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How news affects the trading behaviour of different categories of investors in a financial market

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Listed:
  • Fabrizio Lillo
  • Salvatore Miccich�
  • Michele Tumminello
  • Jyrki Piilo
  • Rosario N. Mantegna

Abstract

We investigate the trading behaviour of a large set of single investors trading the highly liquid Nokia stock over the period 2003-2008 with the aim of determining the relative role of endogenous and exogenous factors that may affect their behaviour. As endogenous factors, we consider returns and volatility, whereas the exogenous factors are the total daily number of news articles and a semantic variable based on a sentiment analysis of the news. Linear regression and partial correlation analysis of the data show that different categories of investors are differently correlated to these factors. Governmental and non-profit organizations are weakly sensitive to news and returns or volatility, and, typically, they are more correlated with the former than with the latter. Households and companies, on the contrary, are very sensitive to both endogenous and exogenous factors, and volatility and returns are, on average, much more relevant than the number of news articles and sentiment, respectively. Financial institutions and foreign organizations are intermediate between these two cases, in terms of both the total explanatory power of these factors and their relative importance. We explicitly consider the role of overnight news and overnight returns on the successive trading activity and trading balance of the different categories of investors. We observe the role of the overnight news, which is weaker than the ones observed between synchronous variables. By performing a vector autoregression (VAR) analysis, we show that the flux of news of the previous day affects the trading activity of companies, households and foreign investors and the dynamics of volatility. VAR is not detecting any role of the lagged sentiment in the successive values of the difference between the number of buying and selling investors for each category of investors.

Suggested Citation

  • Fabrizio Lillo & Salvatore Miccich� & Michele Tumminello & Jyrki Piilo & Rosario N. Mantegna, 2015. "How news affects the trading behaviour of different categories of investors in a financial market," Quantitative Finance, Taylor & Francis Journals, vol. 15(2), pages 213-229, February.
    • Handle: RePEc:taf:quantf:v:15:y:2015:i:2:p:213-229
    DOI: 10.1080/14697688.2014.931593
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    1. John M. Griffin & Jeffrey H. Harris & Selim Topaloglu, 2003. "The Dynamics of Institutional and Individual Trading," Journal of Finance, American Finance Association, vol. 58(6), pages 2285-2320, December.
    2. Mitchell, Mark L & Mulherin, J Harold, 1994. "The Impact of Public Information on the Stock Market," Journal of Finance, American Finance Association, vol. 49(3), pages 923-950, July.
    3. Birz, Gene & Lott Jr., John R., 2011. "The effect of macroeconomic news on stock returns: New evidence from newspaper coverage," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2791-2800, November.
    4. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    5. Armand Joulin & Augustin Lefevre & Daniel Grunberg & Jean-Philippe Bouchaud, 2008. "Stock price jumps: news and volume play a minor role," Papers 0803.1769, arXiv.org.
    6. David H. Cutler & James M. Poterba & Lawrence H. Summers, 1988. "What Moves Stock Prices?," Working papers 487, Massachusetts Institute of Technology (MIT), Department of Economics.
    7. Paul C. Tetlock & Maytal Saar‐Tsechansky & Sofus Macskassy, 2008. "More Than Words: Quantifying Language to Measure Firms' Fundamentals," Journal of Finance, American Finance Association, vol. 63(3), pages 1437-1467, June.
    8. Lily Fang & Joel Peress, 2009. "Media Coverage and the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 64(5), pages 2023-2052, October.
    9. Vega, Clara, 2006. "Stock price reaction to public and private information," Journal of Financial Economics, Elsevier, vol. 82(1), pages 103-133, October.
    10. Yu, Jianfeng & Yuan, Yu, 2011. "Investor sentiment and the mean-variance relation," Journal of Financial Economics, Elsevier, vol. 100(2), pages 367-381, May.
    11. Engelberg, Joseph E. & Reed, Adam V. & Ringgenberg, Matthew C., 2012. "How are shorts informed?," Journal of Financial Economics, Elsevier, vol. 105(2), pages 260-278.
    12. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    13. Ederington, Louis H & Lee, Jae Ha, 1993. "How Markets Process Information: News Releases and Volatility," Journal of Finance, American Finance Association, vol. 48(4), pages 1161-1191, September.
    14. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    15. David Hirshleifer & James N. Myers & Linda A. Myers & Siew Hong Teoh, 2004. "Do Individual Investors Drive Post-Earnings Announcement Drift? Direct Evidence from Personal Trades," Finance 0412003, University Library of Munich, Germany.
    16. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 321-340, March.
    17. Chan, Wesley S., 2003. "Stock price reaction to news and no-news: drift and reversal after headlines," Journal of Financial Economics, Elsevier, vol. 70(2), pages 223-260, November.
    18. Brown, Gregory W. & Cliff, Michael T., 2004. "Investor sentiment and the near-term stock market," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 1-27, January.
    19. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
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