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Institutional and Individual Sentiment: Smart Money and Noise Trader Risk

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  • Schmeling, Maik

Abstract

Using a new data set on investor sentiment we show that institutional and individual sentiment proxy for smart money and noise trader risk, respectively. First, using bias-adjusted long-horizon regressions, we document that institutional sentiment forecasts stock market returns at intermediate horizons correctly, whereas individuals consistently get the direction wrong. Second, VEC models show that institutional sentiment forecasts mean-reversion whereas individuals forecast trend continuation. Finally, institutional investors take into account expected individual sentiment when forming their expectations in a way that higher (lower) expected sentiment of individuals lowers (increases) institutional return forecasts. Individuals neglect the information contained in institutional sentiment.

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Bibliographic Info

Paper provided by Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät in its series Hannover Economic Papers (HEP) with number dp-337.

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Length: 37 pages
Date of creation: May 2006
Date of revision:
Handle: RePEc:han:dpaper:dp-337

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Keywords: investor sentiment; predictive regressions; noise trader; smart money;

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Cited by:
  1. Chen, Haojun & Maher, Daniela, 2013. "On the predictive role of large futures trades for S&P500 index returns: An analysis of COT data as an informative trading signal," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 177-201.
  2. Hengelbrock, Jördis & Theissen, Erik & Westheide, Christian, 2011. "Market response to investor sentiment," CFR Working Papers 11-01, University of Cologne, Centre for Financial Research (CFR).
  3. Gębka, Bartosz & Wohar, Mark E., 2013. "International herding: Does it differ across sectors?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 23(C), pages 55-84.
  4. Menkhoff, Lukas & Rebitzky, Rafael R., 2008. "Investor sentiment in the US-dollar: Longer-term, non-linear orientation on PPP," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 455-467, June.
  5. Menkhoff, Lukas & Suwanaporn, Chodechai, 2007. "10 Years after the Crisis: Thailand's Financial System Reform," Hannover Economic Papers (HEP) dp-356, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  6. Thomas Lux, 2011. "Sentiment dynamics and stock returns: the case of the German stock market," Empirical Economics, Springer, vol. 41(3), pages 663-679, December.
  7. Singer, Nico & Dreher, Frank & Laser, Saskia, 2012. "Published stock recommendations as institutional investor sentiment in the near-term stock market," Thuenen-Series of Applied Economic Theory 121, University of Rostock, Institute of Economics.
  8. Schmeling, Maik, 2008. "Investor sentiment and stock returns: Some international evidence," Hannover Economic Papers (HEP) dp-407, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  9. Finter, Philipp & Niessen-Ruenzi, Alexandra & Ruenzi, Stefan, 2010. "The impact of investor sentiment on the German stock market," CFR Working Papers 10-03, University of Cologne, Centre for Financial Research (CFR).
  10. Thomas Lux, 2008. "Sentiment Dynamics and Stock Returns: The Case of the German Stock Market," Kiel Working Papers 1470, Kiel Institute for the World Economy.
  11. Joseph, Kissan & Babajide Wintoki, M. & Zhang, Zelin, 2011. "Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1116-1127, October.
  12. Finter, Philipp & Niessen-Ruenzi, Alexandra & Ruenzi, Stefan, 2011. "The impact of investor sentiment on the German stock market," CFR Working Papers 10-03 [rev.], University of Cologne, Centre for Financial Research (CFR).
  13. Bormann, Sven-Kristjan, 2013. "Sentiment indices on financial markets: What do they measure?," Economics Discussion Papers 2013-58, Kiel Institute for the World Economy.

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