016/j.qref.2021.09.013

Ardia, D., Bluteau, K., & Boudt, K. (2022). Media abnormal tone, earnings announcements, and the stock market. Journal of Financial Markets, 61. https://doi.org/10.1016/j.finmar.2021.100683

Borden, M.J. (2007). The role of financial reporting in corporate governance. Fordham Journal of Corporate & Financial Law, 12.

Borowski, K. (2014). Finanse behawioralne. Modele. Difin.

Bouteska, A. (2019). The effect of investor sentiment on market reactions to financial earnings restatements: Lessons from the United States. Journal of Behavioral and Experimental Finance, 24. https://doi.org/10.1016/j.jbef.2019.100241

Chen, K., Luo, P., Liu, L., & Zhang, W. (2018). News, search and stock co-movement: Investigating information diffusion in the financial market. Electronic Commerce Research and Applications, 28. https://doi.org/10.1016/j.elerap.2018.01.015

Crawford Camiciottoli, B. (2020). Using English as a lingua franca to engage with investors: An analysis of Italian and Japanese companies’ investor relations communication policies. English for Specific Purposes, 58. https://doi.org/10.1016/j.esp.2020.01.003

Damstra, A., & De Swert, K. (2020). The making of economic news: Dutch economic journalists contextualizing their work. Journalism. https://doi.org/10.1177/1464884919897161

Das, S.R., & Chen, M. (2007). Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web. Management Science, 53(9). https://doi.org/10.1287/mnsc.1070.0704

Das, S.R. (2014). Text and Context: Language Analytics in Finance. In Foundations and Trends® in Finance, 8(3). https://doi.org/10.1561/0500000045

EMIS. (n.d.). https://www.emis.com

Entman, R. (1993). Framing: Toward a clarification of a fractured paradigm. Journal of Communication, 43(3).

Fama, E.F. (1965). The behavior of stock-market prices. The Journal of Business, 38(1). https://doi.org/10.1086/294743

Fama, E.F. (1970). Efficient capital markets : A review of theory and empirical work. The Journal of Finance, 25(2). https://doi.org/10.2307/2325486

Fedorova, E., Drogovoz, P., Nevredinov, A., Kazinina, P., & Qitan, C. (2022). Impact of MD&A sentiment on corporate investment in developing economies: Chinese evidence. Asian Review of Accounting, 30(4). https://doi.org/10.1108/ARA-08-2021-0151

Feuerriegel, S., & Gordon, J. (2018). Long-term stock index forecasting based on text mining of regulatory disclosures. Decision Support Systems, 112(December 2017). https://doi.org/10.1016/j.dss.2018.06.008

Fraiberger, S. P., Lee, D., Puy, D., & Ranciere, R. (2021). Media sentiment and international asset prices. Journal of International Economics, 133. https://doi.org/10.1016/j.jinteco.2021.103526

Gajdka, J. (2013). Behawioralne finanse przedsiębiorstw. Podstawowe podejścia i koncepcje. Wyd. UŁ.

Giełda Papierów Wartościowych w Warszawie. (2016, February 22). Udział inwestorów indywidualnych w obrotach na rynku akcji w 2015 r. https://www.gpw.pl/pub/GPW/analizy/2015_P2_Udzialy_20160222.pdf

Giełda Papierów Wartościowych w Warszawie. (2023). Udział inwestorów indywidualnych w obrotach na rynku akcji: 1H2023. https://www.gpw.pl/pub/GPW/analizy/Udzial_inwestorow_1H2023.pdf

Guo, L., Shi, F., & Tu, J. (2016). Textual analysis and machine leaning: Crack unstructured data in finance and accounting. The Journal of Finance and Data Science, 2(3). https://doi.org/10.1016/j.jfds.2017.02.001

Gurgul, H. (2019). Analiza zdarzeń na rynkach akcji. Wpływ informacji na ceny papierów wartościowych. Nieoczywiste.

Harvard University. (n.d.). The Inquirer. https://inquirer.sites.fas.harvard.edu/

Herrera, G.P., Constantino, M., Su, J.J., & Naranpanawa, A. (2022). Renewable energy stocks forecast using Twitter investor sentiment and deep learning. Energy Economics, 114(August). https://doi.org/10.1016/j.eneco.2022.106285

IDC. (2023, August). Untapped value: What every executive needs to know about unstructured data (Doc # US51128223). https://images.g2crowd.com/uploads/attachment/file/1350731/IDC-Unstructured-Data-White-Paper.pdf

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. The Econometric Society, 47(2).

Kearney, C., & Liu, S. (2014). Textual sentiment in finance: A survey of methods and models. International Review of Financial Analysis, 33. https://doi.org/10.1016/j.irfa.2014.02.006

Khedr, A. E., Salama, S. E., & Yaseen, N. (2017). Predicting stock market behavior using data mining technique and news sentiment analysis. International Journal of Intelligent Systems and Applications, 9(7). https://doi.org/10.5815/ijisa.2017.07.03

Kleinnijenhuis, J., Schultz, F., Oegema, D., & Van Atteveldt, W. (2013). Financial news and market panics in the age of high-frequency sentiment trading algorithms. Journalism, 14(2). https://doi.org/10.1177/1464884912468375

Larsen, V.H., & Thorsrud, L.A. (2017). Asset returns, news topics, and media effects. In CAMP Working Paper Series, 5. https://doi.org/10.1111/sjoe.12469

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 and Accountability Journal, 35(1). https://doi.org/10.1108/AAAJ-08-2020-4786

Li, X., Wu, P., & Wang, W. (2020). Incorporating stock prices and news sentiments for stock market prediction: A case of Hong Kong. Information Processing and Management, 57(5). https://doi.org/10.1016/j.ipm.2020.102212

Li, X., Xie, H., Chen, L., Wang, J., & Deng, X. (2014). News impact on stock price return via sentiment analysis. Knowledge-Based Systems, 69. https://doi.org/10.1016/j.knosys.2014.04.022

Menkhoff, L., Schmidt, U., & Brozynski, T. (2006). The impact of experience on risk taking, overconfidence, and herding of fund managers: Complementary survey evidence. European Economic Review, 50(7). https://doi.org/10.1016/j.euroecorev.2005.08.001

Merrill, G.J. (2019). The political content of british economic, business and financial journalism. In The Political Content of British Economic, Business and Financial Journalism. https://doi.org/10.1007/978-3-030-04012-3

Picard, R.G., Selva, M., & Bironzo, D. (2014). Media Coverage of Banking and Financial News. University of Oxford, Reuters Institute for the Study of Journalism.

Rostek, K., & Młodzianowski, P. (2017). Współzależność informacji sieciowych oraz zmian indeksów zachodzących na Giełdzie Papierów Wartościowych w Warszawie. Zeszyty Naukowe Uniwersytetu Przyrodniczo-Humanistycznego w Siedlcach, 42(115). https://doi.org/10.1111/j.1740-9713.2012.00584.x

Schumaker, R.P., & Chen, H. (2009). Textual analysis of stock market prediction using breaking financial news : The AZFinText System. ACM Transactions on Information Systems, 27(2). https://doi.org/10.1145/1462198.1462204

Shefrin, H. (2002). Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing. Oxford University Press.

Siganos, A., Vagenas-Nanos, E., & Verwijmeren, P. (2014). Facebook’s daily sentiment and international stock markets. Journal of Economic Behavior and Organization, 107(PB). https://doi.org/10.1016/j.jebo.2014.06.004

Smales, L.A. (2014). News sentiment in the gold futures market. https://doi.org/10.1016/j.jbankfin.2014.09.006

Stooq. (n.d.). https://stooq.pl

Stooq. (n.d.). Stooq Poland All Stocks Price Index. https://stooq.pl/q/p/?s=^_pl

Stowarzyszenie Inwestorów Indywidualnych. (2023). Najpopularniejsze źródła informacji dla inwestorów. https://www.sii.org.pl/16873/aktualnosci/badania-i-rankingi/najpopularniejsze-zrodla-informacji-dla-inwestorow-obi-2023.html

Strauß, N., Vliegenthart, R., & Verhoeven, P. (2016). Lagging behind? Emotions in newspaper articles and stock market prices in the Netherlands. Public Relations Review, 42(4). https://doi.org/10.1016/j.pubrev.2016.03.010

Szyszka, A. (2013). Behavioral finance and capital markets: How psychology influences investors and corporations. Palgrave Macmillan.

Tetlock, P.C. (2007). Giving content to investor sentiment : The role of media in the stock market published. The Journal of Finance, LXII(3), 1139–1168.

Thompson, P.A. (2009). Market manipulation? Applying the propaganda model to financial media reporting. Westminster Papers in Communication and Culture, 6(2), 73. https://doi.org/10.16997/wpcc.125

Tversky, A., & Kahneman, D. (1984). Choices, values, and frames. American Psycologist, 39(4).

West, J., & Bhattacharya, M. (2016). Intelligent financial fraud detection: A comprehensive review. Computers and Security, 57. https://doi.org/10.1016/j.cose.2015.09.005

Yekini, L.S., Wiśniewski, P.T., & Millo, Y. (2016). Market reaction to the positiveness of annual report narratives. The British Accounting Review, 48(4). https://doi.org/10.1016/j.bar.2015.12.001

Zikopoulos, P., Eaton, C., & DeRoos, D. (2012). Understanding big data. Analytics for Enterprise Class Hadoop and Streaming Data. In CIM Magazine, 11(1).

Zubair, S., & Cios, K.J. (2015). Extracting News Sentiment and Establishing its Relationship with the S&P500 Index. in 48th Hawaii International Conference on System Sciences. https://doi.org/10.1109/HICSS.2015.120




DOI: http://dx.doi.org/10.17951/h.2025.59.2.143-160
Date of publication: 2025-09-02 13:03:30
Date of submission: 2024-10-12 01:41:19


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