Skip to main content
SpringerLink
Log in

Stock Price Reactions to Wire News from the European Central Bank: Evidence from Changes in the Sentiment Tone and International Market Indexes

  • Published:
International Advances in Economic Research Aims and scope Submit manuscript

Abstract

This paper examines the link between changes in the sentiment tone with respect to the European Central Bank’s (ECB) announcements and stock returns. The analysis constructs a new index that describes the tone of the sentiment derived from these announcements, spanning the period January 2002 to June 2016. The novelty of this work relies on the development of a unique sentiment index associated with the messages conveyed by the ECB’s activities and the effect of this index on both the mean and the volatility of certain major international stock markets. In this context, the sentiment index is present in both the conditional mean and the volatility equations. The findings indicate a significant impact on both the mean and the volatility of returns, whereas the news sentiment/stock returns association increases in strength during the crisis period. The findings survive a robustness check based on the characteristics of the ECB governor’s personality.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2007). Real-time price discovery in global stock, bond and foreign exchange markets. Journal of International Economics, 73(1), 251–277.

    Article  Google Scholar 

  • Apel, M. and Grimaldi, M. (2012). The information content of central bank minutes. Riksbank Research Paper Series, No. 92. http://archive.riksbank.se/Documents/Rapporter/Working_papers/2012/rap_wp261_120426.pdf. Accessed 20 May 2017.

  • Bai, Y. (2014). Cross-border sentiment: An empirical analysis on EU stock markets. Applied Financial Economics, 24(1), 259–290.

    Article  Google Scholar 

  • Baker, M. P., & Wurgler, J. A. (2006). Investor sentiment and the cross-section of stock returns. The Journal of Finance, 61(4), 1645–1680.

    Article  Google Scholar 

  • Baker, M. P., & Wurgler, J. A. (2007). Investor sentiment in the stock market. Journal of Economic Perspectives, 21(1), 129–151.

    Article  Google Scholar 

  • Baker, M. P., Wurgler, J. A., & Yuan, Y. (2012). Global, local, and contagious investor sentiment. Journal of Financial Economics, 104(1), 272–287.

    Article  Google Scholar 

  • Barone-Adesi, G., Mancini, L., & Shefrin, H. (2012). Sentiment, asset prices, and systemic risk. In J. P. Fouque & J. Langsam (Eds.), Handbook of systemic risk. Cambridge: Cambridge University Press.

    Google Scholar 

  • Beetsma, R., Giuliodori, M., De Jongg, F., & Widijanto, D. (2013). Spread the news: The impact of news on the European sovereign bond markets during the crisis. Journal of International Money and Finance, 34(1), 83–101.

    Article  Google Scholar 

  • Bernanke, B. S., Gertler, M., & Gilchrist, S. (1999). The financial accelerator in a quantitative business cycle framework. In J. B. Taylor & M. Woodford (Eds.), Handbook of Macroeconomics 1, Chapter 21 (pp. 1341–1393). Elsevier.

  • Bernoth, K., & Von Hagen, J. (2004). The Euribor futures market: Efficiency and the impact of ECB policy announcements. International Finance, 7(1), 1–24.

    Article  Google Scholar 

  • Bholat, D., Hansen, S., Santos, P., & Schonhardt-Bailey, C. (2015). Text mining for central banks: Handbook. Centre for Central Banking Studies, 33(1), 1–19.

    Google Scholar 

  • Bibow, J. (2013). At the crossroads: The euro and its central bank guardian (and savior?). Cambridge Journal of Economics, 37(3), 609–626.

    Article  Google Scholar 

  • Blajer-Gołębiewska, B. (2012). Stock exchange indices and abnormal returns in the crisis condition. Journal of International Studies, 5(1), 9–17.

    Article  Google Scholar 

  • Blinder, A. S. (2009). Making monetary policy by committee. International Finance, 12(1), 171–194.

    Article  Google Scholar 

  • Blinder, A. S., Ehrmann, M., Fratzscher, M., de Haan, J., & Jansen, D. J. (2008). Central bank communication and monetary policy: A survey of theory and evidence. Journal of Economic Literature, 46(4), 910–945.

    Article  Google Scholar 

  • Bloom, N. (2009). The impact of uncertainty shocks. Econometrica, 77(3), 623–685.

    Article  Google Scholar 

  • Bloom, N. (2014). Fluctuations in uncertainty. Journal of Economic Perspectives, 28(1), 153–176.

    Article  Google Scholar 

  • Boudoukh, J., Feldman, R., Kogan, S. and Richardson, M. (2013). Which news moves stock prices? A textual analysis. NBER Working Paper, No. 18725. https://www.nber.org/papers/w18725.pdf. Accessed 25 August 2017.

  • Bouis, R., Rawdanowicz, L., Renne, J.P., Watanabe, S. and Christensen, A.K. (2013). The effectiveness of monetary policy since the onset of the financial crisis. Department Working Papers, No. 1081, OECD Publishing, Paris. https://doi.org/10.1787/5k41zq9brrbr-en.

  • Brunnermeier, M. K. (2009). Deciphering the liquidity and credit crunch 2007-2008. Journal of Economic Perspectives, 23(1), 77–100.

    Article  Google Scholar 

  • Brunnermeier, M. K., & Pedersen, L. H. (2009). Market liquidity and funding liquidity. Review of Financial Studies, 22(6), 2201–2238.

    Article  Google Scholar 

  • Bulíř, A., Čihák, M., & Jansen, D. J. (2013). What drives clarity of central bank communication about inflation. Open Economies Review, 24(1), 125–145.

    Article  Google Scholar 

  • Chen, H., De, P., Hu, J., & Hwang, B. H. (2014). Wisdom of crowds: The value of stock opinions transmitted through social media. Review of Financial Studies, 27(5), 1367–1403.

    Article  Google Scholar 

  • Christensen, J. H. E., Lopez, J. A., & Rudebusch, G. D. (2014). Do central bank liquidity facilities affect interbank lending rates? Journal of Business & Economic Statistics, 32(1), 136–151 https://www.frbsf.org/economic-research/files/wp09-13bk.pdf. Accessed 27 August 2017.

  • Claussen, C. A., Matsen, E., Røisland, Ø., & Torvik, R. (2012). Overconfidence, monetary policy committees and chairman dominance. Journal of Economic Behavior and Organization, 81(2), 699–711.

    Article  Google Scholar 

  • D’Amico, S., & Farka, M. (2001). The fed and the stock market: An identification based on intraday futures data. Journal of Business and Economic Statistics, 29(1), 126–137.

    Article  Google Scholar 

  • Dées, S., & Brinca, P. S. (2013). Consumer confidence as a predictor of consumption spending: Evidence for the United States and the euro area. International Economics, 134(1), 1–14.

    Article  Google Scholar 

  • Dougal, C., Engelberg, J., García, D., & Parsons, C. A. (2012). Journalists and the stock market. Review of Financial Studies, 25(3), 639–679.

    Article  Google Scholar 

  • Eisenschmidt, J. and Tapking, J. (2009). Liquidity risk premia in unsecured interbank money markets. Working Paper, No. 1025, European Central Bank. https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1025.pdf?70555a16b0b7eb51bbca86a7b111b59e. Accessed 6 August 2017.

  • Elliot, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4), 813–836.

    Article  Google Scholar 

  • Fawley, B. W., & Neely, C. J. (2014). The evolution of Federal Reserve policy and the impact of monetary policy surprises on asset prices. Federal Reserve Bank of St. Louis Review, 96(1), 73–109.

    Google Scholar 

  • Friedman, M. (1962). Should there be an independent monetary authority? In L. B. Yeager (Ed.), In search of a monetary constitution. Cambridge: Harvard University Press.

    Google Scholar 

  • Funke, N., & Matsuda, A. (2006). Macroeconomic news and stock returns in the United States and Germany. German Economic Review, 7(2), 189–210.

    Article  Google Scholar 

  • Gidofalvi, G. (2001). Using news articles to predict stock price movements. Working Paper, Department of Computer Science and Engineering, University of California, San Diego. http://cseweb.ucsd.edu/~elkan/254spring01/gidofalvirep.pdf. Accessed 6 August 2017.

  • Groß-Klußman, A., & Hautsch, N. (2011). When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions. Journal of Empirical Finance, 18(2), 321–340.

    Article  Google Scholar 

  • Hansen, P. and Lunde, A. (2011). Forecasting volatility using high-frequency data. The Oxford Handbook of Economic Forecasting, 525–556.

  • Hansen, S., & McMahon, M. (2016). Shocking language: Understanding the macroeconomic effects of central bank communication. Journal of International Economics, 99(1), S114–S133.

    Article  Google Scholar 

  • Harris, M. N., Levine, P., & Spencer, C. (2011). A decade of dissent: Explaining the dissent voting behaviour of Bank of England members. Public Choice, 146(3–4), 413–442.

    Article  Google Scholar 

  • Hernandez-Murillo, R., & Shell, H. G. (2014). The rising complexity of the FOMC statement. Federal Reserve Bank of St. Louis Economic Synopses, 23(1), 1–2.

    Google Scholar 

  • Hillert, A., Jacobs, H., & Müller, S. (2014). Media makes momentum. Review of Financial Studies, 27(12), 3467–3501.

    Article  Google Scholar 

  • Hoeberichts, M., Tesfaselassie, M. F., & Eijffinger, S. (2009). Central bank communication and output stabilization. Oxford Economic Papers, 61(2), 395–411.

    Article  Google Scholar 

  • Hu, G. X., Pan, J., & Wang, J. (2017). Early peek advantage? Journal of Financial Economics, 126(2), 399–421.

    Article  Google Scholar 

  • Huang, W., Nakamori, Y., & Wang, S. (2005). Forecasting stock market movement direction with support vector machine. Computers & Operations Research, 32(10), 2513–2522.

    Article  Google Scholar 

  • Jansen, D. J. (2011). Does the clarity of central bank communication affect volatility in financial markets? Evidence from Humphrey-Hawkins testimonies. Contemporary Economic Policy, 29(2), 494–509.

    Article  Google Scholar 

  • Jegadeesh, N., & Wu, D. (2013). Word power: A new approach for content analysis. Journal of Financial Economics, 110(3), 712–729.

    Article  Google Scholar 

  • Karabulut, Y. (2013). Can Facebook predict stock market activity? Available at SSRN: http://www.econ.yale.edu//~shiller/behfin/2011-04-11/Karabulut.pdf. Accessed 15 July 2017.

  • Kurihara, Y. (2014). Do European central bank announcements influence stock prices and exchange rates? Journal of Applied Finance & Banking, 4(1), 1–14.

    Google Scholar 

  • Kurov, A., Sancetta, A., Strasser, G. and Wolfe, M.H. (2016). Price drift before U.S. macroeconomic news: Private information about public announcements? Working paper, No. 1901, European Central Bank. https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1901.en.pdf. Accessed 15 July 2017.

  • LeBaron, F. (2008). Central bankers in the contemporary field of power: A ‘social space’ approach. In M. Savage & K. Williams (Eds.), Remembering Elites (Vol. 56, pp. 121–144). Oxford: Blackwell Publishing.

    Google Scholar 

  • Loughran, T., & McDonald, B. (2011). When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks. Journal of Finance, 66(1), 35–65.

    Article  Google Scholar 

  • Lutz, C. (2010). The predictive power of stock market sentiment. Retrieved from http://chandlerlutz.com/uploads/pdfs/pdf2.pdf. Accessed 18 July 2017.

  • Mishkin, F. S. (2009). Is monetary policy effective during financial crises? American Economic Review, 99(2), 573–577.

    Article  Google Scholar 

  • Moritz, B. and Zimmermann, T. (2016). Tree-based conditional portfolio sorts: the relation between past and future stock returns. https://www.cfr-cologne.de/download/kolloquium/2016/MoritzZimmermann.pdf. Accessed 17 July 2017.

  • Mullainathan, S., & Spiess, J. (2017). Machine learning: An applied econometric approach. Journal of Economic Perspectives, 31(1), 87–106.

    Article  Google Scholar 

  • Nelson, D. B. (1991). Conditional heteroscedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.

    Article  Google Scholar 

  • Pain, N., Lewis, C., Dang, T.T., Jin, Y. and Richardson, P. (2014). OECD forecasts during and after the financial crisis: A post mortem. OECD Economics Department, Policy Notes, No. 23 February 2014. http://www.oecd.org/eco/outlook/OECD-Forecast-post-mortem-policy-note.pdf. Accessed 19 July 2017.

  • Reinhart, C. M., & Rogoff, K. S. (2008). Is the 2007 U.S. sub-prime financial crisis so different? An international historical comparison. American Economic Review, 98(2), 339–344.

    Article  Google Scholar 

  • Ro, S. (2012). We may have just witnessed the presence of artificial intelligence in the stock market. http://www.businessinsider.com/art-cashinarticifial-intelligence-stock-market-2012-3. Accessed 19 July 2017.

  • Rülke, J. C., & Tillmann, P. (2011). Do FOMC members herd? Economics Letters, 113(2), 176–179.

    Article  Google Scholar 

  • Savor, P., & Wilson, M. (2013). How much do investors care about macroeconomic risk? Evidence from scheduled economic announcements. Journal of Financial and Quantitative Analysis, 48(2), 343–375.

    Article  Google Scholar 

  • Schmidt, S., & Nautz, D. (2012). Central bank communication and the perception of monetary policy by financial market experts. Journal of Money, Credit and Banking, 44(2), 323–340.

    Article  Google Scholar 

  • Schwarz, K. (2010). Mind the gap: Disentangling credit and liquidity in risk spreads. Working paper, Wharton school, University of Pennsylvania. http://finance.wharton.upenn.edu/~kschwarz/Spreads.pdf. Accessed 20 July 2017.

  • Siklos, P. L. (2002). The changing face of central banking: Evolutionary trends since world war II. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Sinha, N. R. (2016). Under-reaction to news in the U.S. stock market. Quarterly Journal of Finance, 6(1), 165–187.

    Google Scholar 

  • Smales, L. A. (2013). The determinants of RBA target rate decisions: A choice modelling approach. The Economic Record, 89(287), 556–569.

    Article  Google Scholar 

  • Taylor, J. B., & Williams, J. C. (2009). A black swan in the money market. American Economic Journal: Macroeconomics, 1(1), 58–83.

    Google Scholar 

  • Tetlock, P. C. (2007). Giving content to investor sentiment: The role of media in the stock market. Journal of Finance, 62(3), 1139–1168.

    Article  Google Scholar 

  • Tetlock, P., Saar-Tsechansky, M., & Macskassy, S. (2008). More than words: Quantifying language to measure firms’ fundamentals. Journal of Finance, 63(3), 1437–1467.

    Article  Google Scholar 

  • Thomson Reuters. (2002-2016a). Thomson Reuters Tick History database. https://developers.thomsonreuters.com/thomson-reuters-tick-history-trth. Accessed 17 September 2017.

  • Thomson Reuters. (2002-2016b). Datastream database. https://developers.thomsonreuters.com/eikon-apis/datastream-web-service. Accessed 17 September 2017.

  • Tirunillai, S., & Tellis, G. J. (2012). Does chatter really matter? Dynamics of user-generated content and stock performance. Marketing Science, 31(2), 198–215.

    Article  Google Scholar 

  • Weise, C. L. (2012). Political pressures on monetary policy during the U.S. Great Inflation. American Economic Journal: Macroeconomics, 4(1), 33–64.

    Google Scholar 

  • WordNet (2018). WordNet: A lexical database for English. Available at: https://wordnet.princeton.edu/

  • Wynne, M. A. (2013). A short history of FOMC communication. Federal Reserve Bank of Dallas Economic Letter, 8(1), 1–4.

    Google Scholar 

Download references

Acknowledgements

The authors express their gratitude to the participants in the workshops organized by the University of Piraeus, Portsmouth University and Derby University. Many thanks also to Yen-Ju Hsu and to Valeri Sokolovski. Special thanks also to a reviewer of this journal, as well as to the Editor for giving us the opportunity to revise our work.

Author information

Authors and Affiliations

  1. University of Piraeus, Pireas, Greece

    Nicholas Apergis

  2. University of Derby, Derby, UK

    Nicholas Apergis

  3. Democritus University of Thrace, Komotini, Greece

    Ioannis Pragidis

Authors
  1. Nicholas Apergis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ioannis Pragidis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nicholas Apergis.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(DOCX 40 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Apergis, N., Pragidis, I. Stock Price Reactions to Wire News from the European Central Bank: Evidence from Changes in the Sentiment Tone and International Market Indexes. Int Adv Econ Res 25, 91–112 (2019). https://doi.org/10.1007/s11294-019-09721-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11294-019-09721-y

Keywords

JEL Classification

Search

Navigation